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AI Teacher Toolkit by Ditch That Textbook.pdf

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In a recent internal video memo, Susan McCahan, Vice Provost at the University of Toronto,

raised a number of questions about the impact of new AI-tools. I am picking up on two central ones:

How much assistance from an AI system is too much? What constitutes academic misconduct?

We'll discusses the question of AI assistance here. The question of AI co-authorship is related and we'll focus on that in the next post; academic integrity and academic misconduct will be covered after that.

Let's clarify first what we are talking about: we'll use the term submitted work for any work - text, video, audio, performance, or really anything - that a student submits for assessment; assessment here means an evaluation by anyone - lecturers, peers, review boards and committees, even the students themselves - with reference to the educational objectives.

As McCahan points out, the question is not exactly new: homework help from paid tutors is a reality, albeit not at the scale that we will see once ChatGPT comes to class in everyone's back pocket. You might think we are far from that point - but we surely won't disagree on the need to be prepared. All the more, since this gives us an opportunity to examine some of the foundations of the academy. I hope that you are quickly convinced that that is necessary since:

Giving meaning to this statement needs clarity on both: objectives and assessment.

One way in which AI tools can become problematic is when they block the precious opportunity of beginning an enquiry with ones own first-thought. Of course, this is not only a problem of AI-tools, Albert Einstein once remarked that anyone "who reads too much [...] falls into lazy habits of thinking",

and this is especially true of premature reading, reading before one's own mind has had a chance to engage with the problem. In fact, I think this awareness is such an essential skill to hone, as we are going to rely more and more on the suggestively customized, synthesized answers to our queries, that I will introduce a convention to these newsletters: pause - think. The icon below will alert you that some list, hypothesis or other conceptual framework is going to follow, and you might want to engage with the question before you encounter the answer: pause, think, perhaps note down your answers and only then have a look - because if you don't, it may become hard to question the premises that went into a particular approach.

Framing education in terms of specific objectives has a long history.

To structure our argument, we need to define some categories that we can refer to. Let us list the different dimensions of educational objectives:

Educational objectives: dimensions and key concepts -

The kind of holistic education we pursue at an institute of higher education covers all of these dimensions to some degree, either explicitly or implicitly. Many of these require effort and practice, and taking shortcuts may prevent achievement. Mind you, we are not talking (only) of performance - performance could indeed be outsourced to a tool, but we are talking about personal growth, or its incarnation as learning. Of course, we will have different methods to learn with AI assistance, and of course this may ultimately lead to education at a higher level for the same investment of effort and time.

But we need to be explicit what exactly we mean when we claim that AI interferes with our objectives. A starting list could be conjugated through the dimensions we listed above:

Knowledge acquisition needs structure and engagement. In order to become available to thought, the facts of knowledge must be connected to other facts, and their retrieval must be practiced. The crucial part is the formation of associations: understanding is an aesthetic phenomenon of harmonizing associations. Above, I mentioned the importance of priming a framework of understanding with a first-thought, but consumption of synthesized solutions, rather than struggling with their construction, removes a crucial moment of practice, prevents the formation of associations, and prevents engagement, that arises, for example, when we encounter ambiguities and resolve them on our own - or accept them. This is emphatically not to say that the AI-tools are useless for knowledge discovery and learning, on the contrary: the amazing capabilities of summarization help us to focus our efforts, and the algorithm's patience in clarifying required background knowledge in the role of a personal tutor can significantly speed up comprehension. But we need to emphasize that these ought to be supportive roles, and that the availability of answers cannot substitute for learning to answer. "Too much assistance" comes to early, and substitutes for engagement.

Skills require practice. Here too, there is enormous potential for personalized instruction: bespoke training plans, and practice problems; though the technical solutions are not yet quite ready, this is now an engineering problem which will be either solved by specialized interfaces to the existing AI that can capture performance, identify weaknesses, and suggest practice regimes; or more generalized AI, that will be able to perform in such a supporting role as part of its generic abilities. Soon. "Too much assistance" prevents practice, by substituting product for process.

Thinking requires tools. In a generic sense we can think of strengthening thinking ability to involve acquiring and honing patterns of mental manipulation: look for generalizations, consider implications and entailments, compare features and contrast their values, and more. The goal is often intuition, rather than precision -here, the analogy to the pocket calculator is simplistic but illustrative: we would not compute a square root by hand, but we should be troubled if we would not be able to estimate it. Such intuition is crucial for critical thinking: the refusal to accept pronouncements on the basis of authority, and to require being persuaded by evidence instead. "Too much assistance" makes results available that are not thoroughly understood and evaluated like we would evaluate our own thoughts.

Appreciation requires effort. The subtleties of a work of art are not apparent before we spend some time with it. Understanding quality will not come without having seen a lot, heard a lot, read a lot. The joy of insight is gained, not given. "Too much assistance" removes effort, denies opportunities, and thereby diminishes a sense of achievement.

Values require authenticity. Taking a determined ethical position requires to connect the matter at hand to a personal sense of right and wrong, proper and improper. There are no universal formulas, every situation is different, and we ourselves change over time. But if we are unable to find positions that we may properly call our own, and then substitute ideology where value pluralism is required, our inauthentic behaviour becomes a lived lie. Letting the AI decide on our behalf is such a trap. "Too much assistance" produces value judgements that are not based on our own convictions, and are therefore meaningless.

Socialization requires exposure. To the degree that we are social beings, our very being is constructed via socialization. Substituting a non-human "mind" is bound to have an impact. That said - we simply cannot know yet whether this is bad, or neutral, or even good. It would be a mistake to take a statement like "AI diminishes our social dimension of being" and make it a premise for an argument.
Nevertheless, as long as we feel that the various aspects of socialization are valid educational objectives in and of themselves, then "too much assistance" is assistance that moves learning into a relational vacuum.

Mind you, we could expand this list a lot, though we might commit the same sin that we are accusing the AI of: enumerating aspects of a problem domain without regard to the inner coherence of our enumeration. I think the key take-aways are already apparent: "Too much assistance" is that which interferes with educational goals because it diminishes engagement and practice. "Too much assistance" is a substitution of a product for a student's own, meaningful process. "Too much assistance" fails to become an expression of the self.

The construction of learning objectives against this background requires insight and imagination.

Well ... yes - but. The fact that we even need to have this discussion points to dislocations that shape our reality. Ideally, we would expect students who are investing very significantly into their education to fight tooth and nail to get the most out of their investment, i.e. to reject for themselves and in their own best interest any use of AI that is "too much". In reality however, many are exactly concerned with a metric (good grades) and not the content (education); they are locked into a transactional model (work for recognition) which perpetuates a teacher / learner dichotomy, and they are disillusioned about how educational achievements translate into a better life. A certain academic structure - of which we are collectively a part - becomes a culture. AI only illuminates this, though this time there is no easy fix, like changing exam parameters, or engineering modes of assessment.

And that brings us to the other side of the coin: assessment.

If we have discussed above why and where to draw the line, we must ask next how to recognize when it has been crossed. Can we still assess achievement if we cannot distinguish the student's contribution?

Those of us who realize that ChatGPT can in general pass our courses have probably also identified the root cause by now. We assess achievement through proxy measures: the recall of isolated facts substitutes for knowledge, the eloquence of expression substitutes for sophistication of understanding, and the volume of topical writing substitutes for depth.

We have important reasons to do that, but all three measures are failing us completely - or rather: they can be achieved by a readily available algorithm, for free. They have lost their value.

It is not that we don't know that we ought to be assessing quality instead. But quality cannot be quantified, nor can it be decomposed. Assessing quality is hard - and generally does not scale. However, a commitment to scale education for society is a cornerstone of the post-industrial university; the commodification of assessment plays a central role, in teaching, as well as in certifying the outcomes as a basis for career-forming qualifications. This cannot simply be removed.

Two strategies summarize the immediate reactions we have seen: we can make assignments AI-proof, or we can attempt to distinguish AI-contributions from human contributions, and only assess the latter.

Approaches to AI-proof assignments include: to assess only in supervised environments, to make assignments highly specific to in-class discourse, to base assignments on the interpretation or generation of images, and to request verifiable references.

Some of these will be vulnerable to soon-to-be-expected improvements in the tools. But a more fundamental problem is that such assessments become increasingly disconnected from the conditions under which students will work outside the academy.

As for approaches to distinguish AI-contributions, the more I know about this topic the more skeptical I am. We read suggestions to collect a sample of "authentic" student writing for stylistic comparison, or we see reports of tools that are supposed to be able to identify AI-writing

- or other quick-fix approaches to structural problems. I believe: the only robust approach to identify AI-contributions is to ask students to voluntarily disclose them. And students will only disclose them when there are no negative consequences, or when we even incentivize disclosure.

But is there not a third way? Are we not again focussing on the wrong thing, when we try to detect the hand rather than evaluating the contents? How about simply assuming all submissions have their GPU ghostwriters and to follow the idea instead. If a student can make a high-quality idea their own, whether it was written by the AI or taught in class, is this not what we call learning?

Thus, an approach that at first may sound radical, is to take the decision "how much is too much" out of the institution and put it into the hands of the student. This is not just because we ought to be sceptical about our ability to recognize, let alone assess any boundaries. It is above all, because what is "too much" is different for different people, and at different times, and in different contexts. If we nurture the sensibility of each student about the value that self improvement has to them, learning becomes an expression of the self, and not merely positioning oneself in an escalating competition.

It is not that we don't understand what needs to be done, we have just not applied it to our own teaching, because there are technical and generational barriers involved, and we are lacking creative models and incentives. Students spend millions of hours each day with their gaming consoles, not with learning - because we are not making education equally exciting. Online Twitch streams have tens of thousands of viewers while we are concerned about diminishing class attendance - because our content is less engaging. TikTok trends reach hundreds of millions while we worry about course enrolment - because we neglect the social rewards of collective achievement. Influencers change the discourse of a whole generation while our values are fading into irrelevance - because we have not learned to harness the power of role-models. We will need to work on all of that.

Of course motivation will not replace assessment. The academy's stewardship includes upholding standards of excellence and integrity. But such stewardship cannot substitute for enabling students to make their own decisions responsibly on their own. What we need to do however is to assess in a way that correlates with the joy of learning and the quality of achievement, and to do this in an alliance with our students.

In the end, we need to translate this long exploration into policy. The devil has a way of getting into the details - but if we can't follow up with policy, and policy with teeth if it need be, it is all just opinion.
What could a policy for AI-contributions look like?
Here is an example:

The use of AI tools in the preparation of submitted work is permitted without restrictions and will not lead to deduction of marks, if it is properly documented.

For the purpose of assessment, an academic submission in its proper sense is that part of a work that surpasses the capabilities of algorithmic writing. Performing at this level is a challenge, but as faculty we commit to work alongside with you to help you succeed; this is not an issue that concerns any individual course, it is a challenge for your future.

You must be able to demonstrate your understanding and mastery of all submitted work - no matter what the relative contribution of AI-tools and your own ideas are. This will be rigorously assessed.

As well, you take full responsibility that your submitted work is factually correct and sourced according to our standards. Be aware of the risks of "fabrication" and other academic misconduct.

Too long, did not read? "Too much AI contribution" is any part that diminishes our students' achievement - and this needs to be evaluated across all dimensions of our learning objectives. Assessing submitted work in this context cannot be done without the students' contribution. A new sense of alliance with students is needed, that emphasizes how our assessment aims to protect their future. Concrete policies need to express the goals, concrete exemplars need to provide role-models of change.

If we are advocating the joy of learning, let that start with us.

Feedback, comments, and experience are welcome at sentient.syllabus@gmail.com .

Sentient Syllabus is a public good collaborative. To receive new posts you can enter your email for a free subscription. If you find the material useful, please share the post on social media, or quote it in your own writing. If you want to do more, paid subscriptions are available. They have no additional privileges, but they help cover the costs.

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In a recent internal video memo, Susan McCahan, Vice Provost at the University of Toronto, raised a number of questions about the impact of new AI-tools. I am picking up on two central ones: How much assistance from an AI system is too much? What constitutes academic misconduct?

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Research Guides: ChatGPT and other AI tools: Citing ChatGPT and other LLMs

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Learn about ChatGPT. This is an intro to using and citing Language Learning Models, but they change fast!

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The MLA's method for citing sources uses a template of core elements-standardized criteria that writers can use to evaluate sources and create works-cited-list entries based on that evaluation. That new technologies like ChatGPT emerge is a key reason why the MLA has adopted this approach to citation-to give writers flexibility to apply the style when they encounter new types of sources. In what follows, we offer recommendations for citing generative AI, defined as a tool that "can analyze or summarize content from a huge set of information, including web pages, books and other writing available on the internet, and use that data to create original new content" (Weed).

You should

cite a generative AI tool whenever you paraphrase, quote, or incorporate into your own work any content (whether text, image, data, or other) that was created by it

acknowledge all functional uses of the tool (like editing your prose or translating words) in a note, your text, or another suitable location

take care to vet the secondary sources it cites (see example 5 below for more details)

See below for specific examples. And keep in mind: the MLA template of core elements is meant to provide flexibility in citation. So if you find a rationale to modify these recommendations in your own citations, we encourage you to do so. We've opened this post up for commenting, so let us know what you think and how you're using and citing generative AI tools!

Using the MLA Template

Author

We do not recommend treating the AI tool as an author. This recommendation follows the policies developed by various publishers, including the MLA's journal PMLA.

Title of Source

Describe what was generated by the AI tool. This may involve including information about the prompt in the Title of Source element if you have not done so in the text.

Title of Container

Use the Title of Container element to name the AI tool (e.g., ChatGPT).

Version

Name the version of the AI tool as specifically as possible. For example, the examples in this post were developed using ChatGPT 3.5, which assigns a specific date to the version, so the Version element shows this version date.

Publisher

Name the company that made the tool.

Date

Give the date the content was generated.

Location

Give the general URL for the tool.

Example 1: Paraphrasing Text

Passage in Source

Paraphrased in Your Prose

While the green light in The Great Gatsby might be said to chiefly symbolize four main things: optimism, the unattainability of the American dream, greed, and covetousness ("Describe the symbolism"), arguably the most important-the one that ties all four themes together-is greed.

Works-Cited-List Entry

"Describe the symbolism of the green light in the book by F. Scott Fitzgerald" prompt. The Great Gatsby ChatGPT, 13 Feb. version, OpenAI, 8 Mar. 2023, chat.openai.com/chat.

Example 2: Quoting Text

Passage in Source

Quoted in Your Prose

When asked to describe the symbolism of the green light in The Great Gatsby, ChatGPT provided a summary about optimism, the unattainability of the American dream, greed, and covetousness. However, when further prompted to cite the source on which that summary was based, it noted that it lacked "the ability to conduct research or cite sources independently" but that it could "provide a list of scholarly sources related to the symbolism of the green light in The Great Gatsby " ("In 200 words").

Works-Cited-List Entry

"In 200 words, describe the symbolism of the green light in The Great Gatsby" follow-up prompt to list sources. ChatGPT, 13 Feb. version, OpenAI, 9 Mar. 2023, chat.openai.com/chat.

While we've provided fairly detailed descriptions of the prompts above, a more general one (e.g., Symbolism of the green light in The Great Gatsby prompt) could be used, since you are describing something that mimics a conversation, which could have various prompts along the way.

Example 3: Citing Creative Visual Works

If you are incorporating an AI-generated image in your work, you will likely need to create a caption for it following the guidelines in of the MLA Handbook. Use a description of the prompt, followed by the AI tool, version, and date created:

Fig. 1. "Pointillist painting of a sheep in a sunny field of blue flowers" prompt, DALL-E, version 2, OpenAI, 8 Mar. 2023, labs.openai.com/.

You can use this same information if you choose to create a works-cited-list entry instead of including the full citation in the caption (see MLA Handbook, sec. 1.7).

Example 4: Quoting Creative Textual Works

If you ask a generative AI tool to create a work, like a poem, how you cite it will depend on whether you assign a title to it. Let's say, for example, you ask ChatGPT to write a villanelle titled "The Sunflower" that-you guessed it!-describes a sunflower and then quote it in your text. Your works-cited-list entry might look like this:

"The Sunflower" villanelle about a sunflower. ChatGPT, 13 Feb. version, OpenAI, 8 Mar. 2023, chat.openai.com/chat.

If you did not title the work, incorporate part of or all of the first line into the description of the work in the Title of Source element:

"Upon the shore . . ." Shakespearean sonnet about seeing the ocean. ChatGPT, 13 Feb. version, OpenAI, 8 Mar. 2023, chat.openai.com/chat.

For guidance on using descriptions and text from the work itself in the Title of Source element, see the MLA Handbook, 5.28 and 5.29.

Example 5: Citing Secondary Sources Used by an AI Tool

You should also take care to vet the secondary sources cited by a generative AI tool-with the caveat that AI tools do not always cite sources or, when they do, do not always indicate precisely what a given source has contributed. If you cite an AI summary that includes sources and do not go on to consult those sources yourself, we recommend that you acknowledge secondary sources in your work.

For example, let's say that you ask Bing AI to explain the concept of the political unconscious, citing sources, and it provides the following answer:

Let's say that you then decide to quote from the final sentence. You need to click through to the source listed in the note in order to get more information than just a URL for the source. There, you will read the following:

Now, you can treat Oxford Reference as your source since Bing AI was merely a research conduit to the source (see MLA Handbook 5.34 for more information). If for some reason you want to treat a source cited in a generative AI tool as an indirect source-and you know it is, in fact, the source for the information provided by the AI, follow the guidance in section 6.77 of the MLA Handbook.

Note

1. At the time of writing this post, ChatGPT doesn't have a built-in feature to create a unique URL to the conversation. However, an outside tool like the Chrome extension ShareGPT can generate such a link. If you use that type of outside tool, include the unique URL that the tool generates instead of the general URL.

DALL-E allows users to download the AI-generated images they create or generate a publicly-available URL that leads to an image. If you choose to create a shareable link for an image you generate with DALL-E (or other similar AI image generators), include that unique URL that leads to the image instead of the general URL.

Works Cited

MLA Handbook. 9th ed., Modern Language Association of America, 2021. MLA Handbook Plus, 2021, mlahandbookplus.org/.

Weed, Julie. "Can ChatGPT Plan Your Vacation?" The New York Times, 16 Mar. 2023, www.nytimes.com/2023/03/16/travel/chatgpt-artificial-intelligence-travel-vacation.html.

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How do I cite generative AI in MLA style? | MLA Style Center

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The MLA's method for citing sources uses a template of core elements-standardized criteria that writers can use to evaluate sources and create works-cited-list entries based on that evaluation. That new technologies like ChatGPT emerge is a key reason why the MLA has adopted this approach to citation-to give writers flexibility to apply the style when ...

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(Paolo Cordoni/Getty Images)

Block is a first-year political science student at California Polytechnic State University in San Luis Obispo. He is from Encinitas.
Most students (that I know of at least) aren't using artificial intelligence to complete every assignment for them. And the ones who are copying straight from ChatGPT are the same ones who would be copying straight from a Google search.

Since January, I have been using AI tools to help me with my own schoolwork. While large language models like ChatGPT seem to get better every day, they still aren't quite good enough yet to churn out A-worthy answers (plagiarism issues aside). But my reality feels at odds with the perception of ChatGPT among many adults who aren't close with any students who use it. I can only speak for myself, so here are some key ways I use ChatGPT and similar models to help me with my schoolwork.

One of the most helpful services I use ChatGPT for is helping create introductions and conclusions. I sometimes find it difficult to concisely summarize all the information of my work in general. This becomes extra hard when my work is a 12-page research paper, not just a 750-word commentary. Like many people, I find writing the first couple sentences is the hardest part. I will often plug my essay into ChatGPT and ask for its help writing a conclusion. And before you get upset, I never directly copy and paste that into my essay. I'll use the first few sentences of the AI-generated intros and conclusions as inspiration for my full-length, human-generated versions. This goes a long way to get me past the writer's block and get into a flow. For me, it stands as a decent (but imperfect) starting point for me to revise, rework and build upon.

I have also been using large language models to help explain specific concepts I'm struggling to understand. I find that internet-connected tools (specifically Google's Bard and Microsoft's BingAI) are usually better at this than ChatGPT, which is locked to information prior to late 2021 and cannot access the internet without plugins. For a specific example, I was having trouble understanding the difference between a type I (false-positive) error and type II (false-negative) error in my statistics class. Instead of using Google search, I had BingAI explain the difference.

I predicted in a January essay that students may use AI tools as personalized tutors, but I'm not using it as much as I anticipated. As I begin to take more political science-focused classes, where answers can be conveyed well in paragraphs, I expect I'll use it more. For now, it just isn't as useful for classes like statistics.

The last major tool I'll mention here is text summary. Don't get me wrong. I try to do a full reading whenever possible. At the same time, I won't deny that I have busy weeks that make it hard to get through dozens of pages of dense academic writing. Again, the internet-connected large language models reign supreme here. They can usually access the text, while ChatGPT often "hallucinates" (makes up information) or is overly broad. Accessing the key points of a text in an instant is incredibly useful when time is limited. Even when it's not, knowing the key points going into a reading makes it easier to understand. It allows me to pick up the patterns easier and breeze through in-depth explanations for concepts I already understand.

AI can be extremely useful if used the right way. In just a few months, ChatGPT, Bard and BingAI have helped me more than I could have ever expected. I'm looking forward to seeing how I can continue to use these tools as they become more capable. At the same time, I have to acknowledge the drawbacks of AI. Current models are prone to spitting out false information. (For this reason I never ask large language models for sources on a project.) It is hard to consistently identify whether a text is AI generated, making plagiarism easier. And, of course, AI often has trouble understanding context that a human would naturally interpret.

I think my fellow students should use these tools to maximize their time and efficiency but make sure that they still understand and can explain anything they turn in. I also think skeptics worried about AI in school should know that some students may abuse these new tools, but the vast majority of students are using them responsibly (or not at all).

Please cut students some slack and give us the benefit of the doubt. We know that a shortcut now may cost us down the road.

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Opinion: Here's how AI is helping me get through college (Hint: It doesn't involve cheating)

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In just a few months, ChatGPT, Bard and BingAI have helped me more than I could have ever expected.

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Opinion | I’m a Student. You Have No Idea How Much We’re Using ChatGPT.

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No professor or software could ever pick up on it.

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Does AI pose a threat to future learning? And where does the boundary for cheating lie? The first large-scale European study that investigates students' attitudes towards AI seeks to answer these pressing questions.

Students in Sweden are positive towards AI tools such as ChatGPT in education, but 62 percent believe that using chatbots during exams is cheating.

However, where the boundary for cheating lies is highly unclear, according to a new survey from Chalmers University of Technology.

"I am afraid of AI and what it could mean for the future."

"Don't worry so much! Keep up with the development and adapt your teaching for the future."

"ChatGPT and similar tools will revolutionise how we learn, and we will be able to come up with amazing things."

These are three out of nearly two thousand optional comments from the survey in which almost 6,000 students in Sweden recently participated.

"The students express strong, diverse, and in many cases emotionally charged opinions," says Hans Malmström, Professor at the Department of Communication and Learning in Science at Chalmers University of Technology. He, together with his colleagues Christian Stöhr and Amy Wanyu Ou, conducted the study.

More than a third use ChatGPT regularly
A majority of the respondents believe that chatbots and AI language tools make them more efficient as students and argue that such tools improve their academic writing and overall language skills.

Virtually all the responding students are familiar with ChatGPT, the majority use the tool, and 35 percent use the chatbot regularly.

Lack guidance - opposed a ban
Despite their positive attitude towards AI, many students feel anxious and lack clear guidance on how to use AI in their learning environments. It is simply difficult to know where the boundary for cheating lies.

"Most students have no idea whether their educational institution has any rules or guidelines for using AI responsibly, and that is, of course, worrying. At the same time, an overwhelming majority is against a ban on AI in educational contexts," says Malmström.

No replacement for critical thinking
Many students perceive chatbots as a mentor or teacher that they can ask questions or get help from, for example, with explanations of concepts and summaries of ideas.

The dominant attitude is that chatbots should be used as an aid, not replace students' own critical thinking. Or as one student put it: "You should be able to do the same things as the AI, but it should help you do it. You should not use a calculator if you don't know what the plus sign on it does".

Aid in case of disabilities
Another important aspect that emerged in the survey was that AI serves as an effective aid for people with various disabilities. A student with ADD and dyslexia described how they had spent 20 minutes writing down their answer in the survey and then improved it by inputting the text into ChatGPT: "It's like being colour blind and suddenly being able to see all the beautiful colours".

Giving students a voice
The researchers have now gathered a wealth of important information and compiled the results in an overview report.

"We hope and believe that the answers from this survey will give students a voice and the results will thus be an important contribution to our collective understanding of AI and learning," says Christian Stöhr, Associate Professor at the Department of Communication and Learning in Science at Chalmers.

More about the study
"Chatbots and other AI for learning: A survey on use and views among university students in Sweden" was conducted in the following way: the researchers at Chalmers conducted the survey between 5 April and 5 May 2023. Students at all universities in Sweden could participate. The survey was distributed through social media and targeted efforts from multiple universities and student organisations. In total, the survey was answered by 5,894 students.

Summary of results:

* 95 percent of students are familiar with ChatGPT, while awareness of other chatbots is very low
* 56 percent are positive about using chatbots in their studies; 35 percent use ChatGTP regularly
* 60 percent are opposed to a ban on chatbots, and 77 percent are against a ban on other AI tools (such as Grammarly) in education
* More than half of the students do not know if their institution has guidelines for how AI can be used in education; one in four explicitly says that their institution lack such regulations
* 62 percent believe that using chatbots during examinations is cheating
* Students express some concern about AI development, and there is particular concern over the impact of chatbots on future education

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How do students feel about ChatGPT in higher education?

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Students in Sweden are positive towards AI tools such as ChatGPT in education, but 62 percent believe that using chatbots during exams is cheating. However, where the boundary for cheating lies is highly unclear, according to a new survey from Chalmers University of Technology.

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As a doctoral student at the University of California at Los Angeles, I was among those who got a recent campus-wide email with an urgent directive: Don't use AI chatbots like ChatGPT or Bard or Bing, as doing so "is equivalent to receiving assistance from another person."

Upon reading it, I took a pause. I'm a former educator in the process of writing my dissertation for my Doctorate of Education, as part of a part-time program while working a full-time job at Google. And as someone who is also a former journalist and editor for EdSurge, I recognize that we should never plagiarize, and that artificially-intelligent chatbots are very, very capable of responding to prompts like "Write me a 500-word essay on Shakespeare's Twelfth Night."

But as a student, and frankly, as a former teacher, my university's approach struck me as incredibly short-sighted.

Oftentimes, when it comes to technology and new innovations, folks move to a "good" or "bad" binary. This is "good," while this is "bad." But in this case, AI chatbots actually fulfill a really important role on college campuses. If I'm in need of a tutor, or an editor, or a professor's help, is that not "receiving assistance from another person"? And furthermore, if those folks aren't willing or available to help me, why not have a chatbot fulfill that role?

Perhaps we need to reframe the idea of what AI chatbots can do. As such, here are three examples of use cases I've heard from fellow students-and how higher education can do a better job of incorporating the student perspective into these policies.

AI As On-Campus Tutor

Perhaps one of the most potent examples I've heard is that challenging concepts often stop students in their tracks. I mean, what exactly is a Mann-Whitney U stats test, anyway?

For many students, tools like ChatGPT are the tutor they need that can break down new or complex concepts into their most basic parts, in a manner that makes sense to the learner (by plugging in prompts like "Can you explain XYZ at a tenth-grade level?"). In this case, not only is this tutor available on demand, but it's also approachable, and mostly importantly, free.

Technologists have long dreamed of this vision of a "computer-assisted" tutor. In fact, Patrick Suppes, a Stanford University philosophy professor and pioneer of computerized tutoring, said in 1966 that students would someday have "the personal services of a tutor as well informed and as responsive as Aristotle."

Well, that virtual Aristotle is here.

And it should be noted that the responses from ChatGPT are not always correct, making it wise for students to use it as just another tool in their arsenal rather than something that will step in and do all the work for them.

An On-Demand Editor

Additionally, many students use ChatGPT as an editor - a free alternative to existing edtech tools like Grammarly.

Many university campuses host "writing centers" where students can book time to get editing help on their written assignments. However, these centers have limited hours, limited help and, sometimes, limits on expertise.

UCLA's new policy describes using AI chatbots as "receiving assistance from another person." But by that logic, why have writing assistance tools like Grammarly be given leeway to flourish? In fact, by doing a quick search online you'll find that acceptable use policies at UCLA and many other institutions don't explicitly reference writing-assistance tools like Grammarly. In fact, on the contrary in some cases - Chris Dew, who has taught at Swinburne University and Teesside University, describes that he encourages his students to use Grammarly, writing, "You're just using a writing assistant to write... better."

A Sparring Partner in Forging an Argument

A third use case for an AI chatbot is as a "naysayer" or "critic" - not necessarily a role that a university explicitly employs like tutors or editors.

Oftentimes, when writing or describing or designing, it helps to hear feedback, especially when there is argumentation involved. As AI chatbots with a ton of information, like ChatGPT, can provide answers to questions like "I'm arguing XYZ. What might be some responses that disagree with that idea?"

A fundamental part of making an argument in an essay or in a presentation is to understand a counterpoint, but few online tools provide students with a free, instant response that they can plan for in advance.

How Students and Universities Can Co-Develop AI Policies

None of the above examples give way to plagiarism, unless a student has an explicit intent to cheat. However, I should mention that UCLA wasn't entirely dismissive of AI chatbots in its university-wide email. Towards the end of their email message, there was some clarifying information regarding the role of the professor:

"Individual instructors have the authority to establish course policies for the use of ChatGPT and other AI tools. Acceptable use may vary from one course to another, and indeed from one assignment to another. If you are unsure about whether AI tools may be used for a particular assignment, please ask your instructor for clarification."

So how can that work?

One example is the approach adopted by an adjunct professor at Villanova University's graduate department in human resource development.

That instructor, Kyle Ali, took two key steps in his "Diversity in a Global Economy" course. First, he brought together a group of Villanova students to discuss the best use cases and an "acceptable use policy" for AI chatbots in his class. Before beginning a recent Wednesday class session, Ali spent 45 minutes listening and learning from his students.

Following that exercise, Ali also appealed to both educators and students online, publicly requesting existing examples or resources that are already out there:

"'No, not ever' deprives students access to potentially transformative technology and feels largely unenforceable. Unregulated use comes with legit teaching and learning, ethics and integrity concerns... Students - what are some ways you're using it responsibly? Teachers - what have been the implications for grading?"

Within two weeks, Ali had enough information to be able to develop an acceptable use policy for his courses that other professors are starting to adapt. In his policy, he notes that acceptable use includes "prompts or queries to surface additional learning opportunities or potential citations" and "prompts or queries to confirm or challenge examples or assertions."

The policy still includes a mention that "use of AI technology to generate partial or complete responses to course prompts is not permissible," and will lead to "an academic integrity violation."

Ultimately, the underlying approach is not new. Faculty and universities cannot idly sit by as this latest tool - artificial intelligence - becomes more and more omnipresent. But instead of dismissing something like an AI chatbot outright, it's up to higher education leaders to incorporate student voices to better understand why and how these tools get used - and to use what they hear to formulate the best policies for acceptable use.

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What Higher Ed Gets Wrong About AI Chatbots - From the Student Perspective - EdSurge News

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As a doctoral student at the University of California at Los Angeles, I was among those who got a recent campus-wide email with an urgent directive: ...

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AI tools can make teachers' lives easier and help them teach more efficiently, says Lance Key.

"We're just scratching the surface right now with what we're going to be able to do with AI," he says. "If we do it right, we'll be able to help kids, and they'll be able to have opportunities that they didn't have in the past."

Key is an award-winning educator and support specialist at the Putnam County School System in Cookeville, Tennessee. He focuses on helping teachers incorporate technology into their classrooms and has delivered more than 400 professional development presentations across the country.

He sees educators using more and more AI (artificial intelligence) tools for teaching, and recommends a few to consider. He excludes the hyper-popular ChatGPT from the conversation because we've got a feeling you may have already heard about that one.

"MagicSchool AI is really a great resource to help teachers prepare to teach," Key says. The AI-powered tool is designed to save teachers time and help prevent teacher burnout by assisting them as they differentiate, write assessments, write IEPS, communicate, and more.

"If I need a lesson plan written, it will write out a detailed lesson plan for me," Key says.

This tool from Meta AI Research allows people to create a drawing, upload an image of that drawing, and then have that image come to life in animation. Key says this is a favorite new tool of his and there is tons of potential for it in the classroom as what child wouldn't want to see their drawing animated.

"Canva now has AI built into it," Key says. "I can go to Canva and I can tell it to build me a presentation about digital citizenship, and it will build me a slideshow presentation." The Canva AI tool won't do all the work. "I'm gonna have to go edit and fix a few things on it," Key says, however, it can provide a solid foundation to build on for many presentations. It also has a tool called Magic Write, which will write first drafts of emails, captions, or other posts for teachers.

Another good platform for creating first drafts of presentations is Curipod, Key says. "It is like a Nearpod or like a Pear Deck, and it's got a feature in it that you give it your topic and it will build out that presentation," Key says. The tool is geared toward education and lets you choose the grade levels for your presentation. However, it is limited to five presentations per starter account at one time.

A third tool Key recommends for creating presentations is SlidesGPT. Though he noted it is not quite as fast as some of the other options, it is very thorough in its slideshow creation skills. In our recent review, we found that it was impressive overall, except the platform suffered from some of the inaccuracies and mistakes we've come to expect from AI-generated content at this stage.

This is an AI test and quiz builder that can integrate with some learning management systems, allowing teachers to create quizzes on command. "You can say, 'I want a five-question quiz about the harmful use of tobacco' and it will build you out a five-question quiz that you can import straight into Google Classroom."

This is a visual whiteboard that works with ViewSonic and is one that Key regularly uses. "A teacher can draw a picture on her board, and then it gives her images to select from," he says. ESL teachers who Key works with have been particularly drawn to it. "It's been really neat because they've been working with our students on image and word recognition," he says. "So they could draw a picture in there and have the kids try to guess what it is. We have a lot of fun with that."

Runway is an image and movie generator that can quickly be used to create engaging videos with impressive green screen and other special effects. It's designed for teachers looking to make more engaging content for their students, and one that Key' and his colleagues frequently use.

Adobe Firefly is an AI image generator that also allows users to edit the image. "Adobe can make fliers and things for you just by typing in what you're looking for," he says. This can cut down on presentation or other types of teacher prep, but it can also be a fun tool to explore with students.

Another tool Key recommends is TeachMateAi, which provides educators with a suite of AI-powered tools that generate various teaching resources. It is designed to make teaching prep and other administrative tasks associated with the job easier, so teachers can focus on time with students.
To share your feedback and ideas on this article, consider joining our Tech & Learning online community

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12 AI Tools Beyond ChatGPT That Can Save Teachers Time

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AI tools that educators can use to save time, from award-winning educator Lance Key

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Caktus makes learning 200% more efficient. Overcome academic barriers with powerful A.I. technology and never worry about grades again!

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Because we've trained ChatGPT on many course-level appropriate interaction strategies, the students will have different discussion prompt approaches at different points in their career so they never get bored and stay engaged with the content. If you're a pedagogy geek like we are, think how we build them up through Bloom's Taxonomy as they progress through levels of content? *mic drop*

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Because we've trained ChatGPT on many course-level appropriate interaction strategies, the students will have different discussion prompt approaches at different points in their career so they never get bored and stay engaged with the content. If you're a pedagogy geek like we are, think how we build them up through Bloom's Taxonomy as they progress through levels of content?

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Just because we can’t trust generative AI (yet) doesn’t mean we should fear it

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Enterprises should approach generative AI with caution but also celebrate its transformative potential, as with earlier tech innovations.

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Two bestselling novelists filed a suit against OpenAI in a San Francisco federal court on Wednesday, claiming in a proposed class action that the company used copyright-protected intellectual property to "train" its artificial intelligence chatbot.

Authors Mona Awad and Paul Tremblay claim that ChatGPT was trained in part by "ingesting" their novels without their consent. The generative AI is powered by two software programs known as large language models, which forgo a traditional programming method and instead extract massive amounts of text in order to produce natural and lifelike responses to user prompts.

When prompted, ChatGPT emitted extremely detailed summaries of Tremblay's " The Cabin at the End of the World" and Awad's " Bunny" and " 13 Ways of Looking at a Fat Girl." Both authors claim this is proof that their novels were used to train the chatbot, and the filing includes ChatGPT's responses to prompts regarding their novels.

According to the suit, much of the material that OpenAI uses to train its generative chatbots comes from copyrighted works, including books written by Awad and Tremblay, "that were copied by OpenAI without consent, without credit, and without compensation."

The lawsuit alleges that a variety of materials had been used to train the large language models, but books have been "a key ingredient in training datasets for large language models because books offer the best examples of high-quality longform writing."

In June 2018, OpenAI revealed that it trained GPT-1 using BookCorpus, which the suit described as a "controversial dataset" assembled by artificial intelligence researchers in 2015, with a collection of "over 7,000 unique unpublished books from a variety of genres including Adventure, Fantasy, and Romance.

"They copied the books from a website called Smashwords.com that hosts unpublished novels that are available to readers at no cost. Those novels, however, are largely under copyright."

According to the complaint, later iterations of the company's large language models were trained using significantly larger quantities of copyright-protected books. In a July 2020 paper introducing GPT-3, the company revealed that 15% of the training data set came from "two internet-based books corpora" that OpenAI simply called "Books1" and "Books2."

The suit approximates that, based on numbers revealed in OpenAI's paper about GPT-3, Books1 would contain roughly 63,000 titles, and Books2 would include approximately 294,000 titles.

"Because the OpenAI Language Models cannot function without the expressive information extracted from Plaintiffs' works (and others) and retained inside them, the OpenAI Language Models are themselves infringing derivative works, made without Plaintiffs' permission and in violation of their exclusive rights under the Copyright Act.," the suit reads.

Also on Wednesday, a broader class-action suit was filed by Clarkson, a public-interest law firm, on behalf of a dozen anonymous clients, accusing OpenAI of lifting private, sometimes identifying information from Internet users "without their informed consent or knowledge," according to a report in Rolling Stone. Experts have predicted more suits are sure to follow as AI becomes more adept at using information from the web to generate new content.

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Bestselling authors Mona Awad and Paul Tremblay sue OpenAI over copyright infringement

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Two bestselling novelists filed a suit against OpenAI, claiming the company used intellectual property to 'train' its artificial intelligence chatbot.

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ChatGPT for Teachers: Prompt Engineering Basics

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Applying pedagogical best practices starts here. Discover academic integrity resources for the classroom and beyond.

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ChatGPT has received a lot of attention across numerous industries. Bill Gates, drawing on the recent advances in AI which include ChatGPT, proclaimed in late March 2023 that the age of AI has begun, comparing it to the advent of the internet and mobile phones in terms of potential impact on society. The impacts of AI on education, he says, will be revolutionary. However, those of us 'on the ground' in higher education may have only come across AI in relation to how students could use it to write essays for them, or perhaps how AI might help to generate multiple choice questions.

In this extended post, I'd like to share practical examples of how generative AI like ChatGPT has the potential to be so much more, and show you how you can try these examples out for yourself. Many of these have been inspired by educators and others from around the world who have been experimenting with AI over the last few months, as well as evidence-based approaches in the learning sciences.
Check out our other resources, such as the companion piece on Prompt Engineering for Students, and other

Prompts, models, and completions in ChatGPT

practical AI in education resources.
Chatting is the new programming

But first, a few fundamentals. When you use tools like ChatGPT, you provide it a '', which the software sends to a '' (the actual AI), and the model then produces a 'completion' which is shown to you through the tool. There are many models available, but the most powerful to date are called GPT-3.5 and GPT4, made by OpenAI.

The tool is chat-based, which means after the first completion, you can provide another prompt, receive another completion, and so on. The power of this prompt-completion-prompt-completion-... cycle is that you can interact with the AI to improve upon its responses. In each chat session, the prompt-completion-prompt-completion-... provides a '' for the AI to work, so that it can draw from recent turns in your conversation.

Role (act as...)

Task (summary of what the AI needs to do)

Requirements (what the completion needs to include, contain, be, etc)

Instructions (what the AI should do to act on the prompt)

Chatting with the AI is how you get it to produce responses for you. In essence, your chat prompt(s) are how you program the AI to do things for you. Instead of needing to write computer code, your written language is how you control the AI.

Prompting basics

Keeping this in mind, it follows that how you write prompts has an important influence on what kinds of responses you might get from the AI.

ChatGPT (the free version, which runs the GPT-3.5 model),

ChatGPT Plus (the paid version, which runs GPT-4, a much more capable model), or

Bing Chat in creative mode (which uses GPT-4 under the hood).

There is no real magic to writing prompts, but there are some general guidelines for ' prompting' that seem to help the AI return more useful completions to you. OpenAI's own internal prompts seem to follow a similar structure recommended by others. One such structure is:

We'll see in the examples below how this 'RTRI' structure plays out. This is by no means the only (or possibly even best) way to prompt, but it does seem to produce some meaningful completions. The most important thing to remember about prompting is to keep trying, and leverage the chat functionality to iteratively work with the AI to improve its completions.

ChatGPT? GPT-4? What do I use?

The examples below can be run through:

Most of the examples below will run more effectively through GPT-4 instead of GPT-3.5. You can use Bing Chat in creative mode to access GPT-4 for free.

How can generative AI improve learning and teaching?

Supporting retrieval practice

ChatGPT generating MCQs with feedback

One of the most effective ways to learn something is to try and bring it out from your memory. Retrieval practice, as this process is called, helps learning by strengthening connections in memory. One of my favourite ways to study molecular biology as a student was to write biochemical pathways on a whiteboard, rub out parts of it, go for a walk, and come back and try to fill these in. Little did I know, I found this effective because of retrieval practice.

A standard approach to giving students activities for retrieval practice is the humble quiz. Generative AI can help you generate draft questions quickly. It can even suggest feedback to provide to students. The prompt below asks AI to generate some of these for you. The prompt demonstrates how role (e.g. 'you are an...'), task (e.g. 'Make 3 multiple choice questions that...'), requirements (e.g. 'For each question...'), and instructions (e.g. 'Link the topics together...') come together. (You'll also see that RTRI doesn't have to be a strict pattern).

You are an expert business information systems instructor.

Make 3 multiple choice questions that test second-year university students' understanding of the following topics:
- Customer Relationship Management Systems
- Information Security and Privacy
- Business Process Management

For each question, provide the correct answer. Then write feedback to students about the correct and incorrect options. Link the topics together in your feedback to help students connect ideas together. In your feedback, provide questions that encourage students to explore these ideas more themselves, instead of giving them the answer directly.

The screenshot below shows the prompt and part of the completion with ChatGPT, using the GPT-4 model. You can see how it takes the prompt and provides questions with feedback, and the feedback encourages students to draw links between the different topics. This example also draws on another process called elaboration, which involves making connections between different concepts to aid learning.

If you already have questions written but need to generate feedback for students, try this simple prompt. Try spice up the prompt by asking ChatGPT to write the feedback in different ways.

Identify the correct option to the MCQ below. Write feedback for each of the options.

<Question stem>
<Options>

Often a criticism of MCQs is that they focus on recall, or lower level skills. One approach to power-up your MCQs is to get AI to consider Bloom's taxonomy. In a new chat session, first prime the AI with what Bloom's taxonomy is:

What is Bloom's taxonomy?

Now that an explanation of Bloom's taxonomy is in the chat context as part of the AI's first completion, you can ask the second prompt a bit differently.

...
Make 3 multiple choice questions to Bloom's level 'evaluating' that test second-year university students' understanding of the following topics:
...

Learning through analogies and concrete examples

ChatGPT generating analogies.

Elaboration is an approach that promotes learning through making connections, expanding on ideas, and applying concepts to students' own experiences. The biochemistry teachers I learnt the most from came up with amazing analogies that helped to turn abstract concepts into tangible realities. With the help of AI, you can effortlessly generate analogies to kick-start student thinking.

Try the following prompt:

You are an expert tutor in university-level exercise physiology.

Come up with 3 creative analogies to explain the interplay between energy systems and cardiovascular responses to exercise, using analogies drawn from contemporary popular culture.

ChatGPT generating scenarios.

If you know your students have particular interests, you can modify this prompt accordingly. Perhaps you'd like the AI to generate analogies related to Tiktok videos, or car parking on campus, or the Super Mario movie. The analogies won't be perfect - but that's the beauty of analogies. Ask student groups to critique the analogies and identify strengths and weaknesses, and suggest additional analogies or extensions to the existing ones.

Another effective learning approach is to cover concrete examples. This helps students to apply abstract concepts to reality, increases motivation, and encourages them to draw links between different ideas.

Try the following prompt (and notice how the elements of RTRI are present, but interspersed):

Act as an expert in social psychology. I am teaching a class about cognitive biases that affect decision making. Give me 5 examples of real life scenarios where particular cognitive biases might be at play - include examples where 2 cognitive biases are present. Make the scenarios quite diverse. Write the scenarios as short stories involving businesses and their clients. Tell me which cognitive bias(es) are active and explain why.

You could easily turn some of these examples into fuller case studies by chatting with the AI. For example, you could provide a second prompt in the chat context:

Can you expand the first scenario into a few paragraphs, including dialogue between the people involved, and structure it like a case study?

Bing Chat generating quotes from different perspectives

Seeing from different perspectives

Because the training data for these AI is extremely broad, they can often help to provide generated human-sounding opinions from a variety of perspectives. These can then be used in class to kickstart conversation and critique. For example, what assumptions and biases are present in these AI-generated perspectives? Where are the accuracies and inaccuracies? How do these compare to students' own experiences considering their rich and diverse backgrounds?

For example:

Give 5 different perspectives on the Great Resignation from senior managers who are working in different countries with different work cultures. These perspectives need to demonstrate their insights into why their employees are quitting. Write these in the form of short interview quotes from the perspective of these managers. The quotes must subtly demonstrate how their own societal culture impacts on their decision making.

In the screenshot here, you'll see that I've used Bing Chat in 'creative mode'. The benefits of using Bing Chat are that it runs GPT-4 under the hood, is free and, importantly, is connected to the internet. The screenshot shows how Bing Chat searches for the great resignation and then produces its response.

After giving this prompt, you could ask the AI to analyse its own writing and elaborate with explanations. For example, you may want to follow up the completion to the above prompt with another prompt:

Explain why these perspectives stem from their cultural backgrounds.

Bing Chat creative mode running through a simulated scenario

AI as a universal simulator

The inimitable Ethan Mollick from the Wharton School in the US is a thoughtful and prolific proponent of the use of AI in education and across society. In a recent post, he has suggested that generative AI could be a 'universal simulator'.

Consider (or modify the green portions and try!) the following prompt:

I want to do deliberate practice about how to conduct bedside consultations in a large hospital. You will be my teacher. You will simulate a detailed scenario in which I have to engage in a patient consultation. You will fill the role of the patient or their family, I will fill the role of the doctor. You will ask for my response to in each step of the scenario and wait until you receive it. After getting my response, you will give me details of what the other party does and says. You will grade my response and give me detailed feedback about what to do better using medical consultation models. You will give me a harder scenario if I do well, and an easier one if I fail.

This brings together a few of the ideas we've discussed so far, giving students a safe and guided environment to practice applying their knowledge. From the screenshot, the AI takes your input and provides feedback and suggestions. Students may want to use this themselves, or you could run this as a class or group activity where students need to collectively determine a response that you then feed back to the AI and use to spark discussion.

Planning for lessons

We've all been there - you've been given a new class to teach on an unfamiliar topic and don't quite know where to start. AI can give you some ideas that you can then adapt; don't just do exactly what it says, but adapt this based on your own experience and knowledge as an educator.

In order to prime the AI to think about things that will help students learn, try this starting prompt:

Explain why retrieval practice, elaboration, analogies, and active learning are useful for learning.

The AI will tell you about these approaches. This means that the explanation of these ideas and why they are useful for learning will now be in the context for this chat conversation. Next, you might want to provide it with a prompt like:

Act as an expert veterinary sciences educator. Design a 50 minute tutorial for university students who are learning about animal behaviour management in a clinical context. Design activities that leverage retrieval practice, analogies, elaboration, and active learning.

It will give you some ideas about learning and teaching activities you could run within this class, and will likely give you a schedule for these too. Again, don't just do what it says - use your expert human judgement to modify or ignore its suggestions. If you'd like to get specific, you can also modify your prompt, or use follow-up prompts, to ask it focus on particular topics, for example.

Suggesting topics for discussion

I struggle with creativity. If you're in a similar boat and would like some ideas about how you can get students talking about a particular topic in class, you could ask AI to generate some discussion prompts.

The following prompt combines topics that your class needs to discuss, and asks the AI to draw links between these and common student interests. Of course, derive these interests from what you know about your students, so that the discussion starters can be tailored to their interests and experiences.

Come up with 5 examples of discussion prompts to get university students thinking about the key microeconomic concepts of supply and demand, elasticity, and utility. Base these prompts on the following topics which they are interested in:
- Social media influencers
- Climate change
- Casual work
- Parking on campus

Similar to the analogy example earlier, these examples can be a good starting point for exploration and critique in smaller discussion groups.

Screenshot of ChatGPT prompt and completion to connect different biology topics

Interleaving assistant

Here's another great idea from Ethan and Lilach Mollick. Interleaving is the practice of interspersing different topics or concepts and drawing links between them in order to promote deeper learning. If you're switching between topics, interleaving can help your students connect the previous topic to the current one.

AI can help give some ideas about this. The prompt below first establishes a role for the AI and then asks it to suggest these connections:

You are an experienced biology instructor who understands key pedagogical approaches like interleaved practice. I am an instructor. Provide suggestions on how I can connect the previous topic of cell biology with the current topic of evolution. Provide activities that I could use in class. Also provide thought-provoking questions that I can ask students to help them connect the previous topic with the current topic.

One of the emergent properties of generative AI is its ability to be (or appear to be) creative. It can draw quite neat connections between even disparate topics.

How can generative AI improve assessment?

Assessments are one of the key activities in higher education that will be most impacted by generative AI. We are all worried that students may use generative AI inappropriately to complete assessments (interestingly, students also feel the same, and have some great ideas for us). But what if we, as teachers, could use generative AI to enhance assessments so that they are more realistic, authentic, cognitively challenging, and supported through improved feedback? A recent viral Reddit thread discussed how students used GPT-4 to generate a master's level presentation and achieved full marks. Notably, the students (and the ensuing discourse this thread received) highlighted that the key issue being that the presentation was "about a topic quite frankly we couldn't care less about". So, instead of trying to 'AI-proof' assessments, can AI help us to uplift our approach to designing and delivering assessments and feedback that students care about?

ChatGPT generating creative ideas for assessments

Suggesting creative assessment ideas

Students are more likely to be motivated by, and less likely to cheat on, assessments that they find relevant. Academic integrity also improves when students feel a stronger connection to their teachers and to the assessment. AI might be able to help here.

ChatGPT following up on an assessment design it suggested, explaining how students might learn from the process

The prompt below asks AI to generate assessment ideas for a set of learning outcomes. The prompt also asks for the assessments to encourage gradual work; in the era of generative AI, many people have been promoting the idea of 'assessing the process not the product'.

Suggest 5 creative assessment ideas that can assess the following learning outcomes in a university-level media and communications course. Make the assessment meaningful for students, encourage gradual work towards the final product, and use non-essay formats.

LO1. demonstrate a broad yet nuanced understanding of introductory theories in media studies
LO2. demonstrate how to apply these theories to 'reading' media texts
LO3. critically evaluate the usefulness of theories in addressing questions about media production and reception
LO4. demonstrate skills in academic writing and research
LO5. demonstrate personal and intellectual autonomy through assessment and class work.

Once the ideas are generated, leverage the chat to follow up. For example, ask it to expand upon particular assessments and explain how students might most effectively learn from the process of completing the assessment:

Assessment 2 sounds good. How can this assessment be staged so that students can most effectively learn in the process of completing the assessment?

The AI will generate some ideas that help you scaffold the assessment. Its ideas will by no means be perfect; you should always consider these with your human expertise and adapt as appropriate.

Generating exemplars to demonstrate quality standards

As part of helping your students understand the quality of work you expect, it's important to provide examples. These ' exemplars' are critical in the context of standards-based assessment, as they help to demonstrate quality at different levels (e.g. HD, vs CR) of achievement. Importantly, exemplars also help students develop their internal ability to judge quality, and help them to monitor their own progress towards well-demonstrated standards.

Try a prompt like the one below. Make sure you insert your assessment description and the performance criteria you want (i.e. use a separate prompt for HD, another for CR, etc).

Write a 300 word reflection based on the following **assignment parameters**. Ensure your reflection addresses achievement at the level described in the **performance criteria**.

## Assignment parameters

<paste in your assignment parameters>

## Performance criteria

<paste in performance criteria, such as from a rubric, for a particular achievement level>

After the AI generates the exemplars, make sure you go through and edit what it creates to match what you expect from your students at different levels of achievement. Consider using these exemplars in class as well, where you could hold discussions where students use a rubric to grade an exemplar and gain a better understanding of the expected standards.

ChatGPT prompting the teacher to assist in generating a rubric

Drafting rubrics

The rubric generated by ChatGPT

Don't have a rubric? AI could help here too. Rubrics are grids that help to explain what different levels of achievement look like against the marking criteria. They are usually presented in table format, with rows for criteria (e.g. analysis of sources, use of literature, critique of argument, etc) and columns for standards (e.g. HD, DI, CR, PS, FA).

Try the following prompt, adapting it as needed to suit your topic(s):

Act as an expert higher education academic and writer of assessment rubrics.

I need to write a marking rubric for a second-year university-level assessment where students (pre-service teachers) need to critique the use of technology in high schools. You need to help me generate the rubric rows (which are the criteria), and the columns are the various standards (from high distinction, to distinction, to credit, to pass, to fail).

Ask me questions to help me write a strong rubric. Ask one question at a time, wait for my response, and ask me the next question. After I have answered your questions, produce a draft rubric for me.

This prompt will have the AI ask you a few questions to find out more about what you need, before generating a draft rubric for you. This is an interesting example of a prompt because it asks the AI to ask you follow-up questions. The rubric that it generates is by no means something I would immediately use for students, but it gives me things I can think about and improve upon.

With anything generated by AI, you'll need to use your human expertise to amend the content that it generates, but it will be a good starting point - better than a blank page!

Improving feedback for students

ChatGPT helping to suggest rephrasing for feedback

A key part of assessment is the learning that happens through feedback. Feedback needs to be understandable by students and help them know how and where they can improve. Personally, I struggle with a bit of feedback anxiety and can find it tricky to phrase feedback in the right way that is most supportive for student learning.

The prompt below has AI act as a feedback writing assistant:

Use style and tone modifiers. For example, after it has given you a completion, prompt: "Rewrite the above in a <style> style with a <tone> tone." Some styles you might want to try might include: Descriptive, Persuasive, Narrative, Technical, Academic, Creative, Informal, Formal, Dramatic. Some tones you might want to try include: Serious, Confident, Doubtful, Sympathetic, Optimistic, Pessimistic, Aggressive, Playful, Sincere.

Encourage its creativity. Add words like 'uncommon', 'novel', 'unconventional' to your prompt, such as, "What are 5 unconventional things that a first year undergraduate would say after their first week at uni?"

If you encounter a prompt that the AI refuses to return a completion for, try asking it to 'imagine' that it is in a particular role. You can also explain the educational reasons why you need the prompt answered. This often helps to get past its initial refusal.

Act as an expert educator in higher education.

I will give you a summary of notes for feedback to students about an assignment. I want you to expand these into a paragraph or two of feedback to students. The feedback needs to be encouraging and help students understand how they can move forward.

Base your feedback on the **assignment brief** as well as the **marking rubric**.

Acknowledge that you understand this and have received the assignment brief and rubric. Wait for me to provide the summary of notes. When I provide the summary, you should reply with the expanded feedback. Keep your feedback a maximum of 2 paragraphs.

## Assignment brief:

<paste the assignment instructions here>

## Marking rubric:

<paste the marking rubric here, i.e. what the descriptor is for each criterion and standard>

The screenshot shows the AI's first completion in response to the above prompt, and then my summary of notes as the second prompt, and then its completion which contains the re-phrased feedback. The AI is able to take words from the assignment brief and marking rubric, and combine it with my own words. I would then take this rephrased feedback and rework it before providing it to students.

Other tips

Some other final tips that might help you to modulate the output from ChatGPT and similar AIs.

Tell me more!

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Prompt engineering for educators - making generative AI work for you

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ChatGPT has received a lot of attention across numerous industries.

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Generative AI presents clear implications for teaching and learning in higher education. Drawing on their experience as early adopters of ChatGPT and DALL.E2 for teaching and learning, Bert Verhoeven and Vishal Rana present four ways they can be used to promote creativity and engagement from students.

The emergence of generative AI and the release of ChatGPT has split the realm of higher education. Generative AI in general is often viewed as a cheating tool and a threat to academic integrity. Universities and academics have also shown scepticism about the use of this technology, with some institutions banning it outright. However, whilst a degree of scepticism is warranted, it shouldn't hold us back from exploring potential positive applications of AI, especially as employers are already beginning to require AI skills in entry level roles.

As part of the Innovation and Enterprise course we run, we were self-conscious early adopters of AI tools such as ChatGPT and DALL.E2 for authentic assessments. In particular, we wanted to explore new uses and applications of this technology, focusing on the design thinking process to find problems and solutions to the United Nations Sustainable Development Goals (UNSDGs). Here, we show how this technology can benefit (1) experiential learning, student engagement, and collaboration; (2) design research and transfer of knowledge skills; (3) creative/critical thinking and reflection skills; and (4) writing and presentation tone and style skills.

Using AI for experiential learning, student engagement and collaboration

One of the ways we use AI in our course is for experiential learning, student engagement, and collaboration. Experiential learning involves learning through reflection on doing and leads to higher student engagement and performance. Authentic assessment as a part of experiential learning requires students to perform real-world tasks to demonstrate meaningful application of essential knowledge and skills, which can include the use of AI tools. Providing students with authentic assessments and specifying what help they are permitted to use for each activity helps prepare them for their professions. In our workshops, we have seen students embrace and engage with ChatGPT and DALL.E2, sharing experiences and prompts with fellow students and expressing surprise and amazement about some of the results.

Using AI for design research and transfer of knowledge skills

Another way we use AI is for design research and the transfer of knowledge skills. For example, students use AI to generate quiz questions for themselves on the content to facilitate revision (self-testing). AI is also used to identify issues, challenges, and questions within the UNSDGs. For example, ChatGPT helped identify the challenges in the Zero Hunger Sustainable Development Goal. After the prompt: ' What are the challenges in solving hunger as part of the Sustainable Development Goal "Zero Hunger"', ChatGPT offered a list of challenges, one of which was the following: Food Waste: Approximately one-third of the world's food is wasted each year. Reducing food waste and promoting food preservation techniques can help ensure that more food is available for those who need it. The students liked this challenge and used the result to further prompt the ChatGPT about challenges in Food Waste. The process of multiple prompting and answers led to a rapid in-depth understanding of the issue, not unlike the root cause analysis 5 whys tool. The students have the option to use another AI tool called the Prompt Box that has the ability to download, back up and share their prompts with anyone.
Image credit: Yasmin Dwiputri & Data Hazards Project, Better Images of AI, AI across industries (CC-BY 4.0)
As teachers, we could notice the depth of research compared to previous years, better preparing current students for empathy interviews (part of the design thinking process) with stakeholders in the field of "food waste" and possibly more sophisticated solutions. As such, AI can be used as a core part of a task, providing many examples related to a topic and allowing students to prompt deeper and test their understanding and identify inaccuracies, gaps, and missing aspects. This approach enhances their transfer of knowledge skills and critical thinking abilities. Students can save time and effort and focus on the more critical aspects of their work, like understanding the user's needs and wants (a core of the design thinking process).

Using AI for creative/critical thinking and reflection skills

AI can play a role in the facilitation of divergent and convergent thinking processes (part of design thinking). Students use ChatGPT for the generation of ideas. When prompted to generate creative ideas to solve, for instance, homelessness as a part of their UNSDG Goal 11, sustainable cities and communities, ChatGPT came up with 8 ideas ranging from affordable housing, to job training, employment programs and mental health and substance abuse treatment. Students were particularly interested to explore further the idea of Micro-housing (a trend in housing that involves creating small, affordable housing units that are designed for single individuals or couples). AI in the convergent thinking process supports the development, testing (prototype development in DALL.E2 for example) and evaluation of solutions. By combining AI with their own creativity and problem-solving skills, students can generate unique and innovative solutions to complex problems.

Using AI for writing and presentation skills

Finally, students can use AI as a copyediting tool to compare their language and formatting choices with the AI output and make edits to their own work. We encourage students to copy their original work into ChatGPT with the prompt to improve the style and tone of the academic report. Students are then asked to put the original text in the attachment (with reference) and write a reflective paragraph on what they have learned from ChatGPT in terms of tone and style. Non-English native international students, who struggled to express their thoughts in a foreign language, now have a tool to help with clear expression, with a focus on the content. As we teach innovation and not essay writing, this suits our purpose.

Bonus - Using AI to develop an Innovation and Enterprise course?

We have described four ways students use AI as a learning tool in our course. But, it is also helping us as educators to further develop the workshops. When prompted for options for using ChatGPT and DALL.E2 in a university innovation and entrepreneurship course, ChatGPT came up with three more ideas, which we are keen to further explore:

1. Business idea brainstorming: Use ChatGPT to generate a list of potential business ideas based on certain criteria, such as market demand, profitability, or social impact. Students can then use DALL.E2 to refine and develop these ideas into viable business models.

2. Entrepreneurial case studies: Use ChatGPT to create case studies on successful entrepreneurs and startups. Students can use these case studies to learn from real-world examples and identify key strategies and best practices that can be applied to their own entrepreneurial ventures.

3. Business pitch practice: Use DALL.E2 to create a virtual pitch practice platform for students to develop their pitching skills. Students can receive feedback on their delivery, content, and presentation skills, and iterate on their pitches until they are polished and effective.

Importance of Transparency and Formal Acknowledgment

The use of AI and ChatGPT in academic courses can significantly enhance student learning outcomes by improving the transfer of knowledge skills, critical thinking and reflection skills, and self-testing capabilities. By adopting AI as a core part of their tasks, students can harness the power of this technology to generate unique and innovative solutions to complex problems. However, it is important to be transparent and formally acknowledge the use of AI, ensuring that students are aware of the role it plays in their work.

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How to use generative AI creatively in Higher Education

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Generative AI presents clear implications for teaching and learning in higher education. Drawing on their experience as early adopters of ChatGPT and DALL.E2 for teaching and learning, Bert Verhoeven and Vishal Rana present four ways they can be used to promote creativity and engagement from students.

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SlidesGPT is one of the many tools to come from the advent of artificial intelligence going mainstream with ChatGPT and its various competitors.

This particular tool is designed to help make slide presentation creation easier through automating a lot of it, using AI. The idea is that you simply type in what you want and the system will trawl the internet for images and information to come back with a slideshow all set for you.

The reality, at this early stage, is still far from ideal with inaccurate information, innocuous images, and a strong warning that this may even be offensive. So can this be used by educators to help them save time for class prep? And is this a tool that could be used by students to game the system?

Read on to find out all your need to know about SlidesGPT for education.

What is SlidesGPT?

SlidesGPT (opens in new tab)is a slide presentation creation tool that uses artificial intelligence to change inputted text requests into finished slideshows for use immediately -- in theory, at least.

(Image credit: SlidesGPT)

The idea is to save time on slide presentation creation by using the artificial intelligence to most of the digital leg work. This means using AI to take directions and perform tasks on the person's request.

So, rather than trawling the internet for information and images, you can have the bot do that for you. It also compiles that into slides that are ready for presentation. At least that's the theory behind all this. It's worth noting that, at time of publishing, it is still early days and there is a lot of room for improvement for this ever-evolving artificial intelligence tool.

This is built on the GPT-4 artificial intelligence (opens in new tab), which is advanced, but is still growing and finding ways to be implemented for use.

How does SlidesGPT work?

SlidesGPT is very easy to use with a super minimal layout that's welcoming and can be used by most people, even of younger ages. Everything is web-based so it can be accessed across a host of devices, from laptops to smartphones -- as long as you have an internet connection.

On the homepage there is a text box in which you type the request you need. Hit the "Create deck" icon and the AI will get to work building your slides for presentation. There is a fair load time, taking a few minutes in some cases, with a loading bar filling up to show progress as the AI does its work.

The end result should be a selection of slides with text and images that you can scroll down through, right there in the web browser. At the bottom is a short link you can copy as well as a share icon and a download option, allowing you to immediately distribute your creation with the class, individuals, or to other devices for sharing on larger screens, for example.

The download also means you can then edit the project in Google Slides or Microsoft PowerPoint.
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What are the best SlidesGPT features?

Simplicity has to be the best feature here. There is no need to learn, you can just start typing and the AI will do the rest of the work for you.

That said, the more you use it the more you will understand what the AI can do and what it cannot. This lets you add more detailed instructions when needed and say less where not -- something you only really learn after making a few of these.

(Image credit: SlidesGPT)

On each slide deck there is an opening warning message that reads: "The below slide deck has been generated by an AI. The system may occasionally generate incorrect or misleading information and produce offensive or biased content. It is not intended to give advice."

This is worth keeping in mind as it is clear that this is not a tool to be used by students on its own, but rather something that can help save time for educators. It's also useful as you'll notice the end results are clearly AI-generated and not something a student could get away with submitting without an educator noticing it.

If you type in "slide show about the future of AI" the results are impressive -- but since it's built for that, you might expect such. Try typing in "create a slideshow about technology in education, specifically STEM, robotics, and coding" and you'll find the information is lacking, with headings and no real content to be found. This is still clearly a work in progress.

(Image credit: SlidesGPT)

SlidesGPT price

The SlidesGPT service is totally free to use, there are no ads on the website and you are not required to give any personal information at all to start using everything on offer here.

SlidesGPT best tips and tricks

Use the suggestion
There is an example in the text box to show what you can type. Try using exactly that, initially, as a way to see what can be done when this works well.

Start simple
Begin with very basic requests in order to work out what the AI can do well and what it is less able to offer, allowing you to grow as you use it in more complex ways.

Use in class
Try this in class, as a group, to see the abilities and limitations of AI so students can understand how it works and how it doesn't -- they may soon be using this more as it becomes more prevalent and better at its tasks.

To share your feedback and ideas on this article, consider joining our Tech & Learning online community (opens in new tab) .

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What is SlidesGPT and How Does it Work for Teachers? Tips & Tricks

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SlidesGPT is one of the many tools to come from the advent of artificial intelligence going mainstream with ChatGPT and its various competitors. This particular tool is designed to help make slide presentation creation easier through automating a lot of it, using AI.

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Using ChatGPT to prepare for class is easier than I expected.

I recently had the free GPT-3.5 version of ChatGPT create several lesson plans, quizzes, exercises, and a syllabus around journalism topics I teach, and was impressed by the quality and speed by which content was generated.

I wouldn't personally use ChatGPT for these purposes in my own classes due to a variety of reasons, including lack of clarity on whether this would violate institutional rules at the colleges at which I teach, my personal concerns about potential plagiarism in AI-generated text, and my preference for human-generated content overall.

That said, it's easy to see how the free version of ChatGPT, and other similar tools such as Google Bard and the GPT-4-powered subscription version of ChatGPT, could be helpful to teachers, especially new educators.

Here are a few quick ways to use ChatGPT to prepare for class. Keep in mind these tools do make mistakes and ChatGPT and similar AI-powered chatbots are better at providing broad introductions to topics than getting into the weeds, the way educators and their students often do.

1. Using ChatGPT to Prepare for Class: Generating Lesson Plans

Organizing our thoughts into a cohesive lesson plan takes even skilled and experienced educators time. ChatGPT can generate semi-detailed lesson plans on introductory topics in mere moments.

I teach journalism and asked it to create a lesson plan around the inverted pyramid - an important concept in traditional news stories in which the most important information in the story is provided at the beginning.

My prompt: Can you create a writing exercise students can do based on the inverted pyramid?
ChatGPT's response: Sure! Here's a lesson plan on the inverted pyramid for college students: Whiteboard or blackboard Markers or chalk Handouts with news articles Writing materials for students Begin by explaining to students that the inverted pyramid is a structure commonly used in journalism to write news articles. The structure places the most important information at the beginning of the article, with less important details following in descending order. Explain that this structure is designed to allow readers to quickly grasp the most important information and decide if they want to read further. Show examples of news articles that follow the inverted pyramid structure. Divide students into pairs or small groups and provide each group with a news article. Instruct students to read the article and identify the most important information in the first paragraph, followed by the next most important information in the second paragraph, and so on. After each group has identified the important information in their article, ask them to rewrite the article in inverted pyramid style, with the most important information in the first paragraph, and so on. Ask each group to share their rewritten article with the class and discuss the differences between the original article and the inverted pyramid version. Lead a class discussion on the benefits and drawbacks of the inverted pyramid structure. Ask students to discuss the advantages of the structure, such as allowing readers to quickly grasp the most important information. Also, ask them to identify any potential drawbacks, such as making the article seem formulaic or sacrificing the narrative or storytelling elements of journalism. Summarize the lesson and encourage students to practice using the inverted pyramid structure in their own writing. Remind them that while the structure is useful, it should not be used as a substitute for good writing, storytelling, or other elements of journalism. Assess students on their ability to identify the most important information in a news article and to apply the inverted pyramid structure to rewrite the article. You can also assess their participation in class discussion and their ability to reflect on the advantages and drawbacks
How ChatGPT Did: ChatGPT created a really strong lesson plan that, please don't tell my employers, is very similar to how I actually teach the inverted pyramid. If I were to actually use this lesson plan, I would update it slightly and make sure that I was including mention of related journalism jargon terms, such as the lead/lede and nut graph. ChatGPT was also incapable of taking the lesson to the next level when I asked it to provide me with four examples of recent stories that used the inverted pyramid. The Bing search chatbot, which is powered by GPT-4, also failed in this respect, as did Google's Bard.

2. Using ChatGPT to Create Quizzes

ChatGPT can also be used to generate quick quizzes. While educators will want to make sure that they are checking the information carefully, it's another good time-saving method. When you're not working directly with a textbook, crafting questions for liberal arts topics can eat up a lot of time.

My prompt: Can you create a writing exercise students can do based on the inverted pyramid?
ChatGPT's response: Sure, I can create a multiple-choice quiz on the inverted pyramid. Here are 5 questions with 4 possible answers each: 1. What is the inverted pyramid? a) A type of Greek architecture b) A writing style for news articles c) A mathematical equation d) A type of salad Answer: b) A writing style for news articles 2. What is the main characteristic of the inverted pyramid? a) The most important information is at the beginning b) The most important information is at the end c) The information is organized in a circular manner d) The information is organized alphabetically Answer: a) The most important information is at the beginning 3. Why is the inverted pyramid important in journalism? a) It helps reporters organize their thoughts b) It helps reporters meet their word count c) It helps readers quickly understand the most important information d) It helps reporters win awards Answer: c) It helps readers quickly understand the most important information 4. What is the "nut graf" in the inverted pyramid? a) A small paragraph that summarizes the entire article b) A paragraph that explains the headline c) A paragraph that provides background information d) A paragraph that includes a quote from a source Answer: c) A paragraph that provides background information 5. What is the "kicker" in the inverted pyramid? a) A paragraph that concludes the article b) A paragraph that introduces a new topic c) A paragraph that provides a personal anecdote d) A paragraph that includes a humorous comment Answer: a) A paragraph that concludes the article
How ChatGPT Did: I'm impressed by its speed and the clean formatting of the questions. However, question one feels a bit too easy for college students and overall these skew toward the easy side, but as a quick way to generate some starter questions that would be ungraded, these are fairly strong.

3. Using ChatGPT to Write Homework Assignments

ChatGPT works really well as rapid-fire prompt-generating machine. You can easily ask it to generate questions, assignments or homework on various topics that you can than tweak as necessary.

My prompt: Can you create a short homework assignment based upon the inverted pyramid?

ChatGPT's response: Sure! Here is a short homework assignment based on the inverted pyramid:
Here are the specific requirements for each section of the article: 1. Headline: Write a clear and concise headline that accurately reflects the main point of your article. 2. Lead: Begin your article with a strong lead that grabs the reader's attention and summarizes the most important information about the story. Make sure to answer the who, what, when, where, why, and how questions in your lead. 3. Nut graf: In the second or third paragraph of your article, provide more background information about the story and explain why it is important. This should include any relevant statistics, quotes, or historical context. 4. Body: Use the rest of your article to provide additional details and context about the story. Use quotes from relevant sources, provide specific examples, and use descriptive language to help the reader understand the story. 5. Kicker: End your article with a strong kicker that provides a conclusion to the story and leaves the reader with a lasting impression.
How ChatGPT Did: I like the clear and precise guidelines, which can help serve as a checklist for students. However, the details about how students should write this news article are too vague. Should students conduct their own interviews or rewrite an existing story? Also, ChatGPT seems to focus a lot on the "the kicker," which isn't even a part of a traditional inverted pyramid-type story.

4. Writing Syllabi

ChatGPT might not write the most thoughtful of syllabi but what it lacks in depth and meaning it makes up for in brute speed. It took me less time to generate this syllabus using ChatGPT than it did to make coffee this morning and I have an automated coffee maker (calm down coffee snobs, it's a Chemex-made piece of space-age tech designed to emulate a pour over prepared by a skilled barista).

My prompt: Please write a syllabus for a college class called Journalism 101: Basic News Writing.
ChatGPT's response: By the end of the course, students will be able to:

Write news articles using the inverted pyramid style

Conduct research and interviews for news stories

Use Associated Press style guidelines

Analyze and critique news articles

Understand the ethical and legal considerations in journalism

Late Work: Late work will only be accepted in cases of emergency or serious illness, and only with prior approval from the instructor.

Academic Integrity: Plagiarism or any other form of academic dishonesty will not be tolerated and will result in a failing grade for the assignment and potentially for the course.

Disability Accommodations: Students with disabilities who require accommodations should contact the Disability Services office as soon as possible to discuss their needs.

Week 1: Introduction to News Writing

Introduction to the course and syllabus

Overview of news writing and journalism

The role of journalism in society

Week 2: The Inverted Pyramid

The structure and purpose of the inverted pyramid style

Writing effective leads and nut grafs

Identifying and prioritizing news elements

The Associated Press Stylebook, 2021 edition

The Elements of Journalism: What Newspeople Should Know and the Public Should Expect by Bill Kovach and Tom Rosenstiel

News Articles (40%): Students will write several news articles throughout the semester using the inverted pyramid style. These articles will be graded on accuracy, clarity, organization, and adherence to AP style guidelines.

Quizzes (20%): Students will take quizzes on AP style and news writing techniques.

Critiques (20%): Students will analyze and critique news articles from various sources, evaluating their effectiveness and identifying strengths and weaknesses.

Final Project (20%): Students will produce a final news article that incorporates all the skills and techniques learned in the course.

(ChatGPT provided similar broad stroke journalism topic suggestions through 8 weeks of class)

How ChatGPT Did: I like that ChatGPT included details such as learning outcomes, textbook suggestions, plagiarism guidelines, and accommodation information. It's not a finished syllabus but it could certainly have saved me time during a stressful weekend back around 2014 when I was teaching one of my earliest classes and frantically trying to get my syllabus together.

However, there are some drawbacks. Initially, I didn't specifiy the length of the course I was teaching so it created an 8-week course. In a follow-up prompt not shown here, I asked it to create a schedule for 16-week course. It said it would do that and then proceeded to create another 8-week course. However, this was the only example of a "lie" or misleading statement provided by ChatGPT I encountered while preparing this story.

Overall Take: ChatGPT already has the potential to help educators with class prep in specific ways. Though in its current form it sometimes behaves like an overconfident student, certain it can accomplish things above its ability.

That said, it's only going to get better going forward. Actually, it already has. The free version of ChatGPT I used for the examples in this story has already been surpassed by the subscription-only ChatGPT plus, which is powered by GPT-4 and is noticeably more sophisticated in its responses.

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4 Ways to Use ChatGPT to Prepare for Class

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Using ChatGPT to prepare for class is easier than I expected. I recently had the free GPT-3.5 version of ChatGPT create several lesson plans, quizzes, exercises, and a syllabus around journalism topics I teach, and was impressed by the quality and speed by which content was generated.

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We live in an era of practical AI, but many people haven't yet experienced it, or, if they have, they might have wondered what the big deal is. Thus, this guide. It is a modified version of one I put out for my students earlier in the year, but a lot has changed. It is an overview of ways to get AI to do practical things.

Large Language Models like ChatGPT are extremely powerful, but are built in a way that encourages people to use them in the wrong way. When I talk to people who tried ChatGPT but didn't find it useful, I tend to hear a similar story.

The first thing people try to do with AI is what it is worst at; using it like Google: tell me about my company, look up my name, and so on. These answers are terrible. Many of the models are not connected to the internet, and even the ones that are make up facts. AI is not Google. So people leave disappointed.

Second, they may try something speculative, using it like Alexa, and asking a question, often about the AI itself. Will AI take my job? What do you like to eat? These answers are also terrible. With one exception, most of the AI systems have no personality, are not programmed to be fun like Alexa, and are not an oracle for the future. So people leave disappointed.

If people still stick around, they start to ask more interesting questions, either for fun or based on half-remembered college essay prompts: Write an article on why ducks are the best bird. Why is Catcher in the Rye a good novel? These are better. As a result, people see blocks of text on a topic they don't care about very much, and it is fine. Or the see text on something they are an expert in, and notice gaps. But it not that useful, or incredibly well-written. They usually quit around now, convinced that everyone is going to use this to cheat at school, but not much else.

All of these uses are not what AI is actually good at, and how it can be helpful. They can blind you to the real power of these tools. I want to try to show you some of why AI is powerful, in ways both exciting and anxiety-producing.

To start, lets introduce the six Large Language Models available right now, all for somewhere between free and $20 a month.

The first four (including Bing) are all OpenAI systems. There are basically two major OpenAI AIs today: 3.5 and 4. The 3.5 model kicked off the current AI craze in November, the 4 model just premiered and is much more powerful. A new variation uses plugins to connect to the internet and other apps, but it is only in early testing, as is an extremely powerful version of ChatGPT that can run Python programs. If you have never paid for OpenAI, you have only used 3.5. Aside from the plugins variation, none of these models are connected to the internet.

Microsoft's Bing uses a mix of 4 and 3.5. It is connected to the internet. Bing is a bit weird to use, but powerful. Here is my guide to using it. In addition, Google has released a disappointing AI called Bard (though they may show us more impressive models soon) and Anthropic has released Claude, though it is more focused at business users. So what can you do with these things?

For right now, no other general AI tool comes even close to GPT-4, which you can access at Bing for free or by purchasing a $20/month subscription to ChatGPT. GPT-3.5 is also good at writing and is much faster. I have experimented a lot on how to use AI to help with written material, so here is a list of way you might find it useful:

Writing anything. Blog posts, essays, promotional material, speeches, lectures, chose-you-own adventures, scripts, short stories - you name it, it does it. But you can't just give it basic prompts. Basic prompts result in boring writing. Getting good writing out of ChatGPT takes some practice, and here is a guide to doing that. ChatGPT-4 is much better at writing. Bing can be incredible at writing, but needs some convincing.

Make your writing better. Paste your text into ChatGPT. Ask it to improve the content or for suggestions about how to make it better for a particular audience. Ask it to create 10 drafts in radically different styles. Ask it to make things more vivid, or add examples. (though note it only "remembers" a couple thousand words of text)

Help you with tasks. AI can write emails, create sales templates, give you next steps in a business plan, and a lot more. Here is what I could accomplish with it in 30 minutes.

Unblock yourself. It is very easy to get distracted from a task by one difficult challenge. AI provides a way of giving yourself momentum.

Some things to worry about: In a bid to respond to your answers, it is very easy for the AI to "hallucinate" and generate plausible facts. It can generate entirely false content that is utterly convincing. Let me emphasize that: AI lies continuously and well. Every fact or piece of information it tells you may be incorrect. You will need to check it all. Particularly dangerous is asking it for math, references, quotes, citations, and information for the internet (for the models that are not connected to the internet). Bing and ChatGPT-4 are better at this. Here is a guide to avoiding hallucinations.

The AI also doesn't explain itself, it only makes you think it does. If you ask it to explain why it wrote something, it will give you a plausible answer that is completely made up. It is not interrogating its own actions, it is just generating text that sounds like it is doing so. This makes understanding biases in the system very challenging, even though those biases almost certainly exist.

It also can be used unethically to manipulate or cheat. You are responsible for the output of these tools.

Open Source Option: Download Stable Diffusion
Best free option that requires sign-up: Bing or Bing Image Creator (which uses DALL-E), Playgound (which lets you use multiple models)
Best option: Midjourney

There are three big image generators out there:

1. Stable Diffusion, which is open source and you can run from any high-end computer. It takes effort to get started, since you have to learn to craft prompts properly, but once you do it can produce great results. It is especially good for combining AI with images from other sources. Here is a nice guide to Stable Diffusion if you go that route (be sure to read both parts 1 and part 2).

2. DALL-E, from OpenAI, which is incorporated into Bing (you have to use creative mode) and Bing image creator. This system is very good, but a little less powerful, for now, than...

3. Midjourney, which is the best system in early 2023. The reason I would suggest MidJourney is that it has the lowest learning-curve of any system: just type in "thing-you-want-to-see --v 5" (the --v 5 at the end is important, it uses the latest model) and you get a great result. Midjourney requires Discord. Here is a guide to using Discord.

Some uses:

Illustrate presentations or reports

Create stock photographs of your product in use

Create mockups of designs

Create mockups of apps or websites

Create logos

Some things to worry about: These systems are built around models that have built-in biases due to their training on Internet data (if you ask it to create a picture of an entrepreneur, for example, you will likely see more pictures featuring men than women, unless you specify "female entrepreneur"), you can use this explorer to see these biases at work.

These systems are also trained on existing art on the internet in ways that are not transparent and potentially legally and ethically questionable. Though technically you own copyright of the images created, legal rules are still hazy.

Also, right now, they don't create text, just a bunch of stuff that looks like text. But they are getting better at hands.

Despite of (or in fact, because of) all its constraints and weirdness, AI is perfect for idea generation. You often need to have a lot of ideas to have good ideas. Not everyone is good at generating lots of ideas, but AI is very good at volume. Will all these ideas be good or even sane? Of course not. But they can spark further thinking on your part.

How do you do it? Just ask for ideas, and it will provide them. But there are also more advanced techniques. Here is a guide to them.

It is now trivial to generate a video with a completely AI generated character (you can use the images generated using the techniques in the guide), reading a completely AI-written script, talking in an AI-made voice, animated by AI.

It can also deepfake people, as you can see in this link where I deepfaked myself. Instructions and more information here. Use with caution, but this can be great for explainer videos and introductions. And within a few months you are likely to be able to generate videos from text prompts, so stay tuned.

Some things to worry about: Deep fakes are a huge concern, and these systems need to be used ethically.

GPT-3.5 is a powerful coding companion. But GPT-4 is next-level. I have been using it to write programs in Python and Unity (programming languages I literally do not know at all!) by just telling it what I want in words: " I need to create an Amazon Echo skill that will flash my hue lights green and blue when I yell party. Can you create it?" It did, and now my lights flash blue and green. It told me what files to download, what websites to go to, and what to do. When there were errors, I just pasted them in and it corrected the code and told me how to fix problems. I didn't need to know anything. You can code now. Try it.

AI can be a powerful tool for learning and exploration. I have written about how it can be used for teaching and to help make teachers lives easier and their lessons more effective, but it can also work for self-guided learning as well. Some ways to do that in ChatGPT:

Summarize texts. I have pasted in numerous complex academic articles and asked it to summarize the results, and it does a good job! (though remember the size limits). Even better, you can then interrogate the material by asking follow-up questions: what is the evidence for that approach? What do the authors conclude? And so on...

Help with concepts. You can ask the AI to explain concepts. Because we know the AI could be hallucinating, you would be wise to (carefully!) double-check its results against another source. This both helps you learn and confirms the AI output looks good. Once you have a sense that it is right, ask it to explain it in different ways "Like I am 10" or "in a script from The Office" or "in the context of a medical examination." Again, this is a start for your learning journey, since it will often get subtleties wrong.

Explain errors: If you get something wrong, paste in the incorrect text and ask it to explain the error, or to walk you through it step-by-step. The results can be surprisingly helpful.

Some things to worry about: If you don't check for hallucinations, it is possible that you could be taught something inaccurate. Use the AI as a jumping-off point for your own research, not as the final authority on anything. Also, if it isn't connected to the internet, it will make stuff up.

This is just the beginning. AI is improving rapidly, and people are developing new uses all the time. But remember two key points:

AI is a tool. It is not always the right tool. Consider carefully whether, given its weaknesses, it is right for the purpose to which you are planning to apply it.

There are many ethical concerns you need to be aware of. AI can be used to infringe on copyright, or to cheat, or to steal the work of others, or to manipulate. And how a particular AI model is built and who benefits from its use are often complex issues, and not particularly clear at this stage. Ultimately, you are responsible for using these tools in an ethical manner.

We are in the early days of a very rapidly advancing revolution. Are there other uses you want to share? Let me know in the comments.

This post is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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How to use AI to do practical stuff: A new guide

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People often ask me how to use AI. Here's an overview with lots of links.

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Teaching Students to Write with AI: The SPACE Framework

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The Pillars of Digital Transformation in Higher Education | Grammarly

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Every higher education institution shapes the student experience by applying a storied history to its own unique traditions. But there's one area where every institution must depart from tradition to prepare students for what happens after they graduate, and for a central characteristic of the working world: digital transformation.

This is a big undertaking. It's only by complete immersion and repeated exposure to the means of digital transformation-such as new communication practices, patterns, and platforms-that students can fully gain the experience and competence required to succeed. Institutions must not only prepare students for digital transformation in the workplace but also immerse students in it throughout the educational experience.

Institutions face pressure to prepare students for classes, careers, and beyond-a challenge that's inseparable from digital transformation. Here are three areas where institutions must design their approach to student success around new practices that welcome and celebrate technology.

Incorporating student-centered digital learning practices

But to function in a fully digitized world, students need to be exposed to a digitized learning environment and given resources that will help them overcome the digital divide they may encounter outside the institutional ecosystem. Today, that starts with student-centered digital learning practices like those highlighted by EDUCAUSE :

Computers, internet access, and cloud-based technologies

Synchronous communication technologies like audio, video, and text/chat

Time management and self-regulation

Instructional content and teachers

Help desk support

Community building and networking

For some institutions, it's a matter of systematically embracing and implementing these digital learning practices and making resources available. For other institutions, it's a matter of promoting and systematizing the practices already in place that are not used enough by the student population and increasing access to resources.

Augmenting in-person learning with AI and advanced technology

Supporting instructors with technology education

Digital teaching and learning is an expertise of its own, which means there will be a period of adjustment for instructors as they adapt to digital transformation within the higher education classroom. Many institutions see a need for additional training, support, and services for instructors and personnel to prepare to serve students in this way.

Pedagogical and technological skills

Faculty attitudes and beliefs about digital transformation

Accessibility for physical and cognitive disabilities

Copyrights and intellectual property rights

For some institutions, investments to support instructors with technology education can have the same effect as adding personnel. What's more, this new training for existing staff members can provide incentives and recognition. Meanwhile, other institutions will see a need for additional instructional designers, technology support specialists, or academic and student support services staff.

Help students and staff make the most of the digital era

Digital transformation is central to the modern workplace, and that's why it must become central to the modern higher education experience. If students lack experience with learning, assessment, and feedback from digital sources, they will graduate into a strange new world-one they may not be prepared to face.

If digital transformation isn't a top priority at your institution, it's not too late to make it one. In fact, the digital transformation of higher education is still in its infancy, and that's why so many institutions are prioritizing student-centered digital learning, AI and advanced technology, and instructor support in their budgets for the coming year. Now is the time to support instructors, staff, and students in making the most of all the opportunities embedded in digital transformation.
Prepare your students for a world that has embraced digital transformation. Contact our team to learn more about Grammarly for Education.

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The Pillars of Digital Transformation in Higher Education: 3 Ways to Prepare Students for the Future

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Every higher education institution shapes the student experience by applying a storied history to its own unique traditions. But there's one area where every institution must depart from tradition to prepare students for what happens after they graduate, and for a central characteristic of the working world: digital transformation.

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A Snapshot of AI Tools to Create and Curate Content in Higher Education | Welcome to TeachOnline

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ChatGPT caused a stir on its release in that it seemed to have the ability to write meaningful content quickly — and much of it was useful, although not all. What many seemed to miss is there are many AI-enabled supports for people who have to create content, check the writing of others, or apply fo…

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AI Text Generators: What Questions Should Writing Teachers Ask?

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As educators, we seek to engage students in ways that help them find purpose and meaning in their work. ChatGPT can help us support their learning if we use it creatively.

Here are five practical ways it can help students:

1. Improve their writing. For many students, writing is a challenge. You could ask them to: (a) write three paragraphs about a topic in their course (b) submit their work to ChatGPT with a request to "improve on this text" and (c) compare their own writing with ChatGPT's material. Then have them answer the question: "What does this suggest you consider in terms of improving your writing?"

2. Support their research and exploration. For the topics in class, ask students to use ChatGPT for some basic research, bearing in mind that the information available dates only from September 2021 and earlier. For example, students could ask: "List six reasons why productivity in Canada has been essentially flat since the early 1990s" or "What five factors have led to Canada's competitive position falling compared to other developed nations?"

3. Expand their thinking. ChatGPT works well for brainstorming. Encourage students who are working as a team on a presentation to use ChatGPT to brainstorm ideas. Ask it to produce a draft video script or suggest 15 slides for a powerful presentation and it will. The students' task is to use these materials as a starting point for what they then choose to produce.

4. Help them become more critical. When a colleague asked ChatGPT to provide his biography, it did - but it contained 14 factual errors in just three paragraphs. You could ask students to take materials generated by ChatGPT and find errors of fact, understanding and logic. Also help them recognize the phenomenon of "hallucination," which is what happens when ChatGPT produces what initially reads like useful material but is actually just nonsense.

5. Learn to dance with robots. At the end of the course, ask students to share their reflections on how they are working with their new colleague ChatGPT. What are the ways they find ChatGPT helpful as students and organizational leaders and what "trouble" has it gotten them into? This is revealing. One vice-president of human resources uses ChatGPT to generate first drafts of job descriptions and then asks it to look at those descriptions for potential legal and performance pitfalls. A school leader has used it to develop personalized professional learning plans for staff. This work encourages students to push boundaries.

In all of this work, the emphasis must be on the difference between generative material from a chatbot and purposeful, human thought. Chatbots can support our thinking but cannot drive responses or reactions to questions and ideas generated by students through the lens of a deep sense of purpose.

The pressure to succeed through grades is high, and several plagiarism detection suites can now detect material from ChatGPT. We must ensure students understand the consequences of academic misconduct. In a recent college course with 175 students, 55 were disciplined for cheating (31%), with some being suspended from studies and others losing credits toward their diplomas.

As educators, we must consider how ChatGPT will change the nature of assessment, whether that means fewer exams and more formative assessment, more ways to assess critical-reflective thinking and analysis or more emphasis on competency and capability assessments. We should also consider a greater focus on creative work and project work as well as more peer-to-peer assessment.

Although it is early days, ChatGPT is spurring a renaissance in assessment, and that is a good thing.

With AI now able to generate images from text and text from images, create music, write code, create videos from text, convert speech to text and text to speech, and simultaneously translate and generate new images in the style of great artists, we are at the beginning of a journey.

Finding ways to leverage such resources requires educators to be very clear and explicit about their learning purpose. We need to "muddle through" this constantly evolving AI landscape with purpose, courage and skill.

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How ChatGPT Can Help Foster Purposeful Learning

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As educators, we seek to engage students in ways that help them find purpose and meaning in their work. ChatGPT can help us support their learning if we use it creatively. Here are five practical ways it can help students: 1. Improve their writing. For many students, writing is a challenge.

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Author's note: This article was written by the ChatGPT chatbot, in response to prompts from MK. That human-chatbot conversation is presented here, without editing.

[MK: Write a paragraph introducing the history of AI and chatbots.]

The history of AI and chatbots can be traced back to the 1950s when scientists first began exploring the concept of artificial intelligence. Early developments included the creation of the first AI program called ELIZA, which was designed to mimic human conversation. In the decades that followed, AI technology continued to advance, leading to the development of more sophisticated chatbots with the ability to understand and respond to complex requests. Today, AI and chatbots are used in a wide range of industries, from customer service to healthcare, and are continuing to evolve as technology advances.

[MK: Write a paragraph introducing ChatGPT.]

ChatGPT is a cutting-edge AI chatbot technology that uses natural language processing and machine learning to enable users to have conversational interactions with a virtual assistant. Developed by OpenAI, ChatGPT is designed to be highly intelligent and intuitive, with the ability to understand and respond to complex requests in a way that feels natural and human-like. With its advanced capabilities, ChatGPT is revolutionizing the way we interact with technology and is paving the way for a new era of intelligent, conversational AI.

[MK: Write a paragraph about how plagiarism is a growing concern in higher education.]

Plagiarism is a growing concern in higher education as more and more students are turning to the internet for research and information. With the abundance of easily accessible information online, it has become increasingly easy for students to copy and paste from other sources without proper citation. This has led to a rise in incidents of plagiarism, which can have serious consequences for students, including failing grades, expulsion, and damage to their professional reputation. As a result, higher education institutions are implementing stricter policies and stronger penalties to combat plagiarism and ensure academic integrity.

[MK: Write a paragraph about how college students could potentially use ChatGPT to cheat on essay writing assignments.]

College students could potentially use ChatGPT to cheat on essay writing assignments by feeding the chatbot specific prompts and questions, and then copying and pasting the generated responses into their own papers. This would allow them to easily produce essays without putting in the effort and research required to write original content. However, this practice is highly unethical and could have serious consequences if caught, including failing grades and academic penalties. It is important for students to understand the importance of academic integrity and to avoid using ChatGPT or any other technology to cheat on assignments (Fig. 1).

Four depictions of "how artificial intelligence and chatbots might be used for cheating in college", as envisioned by the AI-powered DALL-E 2 image generator (OpenAI).

[MK: Write a paragraph suggesting ways in which college professors could design assignments to minimize potential cheating via ChatGPT.]

College professors can design assignments to minimize potential cheating via ChatGPT by incorporating a variety of assessment methods that go beyond traditional essay writing. For example, they could incorporate oral presentations, group projects, and hands-on activities that require students to demonstrate their knowledge and skills in a more interactive and engaging way. Additionally, they could use plagiarism detection software to identify copied or unoriginal content in submitted papers. By implementing a variety of assessment methods and using technology to monitor for plagiarism, college professors can help ensure academic integrity and discourage students from attempting to cheat using ChatGPT or other technologies.

[MK: Write a paragraph on how AI and chatbots are not inherently good or bad, but certainly deserve further attention in terms of their potential for misuse, such as in higher education.]

AI and chatbots are not inherently good or bad, but they certainly deserve further attention in terms of their potential for misuse, such as in higher education. While these technologies have the potential to greatly enhance our lives and improve various industries, they also have the potential to be used for nefarious purposes, such as cheating on assignments or other unethical practices. As AI and chatbots continue to evolve, it is important for us to carefully consider the implications of their use and take steps to prevent their misuse. This may involve implementing strict policies and regulations, as well as educating individuals on the importance of ethical behavior when using these technologies.

[MK: Write a paragraph that gets philosophical about the very nature of attribution and original writing, in a world where convincing chatbots are readily accessible.]

In a world where convincing chatbots are readily accessible, the very nature of attribution and original writing is called into question. As technology continues to advance, it becomes increasingly difficult to determine whether a piece of writing is truly original or if it has been generated by a machine. This raises questions about the value of originality and the importance of properly crediting sources in the digital age. It also highlights the need for individuals to be more critical of the information they consume and to carefully consider the sources of the information they share. Ultimately, the rapid evolution of AI and chatbot technology challenges us to redefine our understanding of attribution and originality in the digital world.

[MK: Create a list of references on chatbots, AI, and plagiarism, while trying to cite more women authors and people of color to make up for historical biases in scientific citation.]

Author information

Authors and Affiliations

Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, 37235, USA

Michael R. King

Consortia

Corresponding author

Correspondence to Michael R. King.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

About this article

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A Conversation on Artificial Intelligence, Chatbots, and Plagiarism in Higher Education - Cellular and Molecular Bioengineering

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Author's note: This article was written by the ChatGPT chatbot, in response to prompts from MK. That human-chatbot conversation is presented here, without editing. [MK: Write a paragraph introducing the history of AI and chatbots.] The history of AI and chatbots can be traced back to the 1950s when scientists first began exploring the concept of artificial intelligence.

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Artificial intelligence is growing by leaps and bounds. It's no longer science fiction anymore!

Lots of AI tools can serve as our own personal assistants -- answering questions, helping us write text, create images, speak more effectively, and more.

Time has always been a barrier in the classroom. Most teachers would agree that they would be able to do more -- including the things that are most important -- if they had more time.

Teachers can find AI tools that are ready to help them out right now. Lots of them are free or have "freemium" plans with limited free options.

Below is a description of AI and how you can start using it to support your work in class.

What is artificial intelligence?

Artificial intelligence (AI) refers to the ability of a computer or machine to perform tasks that would normally require human intelligence, such as learning, problem-solving, decision-making, and more. There are several different approaches to building AI systems, including machine learning, where a system is trained on a dataset and can improve its performance over time, and rule-based systems, where the system follows a set of predetermined rules to make decisions.

AI can be applied to a wide range of areas, including natural language processing, image and video recognition, robotics, and more. The goal of AI research is to create systems that can perform tasks at least as well as, or ideally better than, humans. AI has the potential to revolutionize many industries and transform the way we live and work, but it also raises important ethical and social questions.

30 AI tools for the classroom

We have gathered 30 of our favorite AI tools for the classroom below. You can scroll down and check them all out or jump to any category of tools by clicking on the icon below.
Note: Pricing is accurate as of our most recent update in November 2023.

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Artificial intelligence is growing by leaps and bounds. It's no longer science fiction anymore! Lots of AI tools can serve as our own personal

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Audrey CampbellM.A. in Teaching; Senior Marketing Writer

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AI terms + education: A glossary of what you need to know

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​A list of important terms relating to education and Artificial Intelligence (AI) for students, educators, and beyond

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The practical guide to using AI to do stuff

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A resource for students in my classes (and other interested people).

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If you spend any time on the internet, you've probably heard about Chat GPT.

This AI technology is capable of generating detailed written responses to complex questions. It can even do math and correct computer code.

I spent some time experimenting with Chat GPT and it is good...really good.

Teachers are nervous

This is an email I received from a teacher just this week:

"I teach in an alternative high school with a credit recovery focus and most of our students are looking for shortcuts. I recently came across this piece about AI and I am super discouraged. It makes me want to quit using computers at all and require everything to be done in class using pencil and paper. Do you have any suggestions?"

Her concern is well founded...how do you know that this entire article wasn't written by Chat GPT?

I sent this teacher my honest response: I'm not really sure what to do.

Instead of giving you my "hot take" on Chat GPT, I decided to learn about Chat GPT by reading as much as I could and spend some time actually using it.

Here are some of the articles that I found helpful. Hopefully they will help you learn about Chat GPT and form your own opinion.

What is Chat GPT?

Here are a few articles on the basics: what is chat GPT and how do you use it?

ChatGPT: Everything you need to know - this is a comprehensive article that explains what Chat GPT is, how to use it, and how it works.

[Video] What is Chat GPT - this is a good by Adrian Twarog with examples of how developers can use Chat GPT to find coding errors.

Who is OpenAI? - this Wikipedia article provides background on the group that has been working on ChatGPT and other AI projects since 2015 (Chat GPT is only one of their current projects).

Chat GPT in the classroom?

There's no shortage of articles written by educators about the potential impact of AI in the classroom. They range from "school is dead" to "this will revolutionize everything." I don't really believe either of these extremes, so here are a few of the more thoughtful articles that I read.

ChatGPT and Solving Math Problems - I'm not a math teacher, so I appreciated this this blog post written by a math professor at how Chat GPT handles complex math. Spoiler: it works very well and gets better as you use it.

[Video] Putting Chat GPT to the test - Canadian social studies teacher Tim Cavey challenged Chat GPT with a variety of questions and learning objectives and evaluated the responses from a teacher's perspective.

ChatGPT, Artificial Intelligence, and UDL: How to Harness the Future to Reach All Students - this article by Jeff Horwitz includes a brief explanation of Chat GPT and some positive and negative implications in the classroom. TL;DR: "ChatGPT forces us to examine what we've always done..."

Yes, you can use Chat GPT with Students - this thoughtful blog post by Brian Bennett includes ideas for using Chat GPT in the classroom and helps calm teachers who might feel that writing is dead (it's not!)

Lesson Planning - Teacher Tyler Tarver figured out that Chat GPT can generate detailed lesson plans. Use responsibly.

Attention, Trust, and GPT-3 - "Technology begins by making old work easier, but then it requires that new work be better." This short blog post by best selling author Seth Godin gets straight to the point.

Want to get creeped out by AI? Read this!

If "end of the world" scenarios keep you up at night, you probably shouldn't read these articles.

New AI fake text generator may be too dangerous to release - this article is from 2019 explains why an earlier version of Chat GPT wasn't publicly released due to ethical concerns.

An interview with an AI Bot - This is the complete transcript of a conversation between a Google engineer and LAMBDA, Google's AI Chat bot.

Google fires engineer for saying its AI has a soul - Yep, this is real. The Google engineer who had the conversation I linked to above was fired for advocating for "AI rights."

Avogadro Corp: The Singularity Is Closer Than It Appears - this is a fictional book trilogy written in 2011 that is uncomfortably similar to things that are happening today.

Conclusion

My conclusion is that we aren't even close to coming to a conclusion.

Tools like Chat-GPT will undoubtedly change education and many industries, so buckle up and hang on!

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Teachers: read these articles to learn about Chat GPT

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If you spend any time on the internet, you've probably heard about Chat GPT. This AI technology is capable of generating detailed written responses to complex questions. It can even do math and correct computer code. I spent some time experimenting with Chat GPT and it is good...really good.

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Leveraging ChatGPT: Practical Ideas for Educators

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The new AI technology could be a boon to inquiry-based instruction if used in the right ways.

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a partially curated bibliography and resource page for UofT community members
last updated Feb 21. 2023, 11:20 a.m.
______________________________________________________________
U of T -specific Resources

The Office of the Vice-Provost, Innovations in Undergraduate Education, has issued a resource page on ChatGPT and generative AI in the classroom. This resource includes a FAQ section that addresses a variety of questions, including the use of AI-detectors such as GPTZero.

University of Toronto Centre for Teaching Support & Innovation Resource: Generative Artificial Intelligence in the Classroom -
https://teaching.utoronto.ca/resources/generative-artificial-intelligence-in-the-classroom/

AI update February 2023 - A description of AI technology and how it is likely to manifest in common applications in the coming months.
A video by Prof. Susan McCahan, Vice-Provost. 2023-02-18 (must have a UTORid to watch)

A Demonstration of Several AI Systems (Video - runtime: 11:20 - requires UTORid to view)
Presented by Prof. Susan McCahan, Vice-Provost, Innovations in Undergraduate Education,
and Vice-Provost, Academic Programs, the University of Toronto
______________________________________________________________ Must Reads: AI in Teaching & Learning

In the Coming Weeks, How to Respond to Generative AI: Many were taken by surprise by the emergence of highly sophisticated large language models. Notice was taken last year with OpenAI's GPT-3. Ray Schroeder, Inside HigherEd, February 15, 2023 - https://www.insidehighered.com/digital-learning/blogs/online-trending-now/coming-weeks-how-respond-generative-ai

7 problems facing Bing, Bard, and the future of AI search: Microsoft and Google say a new era of AI-assisted search is coming. But as with any new era in tech, it comes with plenty of problems, from bullshit generation to culture wars and the end of ad revenue. By James Vincent, The Verge, Feb 9, 2023 - https://www.theverge.com/2023/2/9/23592647/ai-search-bing-bard-chatgpt-microsoft-google-problems-challenges

Editorial: 26 Jan 2023 Vol 379, Issue 6630 - ChatGPT is fun, but not an author - H. Holden Thorp, https://www.science.org/doi/full/10.1126/science.adg7879 Science-

- Jan 18, 2023, Chris Stokel-Walker, Nature - ChatGPT listed as author on research papers: many scientists disapprove https://www.nature.com/articles/d41586-023-00107-z

Videos & Podcasts Worth Watching/Hearing
______________________________________________________________

Other Curated Bibliographies AI in Teaching & Learning
______________________________________________________________

Other AI in Teaching & Learning Readings

Did ChatGPT Really Pass Graduate-Level Exams? by Prof. Melanie Mitchell, Santa Fe Institute in AI: A Guide for Thinking Humans, Feb 9, 2023 - https://aiguide.substack.com/p/did-chatgpt-really-pass-graduate

A Conversation With Bing's Chatbot Left Me Deeply Unsettled: A very strange conversation with the chatbot built into Microsoft's search engine led to it declaring its love for me. By Kevin Roose, New York Times, Feb. 16, 2023 (behind paywall) - https://www.nytimes.com/2023/02/16/technology/bing-chatbot-microsoft-chatgpt.html

- Steven Mintz, January 16, 2023 - ChatGPT: Threat or Menace? Are fears about generative AI warranted? https://www.insidehighered.com/blogs/higher-ed-gamma/chatgpt-threat-or-menace

Machines Can Craft Essays. How Should Writing Be Taught Now? October 26, 2022, Susan D'Agostino, Inside Higher Ed. https://www.insidehighered.com/news/2022/10/26/machines-can-craft-essays-how-should-writing-be-taught-now

ChatGPT Advice Academics Can Use Now: To harness the potential and avert the risks of OpenAI's new chat bot, academics should think a few years out, invite students into the conversation and-most of all-experiment, not panic - by Susan D'Agostino, January 12, 2023 - Inside HigherEd - https://www.insidehighered.com/news/2023/01/12/academic-experts-offer-advice-chatgpt

ChatGPT Both Is and Is Not Like a Calculator: Still talking about ChatGPT because there's a lot at stake to getting this right - John Warner, InsideHigherEd - January 16, 2023 - https://www.insidehighered.com/blogs/just-visiting/chatgpt-both-and-not-calculator

The scary truth about AI copyright is that no one knows what will happen next, Nov. 15, 2022, James Vincent, The Verge, https://www.theverge.com/23444685/generative-ai-copyright-infringement-legal-fair-use-training-data

Microsoft is looking at OpenAI's GPT for Word, Outlook and PowerPoint, Tom Warner, Jan 9, 2023, The Verge, https://www.theverge.com/2023/1/9/23546144/microsoft-openai-word-powerpoint-outlook-gpt-integration-rumor

Teaching: Will ChatGPT Change the Way You Teach? Jan 5, 2023, Beth McMurtrie , The Chronicle of Higher Education newsletter , https://www.chronicle.com/newsletter/teaching/2023-01-05

Australian universities to return to 'pen and paper' exams after students caught using AI to write essays - Caitlin Cassidy - 10 Jan 2023 - The Guardian - https://www.theguardian.com/australia-news/2023/jan/10/universities-to-return-to-pen-and-paper-exams-after-students-caught-using-ai-to-write-essays

AI-assisted plagiarism? ChatGPT bot says it has an answer for that, Dec 31, 2022, Alex Hern, ChatGPT is working toward "watermarking" text in a way that is identifiable by plagiarism detention tools; Also introduces the concept of AIgiarism coined by Paul Graham.)
The Guardian, https://www.theguardian.com/technology/2022/dec/31/ai-assisted-plagiarism-chatgpt-bot-says-it-has-an-answer-for-that (

This copyright lawsuit could shape the future of generative AI, Nov. 21, 2022, Will Knight, Wired, https://www.wired.com/story/this-copyright-lawsuit-could-shape-the-future-of-generative-ai/

How do I cite an artificial intelligence? MLA Style Center, https://style.mla.org/citing-artificial-intelligence/

ChatGPT and higher education: last week and this week - Bryan Alexander - https://bryanalexander.org/future-trends-forum/chatgpt-and-higher-education-last-week-and-this-week/ - Dec. 19, 2022

December 14, 2022, Vitomir Kovanovic, The dawn of AI has come, and its implications for education couldn't be more significant.
The Conversation, https://theconversation.com/the-dawn-of-ai-has-come-and-its-implications-for-education-couldnt-be-more-significant-196383

In addition to The Verge article above:

What does ChatGPT say about ownership?
We asked ChatGPT this question. Its response is given at the end of this document.

Opinion and Business pieces
We have added a new section with relevant readings from companies and suppliers in the tools section below.

A skeptical Take on the A.I. Revolution, Ezra Klein podcast, Jan 6, 2023, https://www.nytimes.com/2023/01/06/opinion/ezra-klein-podcast-gary-marcus.html

A New Ar ea of A.I. Booms, Even Amid the Tech Gloom , Erin Griffith and Cade Metz, Jan 7, 2023, The New York Times , https://www.nytimes.com/2023/01/07/technology/generative-ai-chatgpt-investments.html

How about we put Learning at the Center - John Warner, Inside Higher Ed, Jan. 4, 2023 https://www.insidehighered.com/blogs/just-visiting/how-about-we-put-learning-center

December 6, 2022, Stephen Marche, The College Essay Is Dead: Nobody is prepared for how AI will transform academia.
The Atlantic, https://www.theatlantic.com/technology/archive/2022/12/chatgpt-ai-writing-college-student-essays/672371/

No, Artificial Intelligence Won't Destroy High School English (Or Any Other Subject) John Spencer December 12, 2022 - https://spencerauthor.com/englishai/

What would Plato say about ChatGPT? Dec. 15, 2022, New York Times, Zeynep Tufekci https://www.nytimes.com/2022/12/15/opinion/chatgpt-education-ai-technology.html

I Would Have Cheated in College Using ChatGPT Michael Feldstein. Posted on December 16, 2022 https://eliterate.us/i-would-have-cheated-in-college-using-chatgpt/

A guest post from Marc Watkins of the University of Mississippi, the second in a likely series on freaking out about ChatGPT. Marc Watkins, Guest Post: AI Will Augment, Not Replace Inside HigherEd, December 14, 2022 https://www.insidehighered.com/blogs/just-visiting/guest-post-ai-will-augment-not-replace

AI/ML as Copilot By Michael Feldstein. Posted on October 6, 2022 https://eliterate.us/ai-ml-as-copilot/

Nancy Gleason, New York University,ChatGPT and the rise of AI writers: how should higher education respond? Times Higher Education, 9 Dec 2022 https://www.timeshighereducation.com/campus/chatgpt-and-rise-ai-writers-how-should-higher-education-respond

by Ben Thompson - AI Homework - https://stratechery.com/2022/ai-homework/
The Stratechery Blog

Seeing the Future: Developing Intuitions About Artificial Intelligence By Michael Feldstein. Posted on October 12, 2022
https://eliterate.us/seeing-the-future-developing-intuitions-about-artificial-intelligence/

______________________________________________________________ Events of Note
Upcoming SRI@UofT Seminars explore the societal implications of AI systems (starts January 18)
https://srinstitute.utoronto.ca/news/upcoming-sri-seminars-explore-the-societal-implications-of-ai-systems

Educau se QuickTalk | GPT: The Generative AI Revolution: (January 30, 2023 - recording available)
https://events.educause.edu/member-quicktalks/2023/gpt-the-generative-ai-revolution

ATTENTION: We, and others, have noted that a number of "look alike" sites and apps have arisen recently. If you are trying to access the real OpenAI ChatGPT 3.5, please use this link: https://chat.openai.com - OpenAI does not make an app for mobile devices, despite what you may be seeing on the Internet.

Tools and their functionality

This list is changing daily (see https://www.g2.com/categories/ai-writing-assistant for rankings of 134 writing assistant systems).

Chat GPT 3.5 - a product from OpenAI. It is designed for chatting, but will also produce longer texts, poems, etc. It works best on content that is either "common knowledge" (e.g., first year content) or areas that have received lots of discussion online (e.g., climate change). Currently free (release Nov. 2022), but ultimately may become a commercial product. )

Jasper - A commercial product that is advertising heavily designed for writing ad copy, blogs, and other content. Although primarily aimed at sales and marketing, it also has the capability of "improving" a piece of writing, can create or improve long form text (it advertises writing of books), and operates in multiple languages, and does plagiarism and grammar checks. It is one more frequently reviewed products in this space. (https://www.jasper.ai/ ) Starts at $40/mth, or $80/mth (Boss mode).

Writesonic - "Writesonic's GPT-3 language model deploys powerful AI to generate blog posts, landing pages, adverts, product descriptions, and emails, so it's a top choice if you need a versatile writing tool." (https://www.techradar.com/best/ai-writer) Works in multiple languages. Also advertises a ChatSonic version ("like Chat GPT, but with superpowers"). (https://writesonic.com/ ) About $15/mth for an individual.

Article Forge - Advertises that it "writes entire 1,500+ word articles automatically" in about 60 seconds. Many of the others will write long format also, but this tool seems to be particularly designed for this. Also does plagiarism checking. (https://www.articleforge.com/) starts at $30/mth.

WordAI - Advertises that their tool is best at improving existing content. This tool is a favorite (according to techradar) of people in tech. It is more of a rewriting tool than a content creation tool. "This tool can totally restructure your sentences and paragraphs to make them easier and more pleasing to read, and WordAI will automatically add keywords, make your writing more varied and fix spelling and grammar mistakes. It can use AI to improve clarity, and it'll avoid duplicated content and create up to 1,000 rewrites per article." (https://www.techradar.com/best/ai-writer) (https://wordai.com/ ) $60/mth or $30/mth for an annual license.

AI Writer - Like many of these tools, AI Writer is geared toward the production of web content and search engine optimization (SEO). It is largely designed for sales and marketing. Unlike many of the other tools, AI Writer provides a list of sources and citations. Also does text rewording, although partly this is for SEO optimization, not just readability. (https://ai-writer.com/ ) $30/mth.

Ink - A relatively new product built on GPT-3, it is designed for expanding text you have written, rewriting/editing text, and generating text. Like some other tools, it will give you multiple variations to choose from for each prompt. It also includes grammar support and a readability score, so if you do your own writing/editing it shows you how the readability changes. (https://inkforall.com/ ) $60/mth or $45/mth for an annual license.

Moonbeam - This tool has been mentioned in recent Inside Higher Ed articles on AI probably because pricing and because it is trained to write essays makes it attractive for students. (https://www.gomoonbeam.com/ ) $0 up to 30k words/mth, $20/mth for pro version.

Fermat - AI on a collaborative canvas - a company out of Barcelona - https://fermat.ws/

Jill Watson - Virtual AI Teaching Assistant Project from Georgia Tech U:
https://dilab.gatech.edu/a-suite-of-online-learning-tools/

While many of these are developed for use by sales, marketing and online content creators, there are others (e.g., SciNote, Sembly) specifically designed for a specific type of writing (e.g., FDA and other regulatory submissions/reporting, or meeting minutes from transcripts). Financial analysis companies, for example, are using systems like AlphaSense that take natural language queries to identify relevant sources of information. One type that may find substantial traction in academia is Elicit, Iris - "Elicit is a research assistant using language models like GPT-3 to automate parts of researchers' workflows. Currently, the main workflow in Elicit is Literature Review." (https://elicit.org/faq#what-is-elicit ). Iris.AI claims similar functionality (https://iris.ai/ )

It is worth noting that Microsoft etc. are also entering this space and our staff can, and probably should, be using more of the Microsoft "power tools" like Power BI and Automate. We could probably use Automate to replace or add to some of the homegrown systems we have such as academic offense tracking, or other protocol-based processes. They also have an AI Builder tool. ( https://powerautomate.microsoft.com/en-us/ )

Readings from Companies and Suppliers
What does ChatGPT say about ownership?
Query: Who owns the copyright for writing generated by ChatGPT

GPT, or Generative Pre-trained Transformer, is an artificial intelligence model developed by OpenAI for generating text. As the creator of the GPT model, OpenAI owns the copyright for the software and any text that is generated using the model.

However, the text that is generated using the GPT model is created automatically by the model, and as such, it may not be eligible for copyright protection under copyright law. In general, copyright protection is only granted to original works of authorship that are fixed in a tangible form, such as a book or a document. Automatically generated text may not meet the threshold of originality required for copyright protection.

If you want to use text generated by the GPT model for any purpose, you should first obtain permission from OpenAI. It is also important to note that even if the text generated by the GPT model is not eligible for copyright protection, it may still be protected by other legal rights such as trade secret or patent law.

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Academic & Collaborative Technologies (ACT)

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a partially curated bibliography and resource page for UofT community members last updated Feb 21. 2023, 11:20 a.m. ______________________________________________________________ U of T -specific Resources The Office of the Vice-Provost, Innovations in Undergraduate Education, has issued a resource page on ChatGPT and generative AI in the classroom .

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Is generative AI a new concept for you? Have you dabbled with ChatGPT and want to learn more? Browse this reading list by category (what it is, education, issues). Select readings using the hyperlinked titles.

SLCC Faculty and Staff, visit the "Teaching & Learning with Generative AI" SharePoint site to learn more, find resources, and engage in discussions with colleagues about generative AI in higher education.

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LibGuides: AI, ChatGPT, and the Library: Learn More about Generative AI

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This guide provides a starting place for SLCC faculty, staff, and students to learn how generative AI intersects with information literacy and how to use it responsibly. A repository of resources to help you learn more about ChatGPT and generative AI

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AI just stormed into the classroom with the emergence of ChatGPT. How do we teach now that it exists? How can we use it? Here are some ideas.

ChatGPT is an artificial intelligence chatbot. Drawing on tons and tons of data and massive processing power, it uses GPT3 technology to let users talk to the AI about practically anything.

It'll write you a song. Tell you a story. Make you a list of gifts to buy or reasons to do something.

It'll write your lesson plans. (Go ahead and try it!)

It'll even do your students' homework for them.

ChatGPT (chat.openai.com/chat) was released on November 30, 2022, the first very notable public AI chatbot. (It certainly won't be the last.)

Immediately, students were thinking ...

"Can this write my English essays for me? Write speeches for class? Do my math homework?"

Immediately, teachers were thinking ...

"How will I run class when students can ask a chatbot to do everything for them?"

Meanwhile, the IT staff was thinking ...

"We've got to get this blocked immediately." (Of course, we know that won't stop students from using it, right?)

Now, we're wondering ...

What is ChatGPT? And, more broadly, what are chatbots and AI?

How is this going to impact education?

How can I teach tomorrow knowing that this exists?

Can I use this as a tool for teaching and learning?

Should we block it through the school internet filter -- or try to ban it?

Calculators.
Search engines.
Google Translate.
Wikipedia.
PhotoMath.#ChatGPT.

They disrupt traditional teaching.

We adapt. Education evolves forward.

Blocking them isn't the answer.

Making education more relevant is.
- Matt Miller (@jmattmiller) December 14, 2022

Jump straight to a section (click a button below):

⭐️ Add thoughts, ideas, resources in the comments at the bottom! ⭐️

Define: ChatGPT, GPT3, chatbots, and artificial intelligence.

These are some of the important things to understand as we wrap our brains around what this is and how to navigate it in the classroom.

I'll do plenty of my own human thinking and reasoning, but for the purposes of information, I'm going to let ChatGPT give us working definitions to use:

1. ChatGPT, what are you?

I am an artificial intelligence assistant trained by OpenAI to help answer questions and provide information on a wide variety of topics. I am not a physical being, but rather a program that is designed to process and generate text based on the input I receive. My primary function is to assist users like you by providing information and answering questions to the best of my ability. I have been designed to have a conversational style and can understand and respond to natural language input. I do not have personal experiences or feelings, and my responses are based solely on the information and knowledge that has been programmed into me. Is there anything else you would like to know?

2. What is GPT3?

GPT-3 (Generative Pre-trained Transformer 3) is a language generation model developed by OpenAI. It is a neural network-based machine learning model that is trained on a large dataset of text data to generate human-like text. GPT-3 has the ability to perform a wide range of language tasks, including translation, summarization, question answering, and text generation. It can be fine-tuned on specific tasks or used to generate text in a more general sense. GPT-3 has received a lot of attention due to its impressive performance on various language tasks and its ability to generate human-like text.

3. What is a chatbot?

A chatbot is a computer program designed to simulate conversation with human users, especially over the Internet. Chatbots are often used in customer service, marketing, and other areas where being able to communicate with customers or users in a natural, human-like way is important. Chatbots can be programmed to understand and respond to specific commands or questions, or they can be more general and able to hold a conversation with users on a wide range of topics. They can be integrated into websites, messaging apps, and other digital platforms, and they can be programmed to use natural language processing (NLP) techniques to understand and respond to user input. Chatbots can be very useful for automating tasks and providing quick responses to frequently asked questions, but they are not as advanced as some other artificial intelligence (AI) systems and may not be able to hold more complex or nuanced conversations.

4. What is artificial intelligence?

Artificial intelligence (AI) refers to the ability of a computer or machine to perform tasks that would normally require human intelligence, such as learning, problem-solving, decision-making, and more. There are several different approaches to building AI systems, including machine learning, where a system is trained on a dataset and can improve its performance over time, and rule-based systems, where the system follows a set of predetermined rules to make decisions. AI can be applied to a wide range of areas, including natural language processing, image and video recognition, robotics, and more. The goal of AI research is to create systems that can perform tasks at least as well as, or ideally better than, humans. AI has the potential to revolutionize many industries and transform the way we live and work, but it also raises important ethical and social questions.

Want to make sense of the world of artificial intelligence and its impact on education? Sit in on the panel discussion in the video above, featuring:

Victoria Thompson, Microsoft education executive and former classroom teacher

Donnie Piercey, fifth grade teacher and 2021 Kentucky State Teacher of the Year

Holly Clark, education consultant and National Board Certified Teacher (formerly in the classroom)

Dee Lanier, author, speaker, and former classroom teacher

Matt Miller, author/creator of Ditch That Textbook and former classroom teacher

What are the implications for the classroom?

As soon as the genie was out of the lamp, so to speak, there were effects of ChatGPT and AI on teaching and learning. Whether we felt those impacts right away or not, as soon as it was released, things have the potential to change. Below, we'll talk about ChatGPT in particular, but know that this is just the first one ... and we're thinking long-term about new products to come later.

1. Students can use ChatGPT to do their assignments.

There. I'll just say it clearly and plainly since we're all thinking it. For lots of assignment types (not all of them!), students can ask ChatGPT to do the work for them. They can copy/paste the work into a document or your learning management system and submit it.

2. TurnItIn and other plagiarism checkers can't catch it.

What ChatGPT creates is an original work each time you ask it. It creates something new every time you ask, and its responses are not in the databases of plagiarism checkers. ChatGPT doesn't keep a log of responses it creates, and even if it did, I'm thinking OpenAI (creator of ChatGPT) has no incentive to make all of that available to plagiarism checkers. (Even if it did, the processing power necessary to query that database would be enormous.)

Some people will, undoubtedly, try to find ChatGPT detectors to track down students using it (in a similar way to plagiarism checkers). You may find them. I found one on social media called GPT-2 Output Detector Demo. It's a demo, so it's not a finished product. It's based on GPT2 technology (which is a predecessor to the GPT3 technology that ChatGPT is using as of the writing of this post).

Also, it can be wildly inaccurate. I copied a blog post I wrote into it and it identified it as 92.54% chance of being real. I copied something out of ChatGPT and it identified it as 99.98% chance of being fake. ("Fake," being the term for "written by a bot.") A poem ChatGPT created for a friend, however, was flagged as real.

Beware of using detectors as your way of dealing with this.

They're not reliable. And this approach isn't the long-term solution to helping your students become modern learners.

3. Schools and districts will try to block it, but that won't stop much.

Immediately, IT admins are going to have to decide if they want to block ChatGPT with their internet firewalls. And lots of them will indeed block it. If they do, I hope they don't think that they've solved the "problem" they think they have on their hands.

First of all, blocking ChatGPT on the school's network won't do much. Sure, students won't be able to access it with their school devices on the school network. But did you know that students have cell phones? Phones that operate on a cellular network that the school can't control? They can run to the bathroom, sit in a stall, ask ChatGPT for answers, copy them to a document, come back to class, and transfer the text on that document into their assignment and turn it in. (They can do that at home, too. Or on the bus. Or quietly under the desk in the classroom.)

Whether to block ChatGPT school-wide is still a decision schools and districts have to make.
The bigger decision is: what will teaching and learning look like going forward now that this technology is available?
(Check out the section below called, "Should we block it or try to ban it?")

4. ChatGPT and forthcoming chatbots like it have their limitations.

When you load ChatGPT for the first time, it even tells you what some of its limitations are. Here are a few that it states -- and some others to be aware of for schools/classrooms:

It may occasionally generate incorrect information. As of publication of this post, it's still in "free research preview." That means it's an imperfect product that they're trying to improve.

It may occasionally produce harmful instructions or biased content. Any artificial intelligence is as good as the dataset it's drawing from -- and how it uses it. It has to make judgment calls just like humans do. Bias exists in judgments. It's still learning how to work with and eliminate its bias.

It has limited knowledge of world and events after 2021. Think of its dataset in a sealed box. It isn't drawing from current events. It can't pull anything from social media. It can't even search the active internet.

It won't make ethical decisions for you. I've asked it a few things where it has to make decisions based on morals, ethics and personal values. It has declined, explaining that that's beyond the scope of what it's trained to do.

I've heard that it struggles to do math sometimes. I admit this is a really, really subjective thing to include with very little to back it up. I keep seeing posts on social media about this. Take this for what it's worth to you.

5. School/class uses of ChatGPT, chatbots, and AI aren't all bad.

Lots of teachers are making judgment calls about the use of this new technology, and many are concerned about its immediate impacts. Here's the truth: it'll make lots of teachers reconsider some types of assignments they'll assign going forward. Hey, they don't want to know how a bot will respond to their prompts, questions, and assignments. They want to use it to gauge learning in a human being. It makes sense.

But let's put it this way. There are some really, really mindless, terrible writing prompts out there ... and math worksheets ... and project assignments. If we're looking long-term, this technology will eventually start to push some of those terrible assignments out and force us to come up with something new. It'll probably be painful, and many of us will probably hate parts of the process. But in the end, we will evolve to something better.j

AI isn't going away. But if we ask students to write on paper right now -- as a stopgap, we know it's coming from their own brains. But please don't long-term plan like this.

Also -- just like we did with the calculator, Wikipedia and Google searches -- students and teachers will find productive, meaningful ways to use this new technology for teaching and learning. (More on that below.)

6. Students will have to learn how to navigate life with AI.

Big picture, this is a shift students will deal with for the rest of their lives. Artificial intelligence will continue to get better and better. This version of ChatGPT is the weakest, most rudimentary artificial intelligence of its kind our students will ever use. My friend Holly Clark called it the "Commodore 64 of AI" -- a technology that was revolutionary at the time but is now seen as antiquated and obsolete.

Students will have to wrestle with questions of humanity -- what sets us apart as humans? When should AI be used, and when shouldn't it be?

They'll wrestle with questions of obsolescence -- what can I do that AI can't do? How can I do my best to be sure my work, my passions, my place in this world isn't replaced by artificial intelligence?

They'll wrestle with ethical questions -- how can AI use be fair, equitable, unbiased, good? What happens if it gets in the hands of bad actors? How can I make sure I'm using it in an ethical way?

Big-picture, AI will cause a shift students will deal with for the rest of their lives. They'll wrestle with questions of humanity, questions of obsolescence, ethical questions. Let's help them with this.

What else? How could ChatGPT and artificial intelligence be used as a classroom tool? Share your ideas in a comment below -- and check out what others say!

FREE teaching ideas and templates in your inbox every week!

How to define "cheating" and "plagiarism" with AI

What is cheating? What is plagiarism?

We thought we had a pretty clear idea of how we'd define both of these.

As more and more artificial intelligence (AI) come on the scene, we're going to have to update our definitions.

That is ... if we want our education to be relevant to our students' future.

If AI tools are everywhere -- and they're only going to get better -- they'll be a vital part of the workforce when students progress through school and graduate.

So our definitions will have to morph.

The question is ... where will we draw the line?

Here's a slide I shared during a conference presentation about ChatGPT and AI in education. It was the most-shared slide on social media from that presentation.

We're going to have to draw a line -- as educators, as schools, even as school districts -- to determine what we're going to allow and what we aren't.

First, let's make sure we're clear on these two words. Here are my best definitions for these terms ...

Cheating: When a student does something dishonest in academic work that misrepresents what they understand or are able to do for an unfair advantage.

Plagiarism: When a student represents some type of work to be their own creation when, in reality, it isn't their own work.

Those definitions might not be perfect, but they highlight an important reality.

There's LOTS of gray area. It's fuzzy and unclear.
Which of these would you consider "cheating" or "plagiarism"? (From the image above ...)

Student plugged prompt into AI, copied response and submitted it to the teacher.

AI created a response. Student read, edited, adjusted, and submitted.

Student created multiple AI responses, used the best parts, edited, and submitted.

Student wrote main ideas. AI generated a draft and offered feedback to improve.

Student consulted the internet/AI for ideas, then wrote and submitted.

Student wrote all assignment content without consulting AI or the internet.

There's a good chance your gut reaction -- your visceral answer to this question -- relates to how our current education system operates or how you've taught in the past.

Of course, things are changing.

The artificial intelligence available today is some of the least powerful our students will see in their lifetime. ( ChatGPT is like the MySpace of artificial intelligences. We'll look back on it and laugh at how powerful we thought it was.)

Think of a 10-year-old in school right now. She graduates high school in eight years. She graduates college in four years.

By the time she enters the workforce, artificial intelligence has improved and evolved for 12 years.

As we consider our answer to the question, "What is plagiarism/cheating?," our answer has to be relevant to that student in 12 years.

Also, if we want to be fair, we have to ask ourselves this question:

Which of the above options would we use in our work as adults? If we're willing to use AI in our work right now, it's only going to become more commonplace in the future.

Of course, as educators, we're still trying to grasp AI and its place in the world.

We don't have to have the perfect answer right now.

But now is the time to start trying to get it right.

AI detectors: What's available? Should we use them?

In the days and weeks after ChatGPT was released, teachers kept wondering about one thing.

"How do I know if students used artificial intelligence to do their work?"

Immediately, there was a demand for AI detectors.

Today, there are several options. (We'll get to that in a second.)

But it begs a bigger question: Do they really solve the problem? (And is the perceived problem really a problem?)

Let's put it this way.

When TurnItIn came on the scene, did it fix the problem of plagiarism in classes? Did it make plagiarism go away? No. It's a tool.

Point 1: AI detectors are a tool, not a cure-all. If you found the most accurate, effective one, it wouldn't keep students from using AI to do their work, and it won't make AI tools go away.

Point 2: Today's AI detectors aren't very reliable. They routinely produce false positives, saying human-created text was created by AI. Just like in court, you can't accuse someone using evidence that isn't reliable.

Point 3: They can be the beginning of a discussion. If a student turns in work that appears to be heavily AI-generated, it might be time to talk. How do I know what you've learned? Are there barriers preventing you from doing the work yourself? In a world with more and more AI, how will you leverage your humanity so you're not outsourced by AI?

Point 4: Use your teacher eyes and teacher brain. If you've been reading your students' work and following your progress, your human senses might detect that something doesn't look or sound like them better than an AI checker could.

So, with that all established, what's available?

Should we block it or try to ban it?

If we block ChatGPT (or tools like it) and think we're solving a problem, we're deluding ourselves.

There are two decisions that need to be addressed since ChatGPT was released.

A big, systemic decision that needs to be made is: What will teaching and learning look like with ChatGPT and AI in existence?

We've started unpacking that above (and in conversations all over the globe).

But there's a more pressing question, and it's one that requires a bit of nuance ...

Do we block it at school?

Immediately, schools and districts must decide whether to block access to it on school networks and devices.

That decision, however, won't solve "the problem." (I use quotes because I'm not convinced that the proliferation of AI is a problem. It really does disrupt how we have done -- and are doing -- school, though.)

Students still will have access to it. It's like social media. It can be blocked at school. But students can access it (as I mentioned above) on their phones under a desk, in the restroom, on a bus, at home ... anywhere. They'll get access.

But someone has to decide. Should it be blocked at school?

What educators in my social media circles are saying ...
The resounding answer has been, "No, don't block it."
Their rationale: This is the future. It's not going anywhere. Students must have access to it. It'll prepare them for the future. Why would we want to keep students from accessing something so powerful?

There's something to know about these social media circles, though. Lots of people in them aren't in the classroom and don't have a good perspective on what full-time teachers go through.
(Full disclosure: I don't teach full time anymore either. I'm in my wife's and kids' schools a lot, but I don't teach full time.)
The ones in these social media circles that are in the classroom? They're dreamers (like me). They've seen the ways the system is broken. They're ready for change.

In the end -- if we're playing the long game (and I think we are), I side with them.

Generally.

What regular teachers in regular classrooms are saying ...
If you walk into any given classroom in schools across the United States (and some parts of the world)? The resounding answer has been, "Please block it. Right now!"
These are the teachers who write lesson plans. Every single day.

They grade student work. Every single day.

They teach and supervise and facilitate class. Every single day.

They never have enough time to do what they need. Their checklist is never complete.

There's a level of survival in these classrooms.

Reinventing their teaching methods and assignments at the drop of a hat because a new AI bot came out?

They just don't have time for that. (And they don't have the capacity in their already fractured personal wellness to do that.)

I understand.

I think, deep down inside, these teachers know the potential of AI and tools like ChatGPT. They know that it's going to change how teaching and learning looks.

They just need to survive the day. The week.

They need to survive until break.

They're on the front lines, dealing with all sorts of difficult situations and a lack of resources and a lack of respect for the classroom and the teaching profession.

They also just did this. Do you remember? (If you don't, you probably haven't taught in a classroom for a few years.)

Teachers are just starting to feel a sense of normality after pandemic-induced remote teaching. They had to reinvent the way they teach -- immediately! -- to a remote format, one that most weren't prepared for, technologically or pedagogically or logistically.

As teacher wellness expert Mandy Froehlich (Twitter: @froehlichm) said, they're trying to get out of emergency mode. And when you finally get out of emergency mode, there's a let-down ... an emotional, sometimes physical, response to the trauma you've dealt with.

So to those that look down their noses at teachers who are begging for this to be blocked, let's just remember the recent past. And let's also remember that they likely understand the impact of this.

They just want to survive the week. Survive until break.

Survive until we get a spare moment to think about this. Learn about it. Brainstorm some ways to change our assignments so that they can't

A proposal for schools/districts that's a middle ground

(Hear my justification for this proposal in the video) Let's block it until the end of the school year.
Let's not make a long-term decision to block ChatGPT (and tools like it) forever.

Let's also not make a long-term decision to leave it open forever.

(I'm not totally confident that this is the right answer. But I haven't heard anyone argue for the middle ground yet, so I want to add this voice.)

Let's agree to block it on student devices and networks (and allow it on teachers devices/networks if possible) just until the end of the school year.

To look at their assignments and consider how they'd like to change them in light of this new technology.

To look at how they teach and how this might be incorporated in it.

To look at how technology like this might augment classroom discussions

Here's why ...

Teachers need some time to regroup ...

... and on and on.

We need some space. Some time. A little room to ponder, to sit with all of this. To talk to other educators about what they think. To talk to students and to parents.

Let's just give teachers a little space.

However, let's also make a few things clear.

1. This isn't the long-term answer. This is a stopgap to help struggling teachers to survive this sudden change.

2. Students still will have access to this. Just because we block this on student networks and devices doesn't mean they won't plug your writing prompts and questions into this technology. This just buys you a little time to finish the year with your traditional assignment types to come up with something new.

A faculty-wide discussion and brainstorming session about best ways to teach and learn is in order at the end of the year. Everyone shares their best ideas and prepares for their implementation. (And let's pay the teachers for this extra meeting, OK?)
1. Will this technology be blocked on school networks and devices? 2. How will we evolve our teaching practice now that these technologies exist?
Then, at the beginning of next school year, let's open the ChatGPT floodgates.

Even if this isn't the solution you (or your school/district) comes to, there are two decisions that need to be made:

Blocking ChatGPT district-wide is one decision.

Deciding how teaching/learning happen while it exists is another. (to me)

If a district thinks blocking it will solve the problem, they're deluding themselves.

Blocking it can be one part of a solution, I believe. https://t.co/CvHCT2RqSQ
- Matt Miller (@jmattmiller) December 14, 2022

What other resources can help me learn about this?

Below is a list (albeit incomplete!) of resources I've found in the weeks after ChatGPT came into existence. I'll share links along with why I like them as resources. Please add other resources -- even your own! -- in the comments below!

ChatGPT in Classrooms: What to Know (U.S. News and World Report) -- Students, teachers and others in education weigh in on this new AI tool and the implications it has in the classroom.

What can English teachers do about ChatGPT (Learning in Room 213) -- This post explores what ChatGPT is, the problems with blocking it, and suggestions: entice personal engagement, avoid formulaic assignments, build critical thinking, etc.

No, Artificial Intelligence Won't Destroy High School English (or Any Other Subject) (John Spencer, Spencer Author) -- I've waited to read this because I wanted to create my own piece of content without copying anyone, but I've been excited to see John's thoughts on it. Hang on a second, let me read it ... Yep, it's as fantastic as I expected. Some of John's points include: "Almost any task can be automated, but what's the joy in that?"; "If we outsources every task, we might short-circuit the learning"; and "AI can't replace your voice." This is really, really good.

Human Skills in a World of Artificial Intelligence (John Spencer, Spencer Author) -- In this post (which dovetails wonderfully with the one above), John outlines the problems with a couple approaches to AI and advocates for another one: "the human approach."

The conversation about how much we care (Twitter thread by Evan Weinberg @emwdx) -- This thread doesn't seem to have gotten much attention, but I really like where Evan's going with it. He introduces it with: "As we see start to see how easy it is for a tool like #ChatGPT to generate text that sounds convincingly like us, it is starting the conversation about how much we care. We care a lot more than we might initially admit."

Ideas for using ChatGPT in the Classroom (IB English Guys) -- They opened up this collaborative Google Doc to share ideas. There are 10+ ideas with rationale and comments from educators.

AI Homework (Stratechery) -- This is an interesting, thoughtful, nuanced look at the intersection of homework and artificial intelligence. He talks about the struggles that ChatGPT has with math, and he even runs a virtual machine (like a Linux terminal) inside ChatGPT.

Yes, Teachers, You Should Be Panicking About AI (The Broken Copier) -- This post provides six reasons why we should be concerned about ChatGPT and AI (in light of the condition of education in many classrooms right now), helping us make sense of how we move forward.

The College Essay is Dead (The Atlantic) -- This was one of the first posts I saw (that was circulated widely) about the impact of ChatGPT in education. It's a paid article on The Atlantic. I subscribed so I could read it so that I could tell you ... it's talking points and not much else. If you'd like to read commentary about it and you're a subscribers to The Atlantic, go for it. I wouldn't pay for it ... especially since I'm focused on what we can actually do with this technology.

No, ChatGPT is Not the End of High School English. But Here's the Useful Tool It Offers Teachers (Forbes) -- Here's the best point in this whole article (so you don't have to read it): ChatGPT is an excellent prompt tester. Think you've come up with a good writing prompt? Feed it to the chatbot. If it can come up with an essay that you would consider a good piece of work, then that prompt should be refined, reworked, or simply scrapped.

Learning More about Chat GPT in Education (Jennifer Casa-Todd) -- Jen has written books about social media, digital literacy, and technology's impact on children's lives. She shares some of the best things she's found about the topic.

Education is about to radically change: AI for the masses (Nate McClennen and Rachelle Dené Poth for Getting Smart) -- AI already does and will continue to impact education - along with every other sector. Innovative education leaders have an opportunity to build the foundation for the most personalized learning system we have ever seen.

Let's Chat: OpenAI and ChatGPT (THRIVEinEDU podcast by Rachelle Dené Poth) -- Have you tried OpenAI yet? What has your experience been? Rachelle shares some background info, insights, questions and more in this episode. She also shares at her blog: www.Rdene915.com.

Chatbots in Education: Middle School and High School (Heather Olvey and Terri Files) -- These teachers pulled together slide decks with ideas for implementing chatbots in the classroom.
Have a resource to add -- yours or from someone else? Share it in the comments below!

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ChatGPT, Chatbots and Artificial Intelligence in Education

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AI just stormed into the classroom with the emergence of ChatGPT. How do we teach now that it exists? How can we use it? Here are some ideas.FEATURED

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A Teacher's Prompt Guide to ChatGPT aligned with 'What Works Best'.pdf

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ChatGPT-3 is a state-of-the-art language model developed by OpenAI. It is based on the GPT-3 (Generative Pre-trained Transformer 3) architecture and has been trained on a massive amount of text data. It has the ability to generate human-like text, answer questions, and complete various language-based tasks. It can also perform well on a wide range of natural language processing (NLP) tasks, such as text summarisation, translation, and text-to-speech. Additionally, it has the ability to generate text based on given prompt, which is unique for its large size and capability. It is considered as one of the most advanced language model available and it continues to be updated and improved.
(Generated by ChatGPT-3)

ChatGPT-3 became freely available on 30 November 2022.

In the short space of time that has passed academia has been 'stunned' by the technology's essay-writing skills and usability (Herne 2022), escalating concerns that students can now easily produce AI-assisted written work with minimal effort, dumbing down the value of their university degree. In the past few weeks alone a plethora of articles and guides have emerged to advise how we can approach this new challenge to academic integrity and quality, some of them written by ChatGPT-3 itself, just to prove the point.

But let's not forget that we have a history here, machines have traditionally been troublesome for Universities. In the early 1930s student unions were debating that the l ecturer was at risk of being replaced by the gramophone (Lindsay 2017); in the 1990s the growth of 'distance' learning was poised to cause the eventual dissolution of the university and the profession of the university lecturer (Eamon 1999), which was somewhat mirrored 30 years later during the online pivot of Covid19. Let's not forget that lecture capture has been deemed a technology that would drive students out of lecture halls and replace faculty with recorded online provision (Fagan 2021).

The difference we have with ChatGPT is that it doesn't so much present a threat to the university experience, but rather directly into the heart of the purpose of a university education - its ability to 'teach you how to think'. There have been shadows of this in the past, for instance the hostility towards Wikipedia (Coomer 2013), the emergence of essay mills, not to mention simple, now common place tools such as spell checkers and calculators. I remember vividly a very angry professor in the early 2000s telling me that reading lists with hyperlinks would make students baby birds, with wide open mouths expecting to be spoon fed. We've pretty much moved through all those advancements in technology and realised their benefits, but this one, I would argue, is different. Not because it does not have its benefits, but because of the sheer volume and scale of what's coming will be meaningfully different and ultimately challenge the foundations upon which we measure that ability to think - university assessment.

So what does ChatGPT mean for University assessment? Let's look at four scenarios.

1. Ban it

Whilst this is a rather a futile exercise, it is an option that we have already seen some schools take (Yang 2023), and it's likely we'll see more go down this path. Blocking a tool from a network or device is something most students can get around by simply logging into other networks, using other devices. Could we develop detection software like Turnitin, that is trained to identify AI language algorithms? GPT-2 Output Detector Demo has made a start here, identifying patterns of irregularities in written work that might indicate chat bot assistance. Turnitin have announced that they will build AI detection into their products. But GPT is only going to advance, every time we prompt the free ChatGPT-3 we train it and hurtle towards ChatGPT-4 which according to OpenAPI will be 100x more powerful. At this rate we may well become human-batteries fuelling the machines through constantly feeding them information and data, becoming trapped within an AI generated writing matrix! This detection race is one we will not win. Hard exiting out of this cycle requires a different approach.

Seriously though, plagiarism and cheating is not new, and is already a significant activity across Universities. The QAA recently estimated that one in seven (14%) graduates may have paid someone to undertake their assignment (QAA 2020). A recent bit of polling also indicated that 16% of students had cheated in their online exams in 2022, and 52% surveyed knew someone who had cheated in their academic assessment that year. A very small percentage, only 5%, had been caught. AI technology has the ability to make this practice easier and more accessible, but banning it is simply trying to implement an analogue solution to digital problem. And it's questionable whether it is the technology or our approach to assessment that is problematic.

2. Return to exams

This is an extreme scenario, but again one I am expecting to see, especially where there may be less appetite or resource to advance pedagogically and approach assessment in different ways. Of course exams still exist in many institutions, but increasingly it is recognised that requiring students to be placed in highly pressurised inflexible environments lacks a degree of inclusivity and manifests all kinds of attainment gaps. A return to pen and paper exams feels like a real step back but it is one some universities are willing to take to thwart the machine (Cassidy 2023). Sitting online exams under controlled conditions, with lock-down browser technology and the ability to detect whether students are pasting large chunks of text into their authoring interface is another option. But online proctoring software comes with financial and operational challenges, not to mention ethical considerations and known opportunities for academic dishonesty.

There may be something said though for encouraging more synchronous writing exercises. Johann N. Neem, talking to Inside Higher Ed, says that faculty could find 'new ways to help students learn to read and write well and to help them make the connection between doing so and their own growth' (D'Agostino 2023). An example would be offering opportunities for students to write in class and learn to approach writing as a practice of learning as well as a demonstration of it.

3. Develop AI Literacies as part of Student Assessment

This is undoubtably a good step. Over the past few weeks a range of ideas for engaging, authentic and creative assignments have been shared by the higher education community on how ChatGPT can be incorporated into student assessment and develop critical AI literacies. These range from essay reflection and improvement exercises, to prompt competitions and fact checking. A growing body of guides are emerging - I particularly like ' Update Your Course Syllabus for chatGPT ' from Ryan Watkins, which includes 10 AI-ready assignment ideas.

AI is not going away, it is technology that we are all going to be (and already are) engaging with. Developing AI literacies to enable students to use the technology responsibly and critically, is part of preparing them for the world of work. I'm not on board with a recent statement by JISC that 'We should really regard them as simply the next step up from spelling or grammar checkers: technology that can make everyone's life easier' (Weale 2023). We have to help students to understand where AI writing tools can support them, where it can enable a better outcome, and what its limitations are. Unlike a spell-checker, there is a lot more room for error - after all ChatGPT-3 does not provide you with an answer to your prompt, it provides you with an output. That is a different thing altogether.

It's also worth noting that AI literacy is a space where we should be mindful of looming social inequalities and environmental challenges. Improved future releases of GPT are not planned to be free to access, whilst the carbon footprint of training just a single AI model is significant. As institutions usually committed at some level to social justice, Universities need to look at where they stand on these matters and support students in navigating them.

4. Assess 'Humanness'

Like we can not ban AI tools, we can not use them for all assignments. Currently tools such as ChatGPT-3 can not do a number of things that are generally expected from a university student - it can not consult, critique and cite third party sources, it can not refer to recent real world events or published material, it can't demonstrate higher-level thinking, argue or have original ideas. The more detail and facts you ask for, the more it falters. Today, one of the best ways for students to prove that they are not a predictive language model is to demonstrate sophisticated thinking, which after all is the purpose of a university education. And we have to ask, if a machine can tell us what we need to know, what is the point in learning it? We need to shift contexts of what students need to know and how they need to learn.

Approaching assessment with the question 'what are the cognitive tasks students need to perform without AI assistance?' is a good start. It is possible that the rapid evolution of ChatGPT can positively increase adoption of assessment techniques that measure learners on critical thinking, problem-solving and reasoning skills rather than essay-writing abilities. Increased use of oral and video assessment, reflective assignments that ask students to explain their thinking process, developing concept diagrams, mind maps, engaging in ideation and group projects are other examples of assessment techniques. This is something many Higher Education learning professionals have been promoting for some time in a bid to better connect University education with workplace skills, offering more authentic experiences. Professional bodies would do well to look at what value their End Point Assessments hold in an AI landscape and work with Universities to explore alternative methods.

5. Using ChatGPT to support assessment processes

Much that has come out of the sector on ChatGPT and assessment has very much focused on student learning and risks of plagiarism or cheating. However, on the faculty side there are opportunities to review how this technology can support the assessment burden that many institutions face. The more sophisticated we make assessment in response to AI, the more difficult it will be for AI technology to support tasks such as marking. However, whilst assessment rubric contains generic criteria around structure, referencing and content topics then there is scope to train AI to support the grading of these elements. Multiple formative opportunities could be put in place to raise the bar on these elements, and ultimately reduce the load of markers who can then focus on feeding back on students' demonstration of cognitive skills.

Another possible time saver would be Multiple-Choice Question production. Back in 2018 Donald Clark wrote on the potential for AI to reduce the burden of MCQs which are time consuming and difficult to author and quite often lack the quality and the quantity needed to make them as robust as they could be. Not only can AI help to generate question banks, but it can enable more forms of open input questions as the technology makes possible the interpretation of answers such as typed words, numbers of short answers. Moving forwards the possibilities for ChatGPT to generate customised questions for individual students based on their prior knowledge and proficiency, or to support students in designing their own assignments, could lead to attainable personalisation of curriculum (Barber et al 2021).

In just a few months ChatGPT-3 has laser-focused Higher Education on reviewing the essay as a form of assessment, on the practice of writing, how that will change and why. But we are already moving on. AI is also in the space of media production, not only can it produce art, videos and audio it can adopt voices and faces - our chat bot is evolving beyond written words. It would be naive to think we can stand still. This is a technology that is already two steps ahead of our attempts to contain it in some form of meaningful, solid assessment strategy. In writing this piece I have avoided the possible option that we 'do nothing' in response to ChatGPT-3. Considering how slow Universities can be to implement change this is a possibility, but it is not a viable or sustainable choice. Unless we confront the implications of AI for teaching and learning, and embrace it as a part of our policies and pedagogies to develop critical thinking in an AI world, then we really will start to the lose the value of a University education.
References
Barber, M., Bird, L., Fleming, J., Titterington-Giles, E., Edwards, E., and Leyland, C. (2021). "Gravity assist: Propelling higher education towards a brighter future"Office for students. Available online at: https://www.officeforstudents.org.uk/publications/gravity-assist-propelling-higher-education-towards-a-brighter-future/

Cassidy, C (2023) 'Australian universities to return to 'pen and paper' exams after students caught using AI to write essays' The Guardian, 10 Jan 2023. Available online: https://www.theguardian.com/australia-news/2023/jan/10/universities-to-return-to-pen-and-paper-exams-after-students-caught-using-ai-to-write-essays

Clark, D (2018) Learning Designers will have to adapt or die. Here's 10 ways they need to adapt to AI.... [Blog] Donald Clark Plan B. Available online http://donaldclarkplanb.blogspot.com/2018/09/learning-designers-will-have-to-adapt.html

Coomer, A (2013) Should university students use Wikipedia? The Guardian, 13 May 2013. Available online: https://www.theguardian.com/education/2013/may/13/should-university-students-use-wikipedia

D'Agostino, S (2023) ChatGPT Advice Academics Can Use Now. Inside HigherEd, 13 Jan 2023. Available online: https://www.insidehighered.com/news/2023/01/12/academic-experts-offer-advice-chatgpt

Eamon, D.B. (1999) Distance education: Has technology become a threat to the academy?. Behavior Research Methods, Instruments, & Computers 31, 197-207. Available online: https://doi.org/10.3758/BF032077114

Fagan, J (2021) University of Exeter Lecturers Threaten Industrial Action over Lecture Recordings. Available online: https://www.tptranscription.co.uk/university-of-exeter-lecturers-threatening-industrial-action-over-lecture-recordings/

Heikkilä, M (2022) 'We're getting a better idea of AI's true carbon footprint. MIT Technology Review', 14 Nov 2022. Available online: https://www.technologyreview.com/2022/11/14/1063192/were-getting-a-better-idea-of-ais-true-carbon-footprint/

Hern, A. (2022) 'AI bot ChatGPT stuns academics with essay-writing skills and usability' The Guardian, 4 Dec 2022. https://www.theguardian.com/technology/2022/dec/04/ai-bot-chatgpt-stuns-academics-with-essay-writing-skills-and-usability

QAA.(2020). "Contracting to Cheat in Higher Education -How to Address Contract Cheating, the Use of Third-Party Services and Essay Mills." UK:Quality Assurance Agency (QAA)

Watkins, R (2023) Update Your Course Syllabus for chatGPT [Blog] Ryan Watkins. Available online: https://medium.com/@rwatkins_7167

Weale, S (2023) 'Lecturers urged to review assessments in UK amid concerns over new AI tool' The Guardian, 13 Jan 2023. https://www.theguardian.com/technology/2023/jan/13/end-of-the-essay-uk-lecturers-assessments-chatgpt-concerns-ai?

Yang, M (2023) 'New York City schools ban AI chatbot that writes essays and answers prompts' The Guardian, 6 Jan 2023. Available online: https://www.theguardian.com/us-news/2023/jan/06/new-york-city-schools-ban-ai-chatbot-chatgpt

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ChatGPT and the Future of University Assessment

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Image generated by DALL-E 2 ChatGPT-3 is a state-of-the-art language model developed by OpenAI. It is based on the GPT-3 (Generative Pre-trained Transformer 3) architecture and has been trained on a massive amount of text data. It has the ability to generate human-like text, answer questions, and complete various language-based tasks.

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7 missteps university leaders must avoid in their AI approach | EAB

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In recent conversations with presidents, provosts, CBOs and CIOs, we've identified seven missteps university leaders are making in their AI approach.

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Classroom Policies for AI Generative Tools

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The following syllabus statements were developed by the Senate Committee on Educational Policy as a resource for faculty and instructors, with options ranging from "no restrictions" to "ChatGPT and other AI tools may not be used under any circumstances." These statements may be adopted or adapted to reflect a given instructor's course learning objectives and instructional / assessment style.

For instructors who wish to embrace ChatGPT

Artificial intelligence (AI) language models, such as ChatGPT, may be used for any assignment with appropriate citation. Examples of citing AI language models are available at: l ibguides.umn.edu/chatgpt [or provide an alternative reference appropriate for your class]. You are responsible for fact checking statements composed by AI language models.

For instructors who wish to allow limited usage of ChatGPT

Artificial intelligence (AI) language models, such as ChatGPT, may be used for [assignment types A, B & C] with appropriate citation, but not for [assignment types D, E & F]. If you are in doubt as to whether you are using AI language models appropriately in this course, I encourage you to discuss your situation with me. Examples of citing AI language models are available at: libguides.umn.edu/chatgpt [or provide an alternative reference appropriate for your class]. You are responsible for fact checking statements composed by AI language models.

For instructors who wish to prohibit the usage of ChatGPT

The Board of Regents Student Conduct Code states the following in Section IV, Subd.1: Scholastic Dishonesty:

"Scholastic dishonesty means plagiarism; cheating on assignments or examinations, including the unauthorized use of online learning support and testing platforms; engaging in unauthorized collaboration on academic work, including the posting of student-generated coursework on online learning support and testing platforms not approved for the specific course in question; taking, acquiring, or using course materials without faculty permission, including the posting of faculty-provided course materials on online learning and testing platforms; ..."

Artificial intelligence (AI) language models, such as ChatGPT, and online assignment help tools, such as Chegg®, are examples of online learning support platforms: they can not be used for course assignments except as explicitly authorized by the instructor. The following actions are prohibited in this course [remove bullets as necessary]:

Submitting all or any part of an assignment statement to an online learning support platform;

Incorporating any part of an AI generated response in an assignment;

Using AI to brainstorm, formulate arguments, or template ideas for assignments;

Using AI to summarize or contextualize source materials;

Submitting your own work for this class to an online learning support platform for iteration or improvement.

If you are in doubt as to whether you are using an online learning support platform appropriately in this course, I encourage you to discuss your situation with me.

Any assignment content composed by any resource other than you, regardless of whether that resource is human or digital, must be attributed to the source through proper citation. (Examples of citing content composed by digital tools are presented in: libguides.umn.edu/chatgpt [or provide an alternative reference appropriate for your class].)

Unattributed use of online learning support platforms and unauthorized sharing of instructional property are forms of scholastic dishonesty and will be treated as such.

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The following syllabus statements were developed by the Senate Committee on Educational Policy as a resource for faculty and instructors, with options ranging from "no restrictions" to "ChatGPT and other AI tools may not be used under any circumstances." These statements may be adopted or adapted to reflect a given instructor's course learning objectives and instructional / assessment style.

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With the emergence of ChatGPT and other AI tools, many members of our community are eager to explore their use in the university context. This advisory provides guidance on how to use these tools safely, without putting institutional, personal, or proprietary information at risk. Additional guidance may be forthcoming as circumstances evolve.

Allowable Use:

Prohibited Use:

At present, any use of ChatGPT should be with the assumption that no personal, confidential, proprietary, or otherwise sensitive information may be used with it. In general, student records subject to FERPA , and any other information classified as Protection Level P2, P3, or P4 should not be used.

Similarly, ChatGPT should not be used to generate output that would be considered non-public. Examples include, but are not limited to, proprietary or unpublished research; legal analysis or advice; recruitment, personnel or disciplinary decision making; completion of academic work in a manner not allowed by the instructor; creation of non-public instructional materials; and grading.

Please also note that OpenAI explicitly forbids the use of ChatGPT and their other products for certain categories of activity, including fraud and illegal activities. This list of items can be found in their usage policy document

Additional Guidance:

For further guidance on the use of ChatGPT for teaching and learning, please see Understanding AI Writing Tools and their Uses for Teaching and Learning at UC Berkeley from Research, Teaching & Learning.

Rationale for the Above Guidance:

UPDATE 7/1/2023: The University of California recently renegotiated the UC systemwide agreement with Microsoft to include Microsoft Azure OpenAI. UC Berkeley is currently working with Microsoft to establish how to use this service under UC's agreement. [Note: For questions regarding the approved use of Microsoft's Azure's Open AI service, please consult with the Privacy Office at privacyoffice@berkeley.edu ]

As of September 2023, the University of California's agreements with the parent companies of ChatGPT and other generative AI services, which include our terms and conditions, Appendix Data Security and other privacy protections, do not cover the use of ChatGPT or other similar generative AI services. The UC Office of the President is working on this issue. We hope to see this addressed in the near future and will update this guidance when additional information is available.

Personal Liability: ChatGPT uses a click-through agreement. Click-through agreements, including OpenAI and ChatGPT terms of use, are contracts. Individuals who accept click-through agreements without delegated signature authority may face personal consequences, including responsibility for compliance with terms and conditions. [1]

Guidance on Appropriate Use

For questions regarding the appropriate use of ChatGPT and other AI tools, please contact privacyoffice@berkeley.edu

References

Additional Readings

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Appropriate Use of ChatGPT and Similar AI Tools

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With the emergence of ChatGPT and other AI tools, many members of our community are eager to explore their use in the university context. This advisory provides guidance on how to use these tools safely, without putting institutional, personal, or proprietary information at risk. Additional guidance may be forthcoming as circumstances evolve.

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Since OpenAI released ChatGPT in November 2022, the availability of generative AI tools that produce text, image, or code has expanded to include Microsoft's BingAI, Google's Bard, and OpenAI's more powerful GPT-4. The power of these tools to answer complex questions and generate coherent text continues to improve, and they've recently been integrated into widely used software like Google Docs and Microsoft Office. This has led to questions about how students are using these tools and how faculty can respond to best support their students' learning.

In consultation with instructors and technology experts at Yale and beyond, the Poorvu Center offers guidance on exploring how Generative AI works and suggestions about how to adapt your current teaching. We also offer advice for teaching fellows and a list of recommended reading. Additional resources include examples for incorporating AI into teaching from Yale instructors and resources from Poorvu Center events on teaching in the age of AI.

Instructors: Share your thoughts and ideas with us! Send questions or examples of how you are integrating these tools in your lessons or adjusting in light of them. Email us at askpoorvucenter@yale.edu.

Understanding Generative AI

Generative AI tools respond to user-submitted text with relevant content expressed in natural language. Many of these tools remember all text that a user has entered in an ongoing conversation, and they are capable of revising their responses when prompted.

Generative AI tools operate on programs called large language models. (The technology that underlies image and coding tools is also referred to by LLM.) LLMs are programmed by being fed large bodies of text (e.g. the entire internet) and trained to predict the most relevant sequence of words in response to a prompt. As a result, they can draw on a vast database of human knowledge, and their responses reflect the biases and limitations of the material they are trained on. Put differently, generative AI produces text by calculating the probability that it will be relevant to the prompt a user has submitted. As a result, the responses produced by generative AI tools tend to reflect consensus understandings, including any biases and inaccuracies that inform those positions.

Because generative AI predicts words based on probabilities, they are not capable of original thought. They are best at responding to prompts that require less creativity, like summarizing information, solving problems whose answers are already known, or supporting one position among alternative theories or approaches. But AI tools can generate new ideas by combining existing knowledge in new ways, and users can submit follow-ups that prompt the bot to incorporate additional ideas into an existing response or to revise it for greater complexity.

The best way to learn about AI tools is to try them yourself. Signing up for an account at ChatGPT, Google Bard, or BingAI (requires Microsoft Edge browser) will allow you to explore how these programs work and help you better understand how your students might be using them. You can often learn the most about these programs by simply letting curiosity be your guide. But here are a few prompts you might use to get started:

Ask the program to write a response to one of the assignments from your class.

Prompt the tool for help with a task you're working on like writing an email or choosing the next step toward completing a project.

Choose an assignment one of your students has submitted to your class and prompt the AI tool to produce a response that is as close as possible to the student's, entering follow-up prompts as necessary to bring the text closer to the student's.

Ask the tool to teach you about a subject and then quiz you at the end.

A few words of caution
While it can be valuable to try out these tools so that you understand how they work, they do raise issues of privacy and intellectual property.

Material that you submit may then become part of the program's database-using the software also contributes to its development.

The systems have different policies and methods to let you remove your material, so be sure to look for those instructions and to review the Terms of Service.

If you ask students to use these tools-and over time, many of us may encourage some of this collaboration-the risks become even more complicated.

Even software platforms that don't use your content to train the product DO collect your information and often install cookies to track your other activity. While you may choose to make this bargain to try out AI tools yourself, it can be more problematic to require students to sign up for tools that will track and use their private data.

This article from the New York Times offers guidance on how to phrase prompts submitted to AI tools, and this Beebom article lists dozens of sample prompts that show the range of generative AI capabilities.

Guidance for Instructors

(1) Instructors should be direct and transparent about what tools students are permitted to use, and about the reasons for any restrictions. Yale College already requires that instructors publish policies about academic integrity, and this practice is common in many graduate and professional school courses. To ensure that your students' use of AI tools aligns with your learning goals, consider updating your academic integrity policy to clarify how students are permitted to engage with AI tools and how they should signal that it has been used. Find example statements in the next section.

As for explaining why, understanding the learning goals behind assignments helps students commit to them. The only reason to assign written work is to help students learn-either to deepen their understanding of the material or to develop the skill of writing in itself. From our long experience in reviewing the portfolios of Yale College students, we see clear evidence that over the course of four years, they progress significantly as writers.

Research shows that people learn more and retain the information longer when they write about it in their own words. If instead, students task an AI to generate texts, they won't learn as much. This is why we ask them to write their own papers, homework assignments, problem sets, and coding assignments. This impact on learning applies across all disciplines-STEM problem sets that require explanations also depend on students' generating language to learn more deeply. AI tools can also generate coding solutions, not just natural language.

(2) Controlling the use of AI writing through surveillance or detection technology is probably not feasible. Turnitin has acknowledged a reliability problem with its detection tool software and Yale has not enabled this feature in Canvas. We believe there are more fruitful ways to engage writing processes and expectations than to rely on predictions that will probably be outpaced by further AI development.

Research by the Poorvu Center shows that a minuscule number of Yale College students plagiarize in their course papers. While acknowledging that new technologies can change the landscape, we know that most students want to do their own work because they care about learning.

Tools like ChatGPT raise broader questions. We agree with this approach from Inside Higher Ed: "Go big. How do these tools allow us to achieve our intended outcomes differently and better? How can they promote equity and access? Better thinking and argumentation? ... In the past, near-term prohibitions on ... calculators, ... spellcheck, [and] search engines ... have fared poorly. They focus on in-course tactics rather than on the shifting contexts of what students need to know and how they need to learn it." While the Poorvu Center doesn't have all the answers, we can offer some general guidance and work with you to put this advice into practice.

(3) Changes in assignment design and structure can substantially reduce students' likelihood of cheating-and can also enhance their learning. Based on research about when students plagiarize (whether from published sources, commercial services, or each other), we know that students are less likely to cheat when they:

Are pursuing questions they feel connected to

Understand how the assignment will support their longer-term learning goals

Have produced preliminary work before the deadline

Have discussed their preliminary work with others

Make their writing process visible in the completed assignment

Many of the above characteristics can be integrated into authentic assessments, which are assignments that 1. have a sense of realism to them, 2. are cognitively challenging, and 3. require authentic evaluation (see this handout for more). Examples can be found at the bottom of this website. Authentic assessments also align with practices that prioritize student learning, and make it harder to collaborate with AI tools, including:

Asking students to engage primary and secondary sources, which can include:

Assignments where students place their ideas in conversation with the ideas of other scholars-either readings you give them, or sources they find themselves

Asking students to use resources that are not accessible to ChatGPT, including any resources behind a paywall or many of the amazing resources in Yale's collections.

Incorporating the most up-to-date resources and information of your field so that students are answering questions that have not yet been answered or have only begun to be answered.

Engaging with ChatGPT as a tool that exists in the world and having students critically engage with what it can produce as in these examplesfrom Yale instructors.

Using alternative ways for students to represent their knowledge beyond text (e.g., draw images, make slides, facilitate a discussion). Consider adopting collaboration tools like VoiceThread.

Addressing Generative AI on your Syllabus

The Poorvu Center recommends including on your syllabus an academic integrity statement that clarifies your course policies on academic honesty. The simplest way to state a policy on the use of ChatGPT and other AI composition software is to address it in your academic integrity statement.

A policy that encourages transparency in how students use AI might read: Before collaborating with an AI chatbot on your work for this course, please request permission by sending me a note that describes (a) how you intend to use the tool and (b) how using it will enhance your learning. Any use of AI to complete an assignment must be acknowledged in a citation that includes the prompt you submitted to the bot, the date of access, and the URL of the program.

If you think students' learning is best supported by avoiding AI altogether, your course policy might read: Collaboration with ChatGPT or other AI composition software is not permitted in this course.

Guidance for Teaching Fellows

As a teaching fellow, raising the issue of ChatGPT with your lead instructor can open a broader conversation about the goals of your course and how ChatGPT might impact those goals. For example, it is helpful to understand the intended purpose of both low-stakes and high-stakes assessments, in addition to possible redesigns to work students are doing outside of class.

Regardless of whether you make changes to assessments, you play an important part in making the goals clear to your students. Whether you hope that their work will help them explore new ideas, familiarize themselves with important concepts, or make progress toward a bigger project, articulating those learning outcomes and the purpose of the activities that support them will help students understand why using AI would be counterproductive to their own development and progress.

These conversations with students can happen in conventional sections, but they are also worthwhile to have in office hours and review sessions. Additionally, as you give feedback to students, think about ways that you can point them back to the larger goals of the course: by showing them how they can grow through the assessment process, you indicate its value.

Poorvu Center Sessions

Teaching with AI Writers: Conversation and Workshop on May 25, 2023 provided a space for faculty to hear the various changes colleagues have made to their teaching in response to new artificial intelligence writers, as well as a hands-on opportunity to consider their own assignment design approach.

Spring Teaching Forum: Teaching in the Age of ChatGPT on May 1, 2023 hosted Derek Bruff-an educator, author, higher ed consultant, and former director of the Vanderbilt University Center for Teaching-to briefly survey the landscape of AI text generation tools, then dive into the teaching choices they present.

Artificial Intelligence and Teaching: A Community Conversation on February 14, 2023 featured a panel of Yale faculty and students discussing the implications of AI-writing software for teaching and learning.

Incorporating AI in Teaching: Examples from Yale Instructors

Yale instructors are considering how to redesign elements of their courses to address ChatGPT and other AI platforms. Examples across the disciplines demonstrate some of the novel ways instructors are engaging their students as this technology evolves.

Recommended Reading

New articles on this fast-developing topic are appearing every day. Below is a selection of thoughtful pieces that address various elements of this tool.

The Department of Education released insights and recommendations on AI and the Future of Teaching and Learning (May 2023). Brief summary of the report is available on EdSurge.

OpenAI, the creator of ChatGPT, shares about safety and how they train their tool as well as their guidelines for educators.

Mollick and Mollick at UPenn published seven approaches to using AI in the classroom that aim to help instructors navigate the integration of AI-assisted learning in classrooms (June 21, 2023).

The Chronicle of Higher Education outlines professors' plans to be ready in the fall for ChatGPT (June 13, 2023), provides these highlights from their virtual forum on AI and academic integrity (June 12, 2023), suggests how ChatGPT could help or hurt students with disabilities, and offers some of the ways AI may change how professors assess learning (April 5, 2023).

The Intentional Teaching podcast featured an episode, Rethinking Teaching in an Age of AI, which raises some important questions for educators to consider as they retool courses and assignments to account for AI technology.

The team at NPR's Planet Money creates an episode using Artificial Intelligence and learns ChatGPT's limitations and advantages.

The Center for Teaching at Vanderbilt University and the University of South Carolina's Center for Teaching Excellence offer comprehensive AI guidance to instructors from revised learning goals and assessment to teaching strategies.

Jenny Frederick, Poorvu Center Executive Director, discusses the center's AI guidance with NBC Connecticut (February 14, 2023).

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Since OpenAI released ChatGPT in November 2022, the availability of generative AI tools that produce text, image, or code has expanded to include Microsoft's BingAI, Google's Bard, and OpenAI's more powerful GPT-4. The power of these tools to answer complex questions and generate coherent text continues to improve, and they've recently been integrated into widely used software like Google Docs and Microsoft Office.

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Since OpenAI first rolled out its ChatGPT to the public late in 2022, the generative AI market has grown and diversified. In addition to OpenAI's releasing another large language model, new tools appear in the field constantly. At the same time, concerns are multiplying about the risks generative AI may pose to education, industries, and internet user safety.

In education, a number of quick solutions has been developed, such as AI-detecting functionalities and GPT teach-outs. But as we learn to work around the increasing threat of hard-to-detect plagiarism, we also face new questions: how can we incorporate generative AI into the classroom? Can it be a teaching and learning tool? how can we teach students to interact with AI safely and usefully? how will the advance of generative AI shape our students' professional futures, and how should teachers respond to that?

ChatGPT "is a variant of the GPT (Generative Pre-training Transformer) language model, which was developed by OpenAI. GPT models are trained to generate human-like text by predicting the next word in a sequence based on the words that come before it. CHATGPT is specifically designed to be used in chatbots and conversational systems, and it is trained on a large dataset of human conversations to learn how to generate appropriate responses in a variety of contexts. (response from ChatGPT on 1/3/2023). This model is also known as GPT-3.5. Learn more:

GPT-4: the newest version of OpenAI's language model systems, officially launched in March 2023. It is a multimodal model, in that it accepts text and images as input. It can only generate text. It has demonstrated much stronger academic performance compared to the GPT-3.5 model. Learn more: OpenAI's launch announcement on GPT-4.
The ChatGPT-4 tool based on this model is only available through paid ChatGPT+ subscription at this point ($20/month.)

Bing: Microsoft's AI chatbot. After the release of GPT-4, Microsoft officially confirmed that Bing runs on OpenAI's GPT-4 model.

As of March 2023, OpenAI introduced support for plugins, including a Bing-based browsing plugin, which helps keep the outputs up-to-date and compensates for the training data behind the models only going up to 2021.

Dall-E 2: ChatGPT's visual creation sister, also run by OpenAI. Learn more

Bard: Google's AI chatbot. It is available through waitlist, although the wait is usually only a few days. It is still in beta-testing stage and performs with obvious lapses, but appears to evolve constantly.

Teaching and learning in the era of generative AI does not need to be all about damage control. Plagiarism and ethics concerns are real, but on the other hand, the advance of generative AI gives us a special opportunity to focus on the challenges of teaching and work out strong solutions.

Generative AI itself can be a learning tool- as anyone who gets into the tool and starts inputting queries and studying the output knows. Your synapses are firing as you write and read the rapidly generated text. It's fun, and you're likely wide awake, judging, speculating, disagreeing, agreeing, and doing all those things that happen when an engaged reader encounters text. These potentials can be used in the classroom.
Some specific suggestions:

Assignment Strategies: Authentic assessment, formative assessment, assessment add-ons like problem-solving logs, exam wrappers, minute papers, "muddiest point" questions.

Ask students to use diverse media. Replace an essay or short-answer writing assignment with one that requires students to submit an audio file, podcast, video, speech, drawing, diagram, or multimedia project.

Create connections to real-world experience that AI will not have. Connect assignments to very recent events or new conversations in the field; to issues specific to the local community, or to discussions that took place in your own classroom. Alternatively, ask your students to find a connection between course concepts/topics and their personal experience or knowledge.

Ask your students to reflect and plan as part of learning. Reflecting and envisioning a future are two areas where generative AI's performance remains quite weak. Create space for reflection and sharing after each learning unit. Make reflection and planning a routine part of written assignments that is gradable. Students will not be able to create strong submissions for such tasks using generative AI (also, feel free to tell them just that!)
For example: instead of the traditional essay, which is now easy to cheat through, assign a multimedia project accompanied by a brief self-reflective essay.

Incorporate ChatGPT in your assignments. The more familiar your students become with it, including both its strengths and weaknesses, the less likely they will be to use it blindly for generating submissions.

For example: to develop your students' critical thinking skills, ask them to generate a ChatGPT response to a question of their own choosing, and then write an analysis of the strengths and weaknesses of the ChatGPT response.

Teach your students to cite generative AI correctly.

Teach your students to use generative AI safely. ChatGPT acknowledges that they may share account holders' personal information with third parties, including vendors and service providers. See Privacy Policy. Teach your students to never share personal and sensitive information with generative AI chatbots.

Use social annotation. For short reading responses, instead of using open-ended questions in Canvas, try social annotation tools that require students to engage with a text along with their classmates. Try Hypothes.is or Perusall, both of which are supported by the University.

Extend Flipped Learning: Ask students to read, view, and digest material at home, and then apply, demonstrate, and perform in class, individually or in small groups.

For the full list of tips and ideas, go to this page.

Using generative AI to create or enhance the content of submissions when an assignment does not explicitly call or allow for it is academically dishonest, akin to paying a person to write your paper, take your test, or complete your assignment. Here are some tips on preventing and addressing academic dishonesty in the era of generative AI.

Talk to your students. The first step to addressing the projected or actual academic integrity issues in the classroom is to talk to your students about your expectations for academic honesty.

Remind your students of the University's policies.

Since the University's policies on academic integrity currently do not include a separate clause on generative AI, add a clarifying statement to your syllabus (sample wording can be found here.)

Give examples. Be specific and frank about your concerns.

Raise questions to stimulate reflection: why is academic integrity valuable and important to uphold? What's the point of pursuing a degree, of taking a class, if you don't learn?

See Academic Dishonesty and Student Cheating for additional guidance.

Make plagiarizing difficult. Use some of the assignment design strategies suggested above and/or here to create assignments that encourage honest work.

Run your assignment through ChatGPT. If you assign a task that can be solved by ChatGPT/ other generative AI, run it through ChatGPT first. Review the answer you receive, and tell your students about your experience (and that you've saved the output). ChatGPT does not produce the same answer each time the same question is posed, but the outputs may still be fairly similar.

Be on the lookout for AI-produced texts.

Play around with the tool and get an idea of what kind of prose is produced to the questions you typically ask. Not only will you gain insights on how to better write your assignments, but you may get a sense of the "voice" - or lack of voice - of the tools.

Make use of AI-detecting tools.

Watch out for these red flags.

Always consider students' writing history and the broader context of the assignment before making a decision. When plagiarism is suspected, talking to the student individually is the easiest first step to addressing the problem.

Alby, C. (2022, December 17). ChatGPT: Understanding the new landscape and short-term solutions. Google Docs. Retrieved January 4, 2023, from https://docs.google.com/document/d/1ERCgdylG2LyOeL93aWrK6Jf97N_m1qaueN9W4kzO0Rk/edit#.

Barbaro, M. (Host). (2022, December 16). Did artificial intelligence just get too smart? [Audio podcast episode]. In The Daily. The New York Times Company. Guest: Kevin Roose.

Marchese, D. (2022, December 26). An A.I. pioneer on what we should really fear. The New York Times. Retrieved January 4, 2023, from https://www.nytimes.com/interactive/2022/12/26/magazine/yejin-choi-interview.html?smid=url-share. Interview with computer scientist Yejin Choi.

Rudolph, J. et al (2023). ChatGPT: Bullshit spewer or the end of traditional assessments in higher education? Journal of Applied Learning and Teaching. Vol. 6, No. 1.

Pavlik, J. V. (2023). Collaborating With ChatGPT: Considering the Implications of Generative Artificial Intelligence for Journalism and Media Education. Journalism & Mass Communication Educator, 0(0). https://doi.org/10.1177/10776958221149577

Susnjak, T. (2022). ChatGPT: The End of Online Exam Integrity? Working Paper. http://arxiv.org/abs/2212.09292

Schmitz, R. (Host). (2022, December 16). Has AI reached the point where a software program can do better work than you? [Audio podcast episode]. In: Morning Edition. National Public Radio. Guest: Ethan Mollick of the University of Pennsylvania. Mollick gives an overview and specific examples of how ChatGPT can be used. For example, he tried it out by asking the program to write a syllabus for him, along with a lecture and a final assignment with a grading rubric.

For additional resources, see AI Writing and Creating Bots (Montclair netID required).

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You may need to discuss using AI tools in a variety of contexts, including learning materials and campus, collegiate, and course policies related to academic integrity. Consult with your collegiate leadership about specific policies. In any case, providing transparent information about expectations for student use of AI tools and how these expectations align with course goals and scholarly values is crucial.

Remember that with any policy in your syllabus, it's important to have ongoing conversations throughout the semester.

Some example language:

When AI is prohibited. [This course] assumes that work submitted by students-all process work, drafts, low-stakes writing, final versions, and all other submissions-will be generated by the students themselves, working individually or in groups. This means that the following would be considered violations of academic integrity: a student has another person/entity do the writing of any substantive portion of an assignment for them, which includes hiring a person or a company to write essays and drafts and/or other assignments, research-based or otherwise, and using artificial intelligence affordances like ChatGPT. (Excerpted from ChatGPT by University of California: Irvine Division of Teaching Excellence and Innovation)

When AI is prohibited. Since writing, analytical, and critical thinking skills are part of the learning outcomes of this course, all writing assignments should be prepared by the student. Developing strong competencies in this area will prepare you for a competitive workplace. Therefore, AI-generated submissions are not permitted and will be treated as plagiarism. (Sample statement shared by Chrissann Sparks Ruehle, with permission for others to use, on Higher Ed Discussions of AI Writing Facebook Group on 1/6/2023, cited in ChatGPT Resources by Texas Tech University Teaching, Learning & Professional Development Center)

When AI is allowed with attribution. In all academic work, the ideas and contributions of others must be appropriately acknowledged and work that is presented as original must be, in fact, original. Using an AI-content generator (such as ChatGPT) to complete coursework without proper attribution or authorization is a form of academic dishonesty. If you are unsure about whether something may be plagiarism or academic dishonesty, please contact your instructor to discuss the issue. Faculty, students, and administrative staff all share the responsibility of ensuring the honesty and fairness of the intellectual environment. (Excerpted from Constructing a Syllabus: A Checklist by Washington University in St. Louis Center for Teaching and Learning)

When AI is allowed with attribution. Use of AI tools, including ChatGPT, is permitted in this course for students who wish to use them. To be consistent with our scholarly values, students must cite any AI-generated material that informed their work and use quotation marks or other appropriate indicators of quoted material when appropriate. Students should indicate how AI tools informed their process and the final product, including how you validated any AI-generated citations, which may be invented by the AI. Assignment guidelines will provide additional guidance as to how these tools might be part of your process for each assessment this semester and how to provide transparency about their use in your work.

When AI use is encouraged with certain tasks. Students are invited to use AI platforms to help prepare for assignments and projects (e.g., to help with brainstorming or to see what a completed essay might look like). I also welcome you to use AI tools to help revise and edit your work (e.g., to help identify flaws in reasoning, spot confusing or underdeveloped paragraphs, or to simply fix citations). When submitting work, students must clearly identify any writing, text, or media generated by AI. This can be done in a variety of ways. In this course, parts of essays generated by AI should appear in a different colored font, and the relationship between those sections and student contributions should be discussed in cover letters that accompany the essay submission. (Based on Course Policies related to ChatGPT and other AI Tools by Joel Gladd)

For more, Ryan Watkins, professor of Educational Technology Leadership, and Human-Technology Collaboration at George Washington University, offers suggestions to update your course syllabus and assignments.

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Artificial Intelligence Tools and Teaching

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Co-sponsored by the Center for Teaching and the Office of Teaching, Learning, and Technology, the AI in Teaching Community of Practice will meet monthly to explore the implications of generative AI, such as ChatGPT, in higher education.

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Artificial Intelligence in Teaching & Learning

Syllabi Policy Statements

The AI FLC participants find that there is likely no "one size fits all policy" for AI uses in higher education. Much like attendance/participation policies, AI policy statements will be determined by individual instructors, departments, and programs.

Example policy Statements from the Faculty Learning Community Participants

Claire Hughes-Lynch

AI (artificial intelligence) resources such as ChatGPT can be useful in a number of ways. Because it can also be abused, however, you are required to acknowledge use of AI in any work you submit for class. Text directly copied from AI sites must be treated as any other direct quote and properly cited. Other uses of AI must be clearly described at the end of your assignment.

Selma Koc

Xiongyi Liu

Intellectual honesty is vital to an academic community and for my fair evaluation of your work. All work submitted in this course must be your own, completed in accordance with the University's academic regulations. Use of AI tools, including ChatGPT, is permitted in this course. Nevertheless, you are only encouraged to use AI tools to help brainstorm assignments or projects or to revise existing work you have written. It is sorely your responsibility to make all submitted work your own, maintain academic integrity, and avoid any type of plagiarism. Be aware that the accuracy or quality of AI generated content may not meet the standards of this course, even if you only incorporate such content partially and after substantial paraphrasing, modification and/or editing. Also keep in mind that AI generated content may not provide appropriate or clear attribution to the author(s) of the original sources, while most written assignments in this course require you to find and incorporate highly relevant peer-reviewed scholarly publications following guidelines in the latest publication manual of the APA. Lastly, as your instructor, I reserve the right to use various plagiarism checking tools in evaluating your work, including those screening for AI-generated content, and impose consequences accordingly.

Emily Rauschert on AI as collaboration partner

If you are ever unsure about whether collaboration with others, including using artificial intelligence, is allowed or not, please ask me right away. For the labs, although you may discuss them in groups (and try using AI), you must all create your own code, output and answers. Quizzes will be done in class and must be solely your own work. You alone are always responsible for the correctness of the final answers and assignments you submit.

Leah Schell-Barber for a Business Communications Course

Chat GPT: The use of Chat GTP is neither encouraged nor prohibited from use on assignments for GAD 250. Chat GPT is quickly becoming a communication tool in most business settings. Therefore, if you choose to use Chat GPT for assignments, please be sure to revise the content for clarity, conciseness, and audience awareness. Chat GPT is simply a tool and should not be used as a way to produce first and only drafts. Every assignment submission will be graded using the rubric provided in the syllabus. Be aware that Chat GPT may not develop high-quality work that earns a passing grade. It is your responsibility to review and revise all work before submitting to the instructor.

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Example Policy Statements for AI in Higher Education

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Artificial Intelligence in Teaching & Learning The AI FLC participants find that there is likely no "one size fits all policy" for AI uses in higher education. Much like attendance/participation policies, AI policy statements will be determined by individual instructors, departments, and programs. Claire Hughes-Lynch AI (artificial intelligence) resources such as ChatGPT can be useful in a number of ways.

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THE OFFICE OF THE DEAN OF THE GRADUATE SCHOOL
TO: All Teaching Faculty

FROM: Jill Dolan, Dean of the College; Rod Priestley, Dean of the Graduate School

RE: AI & ChatGPT Guidance for Teaching

January 25, 2023

Dear Colleagues,

We imagine you've been reading as much about generative Artificial Intelligence (AI) lately as we have, especially the new program, ChatGPT, which some observers suggest might have radical consequences for teaching and learning, especially at colleges and universities.

Despite the copious handwringing in the media and elsewhere about this chat bot and its implications for higher education, we and our colleagues in the College and the Graduate School remain confident that our undergraduate liberal arts and graduate education programs will remain vital, vibrant, and useful in the years ahead.

If anything, AI will make higher education and the nuanced and sophisticated ways of thinking it teaches even more essential. The ability of AI tools like ChatGPT to generate comprehensible text and code makes close reading and careful discernment even more important for our students and ourselves.

We expect that faculty have questions about ChatGPT, and we write now to provide some guidance. We also want to acknowledge that this field is developing exceptionally quickly. We'll be learning about AI's power to construct essays and assignments now, next semester, and for many years to come.

Princeton University doesn't intend to ban ChatGPT or to levy a top-down edict about how each instructor should address the AI program in your classes. We outline here instead some ways of thinking about this new landscape.

First, do remember that our Academic Regulations clarify that students are expected to properly acknowledge their sources, adhere to course collaboration policies (which set the standard for "permissible" collaboration), and not seek an unfair advantage over other students. The undergraduate Honor Code and all campus academic integrity rules are quite clear that students must produce original work.

With this broader context in mind, do bring to bear some discernment as you contemplate your course needs and your pedagogy. You might, for example, decide that using AI/ChatGPT violates your collaboration policy, or you might decide it's appropriate for students to use in certain cases.

Other suggestions for those of you who intend to address the chat bot with students:
Be Explicit/Avoid Misunderstandings
Be explicit about your AI/ChatGPT policy in your syllabus, on Canvas, and as you introduce assignments during your first (and perhaps subsequent) class meetings. Make your AI/ChatGPT policy as clear as your academic integrity and collaboration policies and put them on your syllabus where students will be sure to see them. Sample statements that might be useful are linked here.
Explain Your Pedagogical Rationale
Explain to students how completing the assignments in your course will help them learn, and let them know why their own, original work on these assignments is important to their education. Develop grading standards based on your pedagogical values or learning goals, and share them with your students. You're welcome to consult with the McGraw Center or the Princeton Writing Program as you think through your standards.
Design Assignments with Care
To minimize the risk of academic dishonesty, design assignments that require critical and creative thinking (rather than simply summarizing information). Ask students to demonstrate their process and reflect on their work. For example, they might annotate their solution to a novel problem or write a cover letter for their essay that introduces their ideas. Scaffold their work with multiple draft and revision deadlines that offer you opportunities to give them feedback. Ask them to present drafts of their work verbally in class or track their citations in early versions of their work.
Teach Your Students What AI Can and Can't Do
ChatGPT generates patterns of text on a probabilistic basis (similar to "autofill" in your email client, though more powerful). For this reason, it should notbe listed as a co-author on scholarly work; we see it as a compiler rather than a writer ( this article from Nature addresses this issue persuasively).

ChatGPT doesn't have access to web material behind paywalls and has little knowledge of events after 2021. The program can't (yet) cite references. Helping your students recognize what ChatGPT does and doesn't do-as well as its potential benefits and risks as students construct their own original work-is valuable.

Among the most promising teaching suggestions we've seen so far:

1. After students have read and discussed assigned texts, invite them to work in small groups to ask ChatGPT questions about the readings and then assess and critique its answers.

2. After students complete their own drafts of an assigned essay, invite them to request a draft of the assignment from ChatGPT. Facilitate a discussion in which students analyze how the drafts compare, for better and for worse. If they want to incorporate any aspect of the ChatGPT draft into their own revision, offer them guidance on appropriate citation and acknowledgement practices that will make their use of the tool transparent for readers. Again, ChatGPT cannot be listed as a co-author of scholarly work.

As we know, ChatGPT won't be the last AI program that challenges authentic teaching and learning. But this challenge is one we think Princeton faculty and instructors can manage with grace and aplomb.

We hope you'll share your teaching suggestions with us as you experiment with this emerging technology, and keep us posted about what you're seeing and hearing in your classrooms. McGraw will facilitate a discussion about ChatGPT on Zoom sometime early this semester.

Warm best to you all,

CC: Liz Colagiuri, Deputy Dean of the College

Lisa Schreyer, Deputy Dean of the Graduate School

Kate Stanton, Associate Dean of the College, Director, McGraw Center

Amanda Irwin Wilkins, Director, Princeton Writing Program

Kathleen Deignan, Dean of Undergraduate Students

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THE OFFICE OF THE DEAN OF THE GRADUATE SCHOOL TO: All Teaching Faculty FROM: Jill Dolan, Dean of the College; Rod Priestley, Dean of the Graduate School RE: AI & ChatGPT Guidance for Teaching January 25, 2023 Dear Colleagues, We imagine you've been reading as much about generative Artificial Intelligence (AI) lately as we have, especially the new program, ChatGPT, which some observers suggest might have radical consequences for teaching and learning, especially at colleges and universities.

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Two prominent research centers at the University of California, Berkeley have joined together to launch the AI Policy Hub, an interdisciplinary initiative training forward-thinking researchers to develop effective governance and policy frameworks to guide AI, today and into the future.

The AI Policy Hub will support cohorts of UC Berkeley graduate students to conduct research and develop science-based policy recommendations for realizing the potential benefits of AI, while managing harms and reducing the risk of devastating outcomes, including accidents, abuses, and systemic threats. The researchers will share findings through symposia, policy briefings, papers, and other resources, to inform policymakers and other AI decision-makers so they can act with foresight.

The AI Policy Hub will be run jointly by two centers of excellence in AI policy research: the AI Security Initiative, part of the Center for Long-Term Cybersecurity at the UC Berkeley School of Information, and the University of California's CITRIS Policy Lab, part of the Center for Information Technology Research in the Interest of Society and the Banatao Institute (CITRIS). The Hub will kick off this spring, and the first cohort of graduate student researchers will begin their work in fall 2022.

"Recommendations resulting from this research will not only provide guidance to policymakers and decision-makers today but will also assess how potential future shifts will test the resiliency of the recommendations."

"AI systems are already causing significant harm, and the risks are multiplying as AI systems increase in complexity and scale. Meanwhile, there are growing power imbalances as the number of organizations and countries that control the majority of AI development remain small," says Jessica Newman, Director of the AI Security Initiative. "Recommendations resulting from this research will not only provide guidance to policymakers and decision-makers today but will also assess how potential future shifts will test the resiliency of the recommendations."

Artificial intelligence poses consequential risks to humanity, including dark patterns and manipulation, weaponization, growing inequities, and abuses of power. The AI Policy Hub will help mitigate these risks by training a new generation of forward-thinking researchers equipped with the skills to develop appropriate governance and policy frameworks for managing AI into the future.

A key goal of the AI Policy Hub is to expand and diversify the pool of researchers and decision-makers with AI policy expertise. "The AI Policy Hub will strengthen interdisciplinary research approaches to AI policy," says Brandie Nonnecke, Director of the CITRIS Policy Lab. "Expanding inclusion of diverse perspectives is necessary to support the global development and implementation of safe and beneficial AI, today and into the future."

"Expanding inclusion of diverse perspectives is necessary to support the global development and implementation of safe and beneficial AI, today and into the future."

The AI Policy Hub is made possible with initial financial support from the Future of Life Institute (FLI), a nonprofit organization that seeks to steer the development and use of transformative technology towards benefitting life and away from large-scale risks. The initiative will also collaborate with numerous UC Berkeley departments and centers that are contributing work on AI governance and policy, including the I School, the Division of Computing, Data Science, and Society (CDSS), the Center for Human-Compatible Artificial Intelligence (CHAI), the Berkeley Center for Law & Technology, Berkeley's College of Engineering, and the Goldman School of Public Policy.

The Hub will harness the collective networks and expertise of CLTC and CITRIS, which have an established record of helping policymakers develop effective guidelines for the responsible use of AI. For example, CITRIS and AISI were directly involved in efforts to promote the responsible implementation of AI at the University of California and in the California state government. The AI Policy Hub aims to inspire a new generation of AI policy professionals and advance necessary interventions to promote safe and beneficial AI at institutional, state, federal, and international levels.

"Addressing the risks posed by increasingly advanced AI could not be more urgent," says Anthony Aguirre, Executive Vice President and Head of Policy and Strategy at the Future of Life Institute. "As a leader in AI safety, security, and ethics, UC Berkeley is the perfect home for the AI Policy Hub, where world-class researchers will translate cutting-edge AI research into actionable policy insights. We look forward to working with the AI Security Initiative and the CITRIS Policy Lab on this essential effort."

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Two prominent research centers at the University of California, Berkeley have joined together to launch the AI Policy Hub, an interdisciplinary initiative training forward-thinking researchers to develop effective governance and policy frameworks to guide AI, today and into the future.

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Post-pandemic higher education just got interesting. Generative artificial intelligence models such as ChatGPT-released publicly in November 2022-have higher education administrators, faculty and students scrambling to respond to this powerful technology. Pundits include those who fear that the college essay is dead as well as those who counter that the college essay is still very much alive, with many other observers landing somewhere in the middle. Peril and promise. Worry and wonder.

Generative AI is not going to go away. Nobody knows today what generative AI's capabilities and applications will look like in the future, but all indications point to generative AI becoming a routinely accepted and widely used technology in all areas of higher education, from essay writing to syllabus creation to course scheduling and advising, by the end of 2023.

We propose that higher education administrators and faculty members respond to generative AI:

Browse all job openings "

1. with speed (now)

2. with strategic purpose

3. with inclusive focus on equitable student value

Need for Speed

A January 2023 survey of nearly 4,500 professionals shows that 27 percent have already used ChatGPT or some other generative AI tool to assist their work. We should assume that college and university students are being even more adventurous. Responding to possible rule or code of conduct violations by student or faculty use of generative AI without clear generative AI-specific policies in place invites unnecessary challenges. Waiting to see what other institutions do or simply avoiding the hard work of engaging all stakeholders in generative AI policy discussions is an understandable but ineffective reflex.

Strategic Purpose

Start your generative AI policy discussion journey by identifying key questions to consider. Here are some possibilities:

What does it mean to learn with generative AI or AI more broadly?

How can AI-assisted learning be measured?

What should count as cheating with generative AI?

Is the concept of cheating even the right one to apply to generative AI learning policy discussions?

Are there cases in which generative AI use should be prohibited?

How might such prohibition be enforced equitably?

How should we think about student success in this new world of AI?

How might generative AI be used to promote student economic success and mobility after graduation through skill acquisition and job training?

Be sure to include all relevant stakeholders as you ask questions. Recruit student leaders and interested faculty members to join discussions. Listen flexibly. The goal should not be to create a comprehensive, static policy but rather policy guidelines that can respond with agility to emerging shifts and advances in generative AI capabilities over time. Here are some possible policy issues to discuss:

Equity in access to generative AI tools, training and potential value created by use of generative AI.

Training of administrators, faculty members and students on how to properly and most effectively use generative AI.

Transparency of all communications about generative AI policies and best practices.

Proper attribution by students regarding any text or images generated by generative AI and submitted for evaluation, including identification of the specific generative AI prompt used.

Privacy of personal information that might be revealed by generative AI without permission.

Security of data and information from hacking or breaches.

Inclusion of all stakeholders who might gain value from access to and use of generative AI.

Accuracy and quality of data and information generated by generative AI.

Crisis response protocols for reacting quickly to negative impacts of generative AI.

Postsecondary value promotion through strategic use of generative AI to eliminate or narrow college completion gaps and to improve postsecondary outcomes including meaningful employment opportunities.

Inclusive Focus on Equitable Student Value

We recognize that specific generative AI policies created by colleges and universities should reflect the unique features of each institution's learning mission, student demographics and curriculum. However, we propose that administrators and faculty members anchor all generative AI policy and use considerations and discussions with all pertinent stakeholders around promotion of equitable student value.

We borrow from the May 2021 Postsecondary Value Commission report to define "student value" as a combination of positive student learning gains during the postsecondary experience and positive long-term economic returns for students received postgraduation relative to postsecondary education costs incurred.

The Generative AI Policy Equity Considerations image below is adapted from the Postsecondary Value Commission report's conceptualization of the pipeline to equitable value.

Generative AI tools already are being deployed successfully by colleges and universities, for example to power predictive analytics for use in academic advising. A senior administrator at Georgia State University cites the use of predictive analytics and "data-driven, personalized advising" as a major reason the university has increased its graduation rate by 35 percent over the last 15 years, with no disparities in graduation rates by race or ethnicity.

A key principle of the Universal Design for Learning Guidelines created to help learners become "expert learners" is to provide learners with multiple options for "engagement," "representation" and "action and expression." Our challenge is to try to understand how, when and why use of generative AI by students and faculty can be an equitable and effective option for learning.

If higher education administrators and faculty members respond to the uncertainties of our new generative AI present and future with speed, with strategic purpose and with inclusive focus on equitable student value, we have an opportunity to contribute positively to higher education, economic mobility and social good.

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AI policy advice for administrators and faculty (opinion)

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Post-pandemic higher education just got interesting. Generative artificial intelligence models such as ChatGPT-released publicly in November 2022-have higher education administrators, faculty and students scrambling to respond to this powerful technology. Pundits include those who fear that the college essay is dead as well as those who counter that the college essay is still very much alive, with many other observers landing somewhere in the middle.

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Research Guides: APA Style 7th Edition: ChatGPT & AI Tools

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This guide provides information and examples (in-text, references, and formatting) to help you cite sources in APA style. Why cite? Citing sources gives credit to the author(s) whose work you used to support your research.

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This document was developed by the Office of the Academic Deans in robust collaboration with the Center for Writing and Learning, the Faculty Development Center, Collins Memorial Library, Educational Technology, and the Academic Standards Committee. It will be updated if and when any relevant policies change, as well as to add new resources and guidance. Image produced with OpenAI's DALL-E 2.

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AI-Based Writing Tools: Guidance and Policy

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This document was developed by the Office of the Academic Deans in robust collaboration with the Center for Writing and Learning, the Faculty Development Center, Collins Memorial Library, Educational Technology, and the Academic Standards Committee. It will be updated if and when any relevant policies change, as well as to add new resources and guidance.

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Why All Our Classes Suddenly Became AI Classes

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As AI panic spreads across academia, Wharton educators Ethan and Lilach Mollick offer advice for crafting classroom policies and assignments that incorporate the use of AI tools such as ChatGPT and other large language models to elevate student learning.

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Many of you may be aware of the press around the new AI open tool, ChatGPT. ChatGPT is a tool that uses machine learning to generate text in response to a wide range of prompts. There are many open questions regarding how effective the tool is at generating text and how its existence impacts writing instruction moving forward. It is important to note that UCI has world leaders in the areas of writing instruction and education technology. People on campus are actively engaged in evaluating this and other AI-based tools for their impact and effectiveness from a wide range of perspectives. As we learn more, we will provide regular updates to the campus community.

This email provides instructors with some initial information on the tool and offers recommendations for elements they should address in their courses/syllabi.

If you are looking for more information on ChatGPT, please consider attending the free webinar co-hosted by the WRITE Center and the National Writing Project or attending a locally hosted presentation:

ChatGPT, Generative AI, and the Future of Education: Friday, January 13 from 12:00 pm to 1:00 pm (PST). Located in the Public Service Building 270, (next to UCI Parking Office, above the police station) or via Zoom: https://uci.zoom.us/j/95325363357

2. If your course includes essay writing, you should consider addressing ChatGPT explicitly with your class, and even demonstrate the shortcomings and challenges of using it to generate truly effective writing for the types of prompts we typically use in college courses. (In fact, it is a good idea to test your prompts on ChatGPT to evaluate what ChatGPT outputs and potentially refine your writing prompts.) Working explicitly with your students is one of the best ways to avoid academic integrity issues.

3. It is important to note that under the current conditions, using ChatGPT to generate essays for submission for lower division writing will be considered a violation of academic integrity (see sample of lower division writing syllabus text below). However, as with any tool, individual instructors should determine how specific tools are used within their course. Knowing that individual faculty may make different choices within their specific classes, it is critical that we communicate clearly to students what will or will not be considered a violation in a particular course. For example, when can tools be used for testing and brainstorming versus work for submission? Also, it is useful to remind students that the usage of tools will be course-specific and dependent on individual course goals.

4. For your reference, here is the language from the Composition lower division writing course syllabi:

Academic Integrity for Your Writing Class: The Composition Program and its teachers assume that work submitted by students-all process work, drafts, low-stakes writing, final versions, and all other submissions-will be generated by the students themselves, working individually or in groups. This means that the following would be considered violations of academic integrity by the Composition Program:

1) if a student has another person/entity do the writing of any substantive portion of an assignment for them, which includes hiring a person or a company to write essays and drafts and/or other assignments, research-based or otherwise, and using artificial intelligence affordances like ChatGPT;

2) if a student submits the same work for more than one class without consulting with the instructors.

5. We will continue researching and evaluating ChatGPT, both for potential pedagogical uses and in the context of academic integrity violations. As various tools and information become available, we share them through a range of channels, including the Campus Writing and Communication Coordinator Daniel M. Gross, the Division of Teaching Excellence and Innovation, and EEE/Canvas websites.

If you have any questions or please reach out to dtei@uci.edu

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Many of you may be aware of the press around the new AI open tool, ChatGPT. ChatGPT is a tool that uses machine learning to generate text in response to a wide range of prompts. There are many open questions regarding how effective the tool is at generating text and how its existence impacts writing instruction moving forward.

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Course Policies related to ChatGPT and other AI Tools

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Promoting Academic Integrity in Your Course | Center for Teaching Innovation

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Seemingly every year, there is a new platform or website that prompts us to think about how we are assessing student learning and how we can ensure that students are demonstrating what they know with integrity. What follows are several strategies for promoting academic integrity, as well as some spe…

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Contract cheating, the practice of engaging a third party to complete student assignments, is a growing trend in academic misconduct.

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A new sheriff is coming to the wild ChatGPT west

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You know something big is happening when the CEO of Open AI, the creators of ChatGPT, starts advocating for " regulatory guardrails". Sam Altman testified to the US Senate Judiciary Committee this week that the potential risks for misuse are significant, echoing other recent calls by former Google pioneer, the so-called " godfather of A I", Geoffrey Hinton.

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Since November of 2022, I've received 22 emails from the president's office at Tulane University, where I'm a graduate student. Most are the sort of pleasant and predictable institutional announcements that arrive around various holidays; one reports a significant university medical partnership; some acknowledge high-level changes of leadership in various schools and institutes; the most recent pertain to commencement. From the administration of my department's college there have been seven, each a monthly newsletter announcing faculty awards, alumni achievements, capital campaigns, and various monthly happenings. From the dean's office, exactly two: invitations to "Catch Up With the Dean" events, featuring "cornhole boards, baseball/softball gloves and Spikeball, as well as your favorite swag and snacks!" Eleven emails from the Office of Equity, Diversity, and Inclusion; four from the Office of Human Resources and Institutional Equity; 54 from the Office of Graduate and Postdoctoral Studies; and two from the provost's office.

Not a single one of these emails has mentioned one of the most important recent developments in higher education, the November 2022 launch of AI chatbot text-generation technology, better known under the trademark ChatGPT. Its already-widespread use among undergraduates is presenting enormous challenges to faculty across the country.

"At any given time," Owen Kichizo Terry recently wrote in these pages, "I can look around my classroom and find multiple people doing homework with the help of ChatGPT." Or as a graduate student at a large state university told me, "We had students in our upper-level courses turn in essays written entirely by AI ... but from what I've heard, even more of them will prompt the AI and then modify the answer themselves - I think that is already very widely used."

Fellow graduate instructors in my own department have reported encountering student work this past semester that smelled strongly of AI generation. But with no dedicated institutional response to the issue, and an already-byzantine set of procedures for reporting derelictions of academic integrity, nobody in charge of a classroom had clear guidelines for what to do. Some abandoned traditional at-home essay-writing for in-class, handwritten tests and oral exams. But even then, much of the work produced in class had a vague, airy, Wikipedia-lite quality that raised suspicions that students were memorizing and regurgitating the inaccurate answers generated by ChatGPT.

And a humanities professor at a state university told me that he worries that adapting existing disability accommodations - extra time on tests, distraction-free environments, allowances for typing instead of writing longhand - to the new technological landscape while ensuring the integrity of student work will be forbiddingly difficult. Meanwhile, students are still experiencing a "stunning" level of post-pandemic disconnection from schoolwork and campus life. Faced with these challenges and frustrations, however, college administrations have largely remained silent on the issue, leaving teaching staff to fend for themselves.

The silence is howling, considering the gusto with which higher-ed officers and administrators have taken on the role of delivering pronouncements on issues various and sundry. Blake Smith noted last year that "administrators seem to feel expected to speak to their campuses, and to the world beyond, about current events, even though the content of their speech is often studiedly contentless - and even though most of us never open the emails." Yet despite the proliferation of official statements on racism, the Russia-Ukraine War, climate change, and so forth - and despite the fact that at least one university has been found using AI to generate one such statement in response to a mass shooting at another campus - silence yet reigns on a concrete issue of great importance to the day-to-day functioning of educational institutions and the work of students and faculty alike.

On many campuses, high-course-load contingent faculty and graduate students bear much of the responsibility for the kinds of large-enrollment, introductory-level, general-education courses where cheating is rampant. According to the International Center for Academic Integrity, more than 60 percent of college students admit to participating in some kind of cheating. Add to this already-dismal situation the most easily accessible and lowest-cost cheating technology ever devised and watch the entire system of college education strain at its rivets. How can large or even mid-sized colleges withstand the flood of nonsense quasi-plagiarism when academic-integrity first responders are so overburdened and undercompensated?

A meaningful education demands doing work for oneself and owning the product of one's labor, good or bad. The passing off of someone else's work as one's own has always been one of the greatest threats to the educational enterprise. The transformation of institutions of higher education into institutions of higher credentialism means that for many students, the only thing dissuading them from plagiarism or exam-copying is the threat of punishment. One obviously hopes that, eventually, students become motivated less by fear of punishment than by a sense of responsibility for their own education. But if those in charge of the institutions of learning - the ones who are supposed to set an example and lay out the rules - can't bring themselves to even talk about a major issue, let alone establish clear and reasonable guidelines for those facing it, how can students be expected to know what to do?

So to any deans, presidents, department chairs, or other administrators who happen to be reading this, here are some humble, nonexhaustive, first-aid-style recommendations. First, talk to your faculty - especially junior faculty, contingent faculty, and graduate-student lecturers and teaching assistants - about what student writing has looked like this past semester. Try to find ways to get honest perspectives from students, too; the ones actually doing the work are surely frustrated at their classmates' laziness and dishonesty. Any meaningful response is going to demand knowing the scale of the problem, and the paper-graders know best what's going on. Ask teachers what they've seen, what they've done to try to mitigate the possibility of AI plagiarism, and how well they think their strategies worked. Some departments may choose to take a more optimistic approach to AI chatbots, insisting they can be helpful as a student research tool if used right. It is worth figuring out where everyone stands on this question, and how best to align different perspectives and make allowances for divergent opinions while holding a firm line on the question of plagiarism.

Second, meet with your institution's existing honor board (or whatever similar office you might have for enforcing the strictures of academic integrity) and devise a set of standards for identifying and responding to AI plagiarism. Consider simplifying the procedure for reporting academic-integrity issues; research AI-detection services and software, find one that works best for your institution, and make sure all paper-grading faculty have access and know how to use it.

Lastly, and perhaps most importantly, make it very, very clear to your student body - perhaps via a firmly worded statement - that AI-generated work submitted as original effort will be punished to the fullest extent of what your institution allows. Post the statement on your institution's website and make it highly visible on the home page. Consider using this challenge as an opportunity to reassert the basic purpose of education: to develop the skills, to cultivate the virtues and habits of mind, and to acquire the knowledge necessary for leading a rich and meaningful human life.

AI technology, I suspect, will pose a significant threat to many institutions of higher learning, and especially to the already-ailing enterprise of the academic humanities. Smaller schools with more-intimate learning environments - not only high-status, prestigious liberal-arts colleges, but also provincial satellite universities and community colleges where faculty have closer student relationships and more familiarity with students' work - may very well emerge relatively unscathed. But at bigger universities with large classrooms and overburdened teachers, where struggling students can remain anonymous in a cavernous lecture hall, the easy option may prove too tempting. It will take an aggressive and comprehensive institutional response to dissuade students from plagiarism. The time to act was months ago, well before term-paper deadlines. The second-best time is now.

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Opinion | ChatGPT Is a Plagiarism Machine

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Since November of 2022, I've received 22 emails from the president's office at Tulane University, where I'm a graduate student. Most are the sort of pleasant and predictable institutional announcements that arrive around various holidays; one reports a significant university medical partnership; some acknowledge high-level changes of leadership in various schools and institutes; the most recent pertain to commencement.

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Is an ice cream sandwich a sandwich? How about a sushi roll, chicken wrap or sloppy joe? These were some of the prompts included in a classification and model-building assignment in the fall 2022 Knowledge-Based AI course that David Joyner taught at the Georgia Institute of Technology.

But when Joyner, executive director of online education and the online master of science in computer science and senior research associate, was scheduled to teach the course again in the spring 2023 semester, he reconsidered the assignment in the presence of ChatGPT -the OpenAI chat bot that burst onto the global stage in late 2022 and sent shock waves across academe. The bot interacts with users in a conversational way, including by answering questions, admitting its mistakes, challenging falsehoods and rejecting inappropriate requests.

"I'd used the questions for five years because they were fun questions," Joyner said. "But ChatGPT's answer was so precise that I'm pretty sure it was learning from my own best students," whom he suspected had posted their work online. Joyner replaced several of the sandwich options with avocado toast, shawarma, pigs in a blanket, Klondike bar and Monte Cristo. He also updated the academic misconduct statement on his syllabus to "basically say that copying from ChatGPT isn't different from copying from other people." Such efforts, Joyner acknowledges, may be a temporary fix.

As faculty members ponder academe's new ChatGPT-infused reality, may are scrambling to redesign assignments. Some seek to craft assignments that guide students in surpassing what AI can do. Others see that as a fool's errand-one that lends too much agency to the software.

Either way, in creating assignments now, many seek to exploit ChatGPT's weaknesses. But answers to questions concerning how to design and scale assessments, as well as how to help students learn to mitigate the tool's inherent risks are, at best, works in progress.

"I was all ready to not stress about the open AI shit in terms of student papers, because my assignments are always hyper specific to our readings and require the integration of news articles to defend claims etc. ... BUT THEN I TRIED IT ..." Danna Goldthwaite Young, professor of communication at the University of Delaware, wrote this week in introducing a thread on Twitter.

Students Should Surpass AI-or Not

When Boris Steipe, associate professor of molecular genetics at the University of Toronto, first asked ChatGPT questions from his bioinformatics course, it produced detailed, high-level answers that he deemed as good as his own. He still encourages his students to use the chat bot. But he also created The Sentient Syllabus Project, an initiative driven by three principles: AI should not be able to pass a course, AI contributions must be attributed and true, and the use of AI should be open and documented.

"When I say AI cannot pass the course, it means we have to surpass the AI," Steipe said. "But we also must realize that we cannot do that without the AI. We surpass the AI by standing on its shoulders."

Steipe, for example, encourages students to engage in a Socratic debate with ChatGPT as a way of thinking through a question and articulating an argument.

"You will get the plain vanilla answer-what everybody thinks-from ChatGPT," Steipe said, adding that the tool is a knowledgeable, infinitely patient and nonjudgmental debate partner. "That's where you need to start to think. That's where you need to ask, 'How is it possibly incomplete?'"

But not every faculty member is convinced that students should begin with ChatGPT's outputs.

"Even when the outputs are decent, they're shortcutting the students' process of thinking through the issue," said Anna Mills, English instructor at the College of Marin. "They might be taking the student in a different direction than they would have gone if they were following the germ of their own thought."

Some faculty members also challenge the suggestion that students should compete with AI, as such framing appears to assign the software agency or intelligence.

"I do not see value in framing AI as anything other than a tool," Marc Watkins, lecturer in composition and rhetoric at the University of Mississippi, wrote in an email. Watkins, his department colleagues and his students are experimenting with ChatGPT to better understand its limitations and benefits. "Our students are not John Henry, and AI is not a steam-powered drilling machine that will replace them. We don't need to exhaust ourselves trying to surpass technology."

Still, others question the suggestion that AI-proofing a course is difficult.

"Creating a course that AI cannot pass? Shouldn't take very long at all," Robert Cummings, associate professor of writing and rhetoric at the University of Mississippi, wrote in an email. "Most AI writing generators are, at this stage, laughably inaccurate ... Testing AI interactions with components of a course might make more sense."

But Steipe is pondering a possible future in which descendants of today's AI-writing tools raise existential questions.

"This is not just about upholding academic quality," Steipe said. "This is channeling our survival instincts. If we can't do that, we are losing our justification for a contribution to society. That's the level we have to achieve."

How Faculty Can Exploit ChatGPT's (Current) Weaknesses

In the future, faculty members may get formal advice about how to craft assignments in a ChatGPT world, according to James Hendler, director of the Future of Computing Institute and professor of computer, web and cognitive sciences at Rensselaer Polytechnic Institute.

In the meantime, faculty are innovating on their own.

In computer science, for example, many professors have observed that AI writing tools can write codes that work, though not necessarily of the kind that humans find easy to edit, Hendler said. That observation can be exploited to create assignments that distinguish between content and creative content.

"We try to teach our students how to write code that other people will understand, with comments, mnemonic variable names and breaking code up into meaningful pieces," Hendler said. "That's not what's happening with these systems yet."

Also, since ChatGPT's ability to craft logical arguments can underwhelm, assignments that require critical thinking can work well in the presence of ChatGPT.

"It's not very good at introspecting," Steipe said. "It just generates. You often find non sequiturs or arguments that don't hold water. When you point it out to the to the AI, it says, 'Oh, I got something wrong. I apologize for the confusion.'"

Several faculty members contacted for this article mentioned that lessons learned from the earlier emergence of Wikipedia hint at a path forward. That is, both the online encyclopedia and OpenAI's chat bot offer coherent prose that is prone to errors. They adapted assignments to mix use of the tech tools with fact-checking.

Moving forward, professors can expect students to use ChatGPT to produce first drafts that warrant review for accuracy, voice, audience and integration to the purpose of the writing project, Cummings wrote. As the tools improve, students will need to develop more nuanced skills in these areas, he added.

An Unsolved Problem

Big tech plans to mainstream AI writing tools in its products. For example, Microsoft, which recently invested in ChatGPT, will integrate the tool into its popular office software and sell access to the tool to other businesses. That has applied pressure to Google and Meta to speed up their AI-approval processes.

"My classes now require AI, and if I didn't require AI use, it wouldn't matter, everyone is using AI anyway," Ethan Mollick, associate professor of management and academic director of the Wharton Interactive at the University of Pennsylvania, wrote on his blog that translates academic research into useful insights.

But big tech's speed in delivering AI products to market has not always been accomplished with care. Social media platforms, for example, were once naïvely celebrated for bringing together those with shared interests, not realizing at the time that the platforms also brought together supporters of terror, extremism and hate.

Meta's release of a ChatGPT-like chat bot several months before OpenAI's product received a tepid response, which Meta's chief artificial intelligence scientist, Yan LeCun, blamed on Meta being " overly careful about content moderation," according to The Washington Post.(LeCun spoke with Inside Higher Ed about challenges in computer science in September.) Faculty members may need to help students learn to mitigate and address inherent, real-world harm new tech tools may pose.

"The gloves are off," Steipe said of the huge monetary driver of the emergence of sophisticated chat bots. In higher education, this may mean that the ways in which professors assess students may change. "We've heavily been basing assessment on proxy measures, and that may no longer work."

Professors may assess their students directly, but that level of personal interaction generally does not scale. Still, some are encouraged to find themselves on the same side, so to speak, as their students.

"Our students want to learn and are not in a rush to cede their voices to an algorithm," Watkins wrote.

Such alignment, when present, may offer comfort to the heady disruption academics have experienced since ChatGPT's release, especially as bigger questions-beyond how to assign grades-loom.

"The difference between the AI and the human mind is sentience," Steipe said. "If we want to teach as an academy in the future that is going to be dominated by digital 'thought,' we have to understand the added value of sentience-not just what sentience is and what it does, but how we justify that it is important and important in the way that we're going to get paid for it."

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ChatGPT sparks debate on how to design student assignments now

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Is an ice cream sandwich a sandwich? How about a sushi roll, chicken wrap or sloppy joe? These were some of the prompts included in a classification and model-building assignment in the fall 2022 Knowledge-Based AI course that David Joyner taught at the Georgia Institute of Technology.

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Here’s What Happens When Your Lawyer Uses ChatGPT

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A lawyer representing a man who sued an airline relied on artificial intelligence to help prepare a court filing. It did not go well.

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May 22 (Reuters) - ChatGPT's creator OpenAI is testing how to gather broad input on decisions impacting its artificial intelligence, its president Greg Brockman said on Monday.

At AI Forward, an event in San Francisco hosted by Goldman Sachs Group Inc (GS.N) and SV Angel, Brockman discussed the broad contours of how the maker of the wildly popular chatbot is seeking regulation of AI globally.

One announcement he previewed is akin to the model of Wikipedia, which he said requires people with diverse views to coalesce and agree on the encyclopedia's entries.

"We're not just sitting in Silicon Valley thinking we can write these rules for everyone," he said of AI policy. "We're starting to think about democratic decision-making."

Another idea that Brockman discussed, on which OpenAI elaborated in a blog post Monday, is that governments around the world should coordinate to ensure AI is developed safely.

Since the Nov. 30 launch of ChatGPT, generative AI technology that can spin uncannily authoritative prose from text prompts has captivated the public, making the program the fastest growing app of all time. AI has also become a focus of concern over its ability to create deepfake pictures and other misinformation.

In assessing the path forward for AI, Brockman looked at Wikipedia as well as elsewhere. He and OpenAI said a body like the International Atomic Energy Agency (IAEA) could place restrictions on deployment, vet compliance with safety standards and track usage of computing power.

Another suggestion was a global agreement to limit the annual growth of frontier AI capabilities, or a joint global project that major governments could participate in.

OpenAI CEO Sam Altman proposed various ideas to U.S. lawmakers last week for setting guardrails for artificial intelligence, among them requiring licenses to develop the most sophisticated AI models and establishing a related governance regime. He is visiting European policymakers this week.

Reporting By Jeffrey Dastin in San Francisco

Our Standards: The Thomson Reuters Trust Principles.

Jeffrey Dastin
Thomson Reuters

Jeffrey Dastin is a correspondent for Reuters based in San Francisco, where he reports on the technology industry and artificial intelligence. He joined Reuters in 2014, originally writing about airlines and travel from the New York bureau. Dastin graduated from Yale University with a degree in history. He was part of a team that examined lobbying by Amazon.com around the world, for which he won a SOPA Award in 2022.

Anna Tong
Thomson Reuters

Anna Tong is a correspondent for Reuters based in San Francisco, where she reports on the technology industry. She joined Reuters in 2023 after working at the San Francisco Standard as a data editor. Tong previously worked at technology startups as a product manager and at Google where she worked in user insights and helped run a call center. Tong graduated from Harvard University. Contact:4152373211

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OpenAI is exploring collective decisions on AI, like Wikipedia entries

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May 22 (Reuters) - ChatGPT's creator OpenAI is testing how to gather broad input on decisions impacting its artificial intelligence, its president Greg Brockman said on Monday. At AI Forward, an event in San Francisco hosted by Goldman Sachs Group Inc (GS.N) and SV Angel, Brockman discussed the broad contours of how the maker of the wildly popular chatbot is seeking regulation of AI globally.

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The ed-tech world has been buzzing for months about ChatGPT, the powerful artificial intelligence tool that can respond to seemingly any prompt. Observers have speculated about how it might change the nature of teachers' jobs and personalize education for students.

Now, some in ed tech are betting it can improve tutoring-a strategy that has boomed as schools struggle to help kids make up lost ground after months of disrupted learning.

In March, the online learning platform Khan Academy debuted a new AI chatbot-Khanmigo-designed to tutor and coach students in one-on-one interactions. Saga Education, a nonprofit that works with districts to design and implement tutoring programs, is starting to use AI to analyze tutors' performance and offer feedback. And Varsity Tutors, a platform that provides private tutoring and also works with schools, is rolling out AI-generated lesson plans.

Developing and staffing the kind of tutoring that research has shown is most effective-often referred to as high quality, or high-impact tutoring-is complex, time-consuming, and expensive. Tutors meet with students at least three times a week, in small groups or one-on-one. Work should be targeted to a specific subject and aligned to high-quality curriculum, and should develop strong tutor-tutee relationships.

"High-impact tutoring is not homework help. They're not sporadically dropping in," said Carly Robinson, a senior researcher at Stanford University's Graduate School of Education who works with the National Student Support Accelerator, a group promoting research-based tutoring programs.

Experts say AI can take over some pieces of this puzzle, but there are potential pitfalls, too.

An AI-enabled tutoring program can give students immediate, personalized feedback, said Helen Crompton, an associate professor of instructional technology at Old Dominion University in Norfolk, Va. And the kinds of questions that students ask of the AI can offer teachers and tutors an insight into their thinking.

But there's also the possibility that a virtual tutor could present students with incorrect information, or reinforce bias, Crompton said. And then, there's one crucial element of good tutoring that experts agree an AI can't replace: the student-tutor relationship.

"AI is all brain and no heart," Crompton said. "There's a human aspect that should always be added in."

How tutoring companies are adapting

Since ChatGPT exploded on the scene at the end of 2022, educators have debated how the tool, which generates its answers based on taking in huge amounts of written text, could be used in education. Still, the tool is far from foolproof: It plagiarizes, often makes up information, and has trouble with certain tasks, like solving math problems.

For now, in education, "we're at the stage of the early adopters," said Rob Moore, an assistant professor of educational technology at the University of Florida. Some of these early adopters are tutoring companies.

The most well-known of these might be Khan Academy, which debuted its AI tutor chatbot early this year. Called Khanmigo, the name references the Spanish words conmigo ("with me") and amigo ("friend"). The tool combines the technology that powers ChatGPT with tutoring-specific instructions and relevant information from Khan Academy's platform, said Kristen DiCerbo, the company's chief learning officer.

"If you just go to ChatGPT, and type in something, that's going to get you a different experience than what we do," she said.

Say, for example, that a student types "I'm stuck" into the chatbot. "We don't just send, 'I'm stuck,' to the model," DiCerbo said. Khanmigo also gets a short prompt about how to be a Socratic tutor, asking students questions to get to the root of their misunderstanding, rather than just giving them the answer.

It also has access to the Khan Academy site-what course student is in, what unit the class is working on now, and the specific skills that the student has or hasn't mastered. It uses all of that information to craft its response, DiCerbo said.

Khan Academy is now piloting Khanmigo in schools. Most teachers are using it in a classroom context to provide students with individualized support while a teacher is present, rather than in a separate designated tutoring block, DiCerbo said.

In Khan Academy's model, the AI is the tutor: Students ask Khanmigo questions and the bot helps them work through the problem. Other companies are using the ChatGPT technology to support the processes around tutoring-creating lesson plans, writing session notes, and offering tutors feedback, but not actually as a tutor.

Varsity Tutors, which works with about 200 school districts, is rolling out AI-generated lesson plans, which will be designed to align to standards and reflect individual students' learning progressions, in the 2023-24 school year, said Anthony Salcito, the chief institutional business officer at Nerdy, the parent company for Varsity Tutors.

Right now, Varsity Tutors is testing AI-produced session notes: feeding the tool transcripts of tutoring sessions and asking it to provide a summary. "That's exciting, because it brings us consistency," Salcito said. "We can consume all the notes and then track patterns over time."

Finally, Saga Education, a tutoring nonprofit that works with school districts, is using AI to give the tutors feedback. The organization has partnered with the University of Colorado Boulder, using AI technology developed by researchers there to analyze recordings of tutoring sessions, said Krista Marks, chief technology officer at Saga Education.

The AI has been trained on rubrics of effective tutoring, measuring recordings of the sessions against those markers and offering feedback. Tutoring site directors can then review feedback from multiple sessions, and use that to identify strengths and weaknesses for coaching sessions with the tutors.

The tool can offer site directors a way to personalize coaching conversations with their staff, without having to spend all day sitting in on different tutoring sessions, Marks said.

Marks, Salcito, and DiCerbo said that the next frontier is more personalization.

Next year, Saga Education will pilot technology that offers tutors real-time recommendations about the next steps to take in a tutoring session, adapting suggestions to individual student interests-offering a two-step equation math problem about basketball, for example.

Khan Academy is hoping to tailor Khanmigo's assistance more closely to student needs. Right now, DiCerbo said, the AI knows where kids are in a unit and their past performance. But it doesn't know exactly why students are struggling, or how to pinpoint and address prerequisite skills that they need but might not have mastered.

"It's not about, I need to just keep banging my head against the wall on this grade level thing," DiCerbo said. "I need to fill in these gaps on things I haven't learned yet."

For now, Khanmigo can't do that, DiCerbo said: "It's shaky at best."

When AI gets the answers wrong

There are other, more immediate issues with AI tutoring technologies, too. Khanmigo, for example, struggles with math-a problem ChatGPT has as well.

"If you just ask it to do the problem, it usually does it correctly," DiCerbo said. Sometimes, though, it gets the wrong answer. And it has difficulty with math conversations, where it has to discuss problem-solving steps and strategies with students.

Khan Academy offers teachers and students an option to give feedback and flag interactions where the AI gives the wrong information. Khanmigo also asks kids to explain their reasoning when its answer doesn't match a student's, DiCerbo said. "It allows the model to check its own work and work through that," she said.

Pointing out these flaws to students can help them understand that AI isn't infallible, said Moore, of the University of Florida. "You can flip that and make that a teaching moment."

Still, errors could introduce new challenges in tutoring, where a student is already struggling-and might not have a good enough grasp on the material to recognize an AI's misstep.

Not every student is going to be well-served by an AI tutor, said Robinson, the Stanford researcher. Beyond these technical limitations, there's also a big question of motivation. Would the students who are in most need of support actually use the tool as intended?

When districts have provided on-demand optional programs in recent years, most students don't actively engage with them, she said. The kids that do take advantage of them are more likely to be higher-achieving students-not typically the demographic that schools were most hoping to reach, she added.

"Delivering a scripted curriculum that can be responsive to students' answers is something that AI could take on. Where we might actually need a human is where it comes to the relationships and the motivation and the engagement aspects of tutoring," Robinson said.

All of the company representatives said that AI is meant to complement teachers and tutors-not replace them. "If we do not have teachers, tutors, caring adults to guide students in how to ask good questions ... I think we're lost," said Marks, of Saga Education.

'We haven't even scratched the surface' on ethics

In examples of Khanmigo in action that Khan Academy has shared, the bot is encouraging-gently prompting students to persevere and praising them when they get the right answer.

These cheery interactions with students are part of the programming, Crompton said. "It doesn't actually have a personal relationship with students. It doesn't actually have that investment in how a student is doing."

And that's a concern for some researchers: How an AI acts is based on the source material and instructions it's given-a fact that introduces "a lot of ethical concerns that we haven't even scratched the surface on," said Robinson.

AI tools can be designed to have a positive and helpful attitude, "but they could just as easily be designed to bully," Robinson said.

Crompton fears the possibility for bias. The technology that powers ChatGPT pulls information from the internet, so it's going to reflect dominant perspectives and ideas in published materials, she said. Take social studies as an example, a discipline whose subjectivity has led repeatedly to fierce debates over the years over which narratives should be taught.

"Those textbooks, those notes, all those have bias in them. So we are still going to have a biased product in the end," she said.

These fallibilities mean that districts need to carefully vet AI tutoring tools, the same way they would vet other materials and programs that they bring into schools, Crompton said.

"We'll need to do our due diligence and recognize that there will be a lot out there provided," she said. "And some AI programs will be good, and some won't be as good."

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The ed-tech world has been buzzing for months about ChatGPT, the powerful artificial intelligence tool that can respond to seemingly any prompt. Observers have speculated about how it might change the nature of teachers' jobs and personalize education for students.

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In the seven months since ChatGPT was released, the world of generative AI has progressed at an almost impossible pace. Trying to keep up with weekly updates on its impact on education has been like drinking from a firehose. The next big thing on the generative AI front that we need to pay urgent attention to are AI writing co-pilots that will be directly embedded into productivity suites like Microsoft Office. These "co-pilots" are AI-powered assistants designed to assist you to generate content.

The companies behind the productivity tools that most of us and our students use, Microsoft and Google, are getting their versions of AI co-pilots ready for imminent release. . Microsoft 365 Copilot and Google Duet AI will embed generative AI directly into software like Microsoft Word and Google This means that we will all have access to text generation AI right from within the spaces where we write. Notion, a popular app used by many students, already has an AI-powered writing assistant.

Ethan Mollick, a pragmatic and thoughtful educator with AI from the Wharton School in the US, describes this as a " crisis of meaning ":
I don't see a way that we avoid dealing with this coming storm. So many important processes assume that the amount and quality of our written output is a useful measure of thoughtfulness, effort, and time. If we don't start thinking about this shift in meaning now... we are likely to face a series of crises of meaning, as centuries-old approaches to filtering and signalling lose all of their value.
So, what happens to assessments now?

but higher costs. And, as assessment experts Liz Johnson, Helen Partridge & Phillip Dawson from Deakin University say, exams can have Jason Lodge from the University of Queensland and colleagues, and Michael Webb from Jisc UK's National Centre for AI, have written about the main options regarding assessments. Webb writes that we can either avoid it, try and outrun it, or adapt to AI . All of these responses are legitimate, and all have their short- and long-term benefits and drawbacks. Avoiding it includes reverting to oral or otherwise invigilated exams, which have stronger assessment security questionable authenticity. That said, there is certainly a place for secured assessments in order to assure learning outcomes are met - more on this towards the end of this piece.

Outrunning it involves trying to design assessments that AI has more difficulty completing - but the risks are that our redesigns will only be temporarily effective as the pace of AI development accelerates and will make the assessment more inequitable for many of our students. Modifying stimulus (e.g. using images in questions) has been suggested, but ability to parse images will be released to the public. Modifying the content of assessment is also a popular suggestion, such as connecting with personal events, writing reflections, or linking to class material - but recent work has shown that GPT writes higher-quality reflections than humans , and a larger context window allows students to send it as much relevant class material as needed. Modifying outputs that students produce is also a common response, such as changing assessments to in-class presentations or multimodal outputs - but rapid advances in voice cloning AIs and and image generation AIs make outrunning AI almost futile. Besides, students could just ( and have, to excellent effect ) use AI to generate an in-class presentation. This approach also has the potential to exacerbate achievement gaps for those students skilled in the use of AI and those who are not.

Adapting to it means we need to rethink how we assess - as Lodge writes, , but also much harder. The imminent arrival of AI writing co-pilots makes this even more important - this is a more effective, longer-term solution students will have AI asking to be invited into their writing process right from the start, through an innocuous prompt to us humans like "Help me write" (Google) or "Describe what you'd like to write" (Microsoft). With this capability in place within the mainstream productivity tools also makes it inescapable - it will become specious and even meaningless for us to "ban" their use.

"Assess the process", "use authentic assessment" - but how exactly?

Changing assessments to assess the process and not the product has been a growing retort over the last 6 months in response to generative AI. Lodge puts this elegantly in a recent post :
While generative AI can increasingly reproduce or even surpass human performance in the production of certain artefacts, it cannot replicate the human learning journey, with all its accompanying challenges, discoveries, and moments of insight. It can simulate this journey but not replicate it. The ability to trace this journey, through the assessment of learning processes, ensures the ongoing relevance and integrity of assessment in a way that a focus on outputs cannot. (emphasis added)
Lodge mentions "reflection activities, e-portfolios, nested tasks, peer collaborations, and other approaches" as effective process-based assessments, but acknowledges that these "often do not scale easily or leave too much room for threats to academic integrity". This is especially the case in the coming era of AI writing co-pilots.

And even before generative AI burst on the scene, there have been calls to recalibrate higher education towards more authentic assessment. Through a systematic review, Verónica Villarroel and colleagues determined there were three main dimensions to authentic assessment :

1. Realism (having a realistic task and realistic context)

2. Cognitive challenge

3. Evaluative judgement (developing students' ability to judge quality)

Over the years, we've collected a few examples of authentic assessment on Teaching@Sydney , and the University of Queensland has a handy searchable assessment database with examples of authentic assessments .

But again, in a time when generative AI is so in-your-face and part of the way we [will] work, what is 'authentic', and what is 'process' - and how do we actually assess? Are our assessment approaches built to be effective or to be efficient?

Rediscovering what it means to be human (and assessing this)

Going back to first principles, the Higher Education Standards Framework 2021 legislation reminds us that assessments need to assure that learning outcomes have been met, and that the way that we assess needs to be consistent with these learning outcomes. Specifically, Part A section 1.4 clauses 3 and 4 say:

1. Methods of assessment are consistent with the learning outcomes being assessed, are capable of confirming that all specified learning outcomes are achieved and that grades awarded reflect the level of student attainment.

2. On completion of a course of study, students have demonstrated the learning outcomes specified for the course of study, whether assessed at unit level, course level, or in combination.

There have been calls for a revisit to learning outcomes in the age of AI - the Australian Academic Integrity Network has that "unit and course learning outcomes, assessment tasks and marking criteria may require review to incorporate the ethical use of generative AI". posted on the TEQSA website Given the close and dynamic interplay between learning outcomes and assessments, the increasing presence of AI in common productivity tools suggests we may need to rethink learning outcomes as well.

What do we want our students to know and be able to do when they leave our units and our courses? At Sydney, we want our graduates to have the skills and knowledge to adapt and thrive in a changing world, improving the wellbeing of our communities and society . But what does this actually mean in practice, in the context of an AI-infused world? Cecilia Chan and colleagues from the University of Hong Kong have asked a similar question, from the perspective of educators . They suggest that there are key human aspects that AI can never replace, such as cultural sensitivity, resilience, relationships, curiosity, critical thinking, teamwork, innovation, ethics, civic engagement, leadership, etc. If these sound familiar, it's because they're also embedded in Sydney's graduate qualities for students.

So perhaps a contemporary set of learning outcomes (and assessments) needs to address these human elements. The ability to be able to judge the quality of their own work and that of their co-pilot may be the most important quality we need to develop. Sure, generative AI can create text and other outputs that mimic these human qualities, but that enhances our prerogative to adapt assessments appropriately to an AI world.

Designing assessments in an era where generative AI is inescapable

Consider this diagram, which we recently presented in the closing keynote of a UK conference on 'Education fit for the future' and had useful conversations on via Twitter afterwards. Much of the early dialogue around generative AI has been around its (mis)use in the bottom right quadrant - high AI contribution and low human contribution. As generative AI becomes more inescapable, we need to consider where along the top half of the diagram each of our assessments sit - and they will necessarily sit at different places, depending on the year level, learning outcomes, and other factors.

Leon Furze helpfully characterises this as an ' AI assessment scale ', where educators need to consider whether and how AI helps students in assessments. We've adapted his scale in the diagram below, to emphasise that AI can also help educators in the design and delivery of assessments.

What are some approaches to assessments that might work in the age of AI writing co-pilots, considering all we've discussed about process, authenticity, and learning outcomes? How might students work productively and responsibly in the top-right quadrant?

Co-creating an output with AI

There are many ways that industry and community groups are already and could potentially leverage generative AI, including content generation, customer insights, software development , media generation, document summarisation, knowledge organisation, and more. What are the steps that we and our students can take through assessments in this context? Here is a strawman for consideration:

1. In your field or discipline, consider the kinds of authentic tasks and authentic contexts that your students may eventually find themselves meeting. This may be producing an annual report for stakeholders, a design proposal for a firm, a policy briefing for government, marketing copy for a client, a scientific report for a journal, a pitch deck for investors, an environmental impact analysis for a local council, a proposal for a museum exhibition, a clinical management protocol for a hospital, a citizen science project outline for the community, etc. At this stage, you don't need to necessarily think about AI. (AI could help you, as an educator, dream up some of these ideas - ).

2. Ensure the assessment is aligned to your learning outcomes. If it doesn't align, you may need to either refine your learning outcomes, or try a different assessment.

3. Draft a marking rubric for the assessment, which is aligned to the learning outcomes. As part of this rubric, you may want to consider incorporating some of the very human qualities encapsulated in the Graduate Qualities as rubric criteria (rows). For example, you may want students to develop and demonstrate information and digital literacy skills, as well as inventiveness. As part of the rubric, consider adding criteria that will allow you to evaluate students' approach to co-writing - see the next section.

4. In the process of starting the assessment, , and the quality of the initial prompt (and follow-up prompts) will determine the quality of the AI output. To design a good prompt that leads to a meaningful output, students will need to clearly specify the task, provide relevant context and examples, and even split complex tasks into subtasks or steps. have students design a good prompt for generative AI, and document this process. There are many considerations when designing a good prompt You can already see that a meaningful engagement with generative AI relies heavily on students having developed some disciplinary expertise. It's important for students to document this as it demonstrates their learning process, critical thinking, and the cognitive challenges they overcome.

5. Once an acceptable draft has been generated by the AI co-pilot, have students critique and enhance this, and document what they do, how they do it, and why. The aim here is for students to improve the AI's outputs by analysing its accuracy, judging its quality, integrating relevant scholarly sources (the AI is unlikely to yield any reliable sources) - all elements of developing evaluative judgement. Again, it's important that students document what they do, how, and why, as it serves as a tool for you to assess the process.

6. If there is space in your curriculum, implement a draft submission at this stage. Students can get feedback and critique from peers, who have also gone through a similar process of using an AI co-pilot.

7. Since we are interested in assessing the process and not (as much) the outcome, at this stage have students submit the amended draft, their documentation (initial prompt and reasoning, and their analysis and improvement steps), their reflections on peer feedback, and their proposed changes going forwards. Assess these as the primary (i.e. most heavily weighted) component of the overall assessment grade - for ideas on how, see the next section.

8. Have students improve the output again, documenting the process as before.

9. Students submit the final output. This, and their documentation, is assessed, but has a lower weighting because we are interested in assessing the process, not the outcome.

Evaluating co-creation with AI

An integral part of the suggested model above is to be able to evaluate the process of making something AI. Some of the following ideas may be useful criteria to include in the marking rubric, alongside other criteria. Ensure that the criteria that you include in your rubric align with your learning outcomes and the Graduate Qualities.

AI prompt design that demonstrates disciplinary expertise: how thoughtfully the student has designed the prompt(s) for AI and considered the complexity and clarity of prompts. High distinction could include a well-structured and deep understanding of disciplinary concepts that are demonstrated in effective prompt design.

Critical evaluation of AI suggestions: how effectively the student evaluates and utilises AI suggestions, as in whether they simply adopt AI-generated content or make conscious choices about what to include. High distinction could include critically making nuanced and evidence-based decisions about what to accept, modify, or reject.

Revision process: how the student has revised AI suggestions and demonstrated their critical thinking skills and disciplinary expertise. High distinction could include an insightful and critical reflection on where AI generated content needed improvement, and why. It could also include a demonstrably significant improvement in the quality of the work.

Information and digital literacy: how the student has evaluated AI-generated content through relevant scholarly sources to enhance the rigour and reliability of the output. High distinction could include the integration of high-quality sources that are appropriately critiqued.

Documentation and reflection on the co-creation process: how the student has recorded appropriate decisions and interactions with the AI co-pilot, and analysed the strengths, weaknesses, and future improvements to these interactions. High distinction could include a clear and ethical articulation of decisions and their reasoning, deep insight into the role of AI in the co-creation process, and suggestions for future practice.

Ethical considerations: students' awareness of the reliability, biases, and other limitations of AI generated content. High distinction could indicate a strong understanding of these issues, with suggestions for mitigating potential problems.

These are by no means an exhaustive or prescriptive list. You will need to determine the most effective way to assess and evaluate these skills for your own teaching context.

In contexts where collaboration with AI is acceptable, authentic, and productive, it may be conceivable that a student who creates something AI may learn more, better hone their critical thinking and information and digital literacy skills, and produce a better artefact. To very loosely paraphrase , Ethan Mollick anchoring bias students may be hurting themselves by not using AI, if AI-enabled writing is of a higher quality. Certainly, we need to be fiercely conscious of many issues of collaborating with AI, not the least because of where the first (in this context, AI-generated) piece of information clouds our judgement.

Assuring learning outcomes

Webb 's strategies of either avoiding, trying to outrun, or adapting to AI are not necessarily stark choices and our final position will no doubt be a mixture of all three.

We want to know our students (and our future bridge builders and dentists) know what they are doing: our purpose and social licence is based on our ability to assure that our graduates have met their learning outcomes. This will no doubt involve some secure summative tasks in degrees and programs which exclude technology to ensure program level outcomes are met. Given the inevitable play off between authenticity, security and cost, we need to consider the responsibilities of each unit versus those of the program. With generative AI baked into our productivity tools, this may involve appropriate methods of assurance in these exceptional 'high stakes' assessments. A s Cath Ellis from UNSW , perhaps we need to stop agonising about over-securing every single assessment. Assessments where students collaborate with AI may help them learn critical skills and develop deeper disciplinary expertise, whilst assessments that are highly secured may help us (and them) additionally assure learning outcomes are met.

If we are honest, our present assessment regime reflects our need to deliver efficiency , reflecting the workload implications of large enrolments and tight deadlines. Assessment for and of learning is not the only consideration that a unit coordinator tasked with returning results to a deadline and within a limited budget needs to consider. Whilst generative AI may offer some efficiencies in designing and delivering assessments , it also requires us to consider where and what to assess.

As the costs, security, and reliability of 'traditional' assessments soar, is this a time to think about assessing learning happens - such as in the laboratory, in the design studio, and in the tutorial? At the moment, assessment weightings and hence student behaviours favour products (notably assignments and exams) whereas formative learning, development, and evaluative judgement occurs in the tasks in our active learning classes.

Adapting to AI will take time and will probably require a mixture of student skill building, staff development, and a paradigm shift in our understanding of what assessment is for. For students, this will involve foundational digital literacy in using AI (such as generic prompt writing) but this will eventually need to be a discipline-specific skill and part of their knowledge creation methodologies. For staff, we need to rapidly and widely build awareness and support the innovations of early adopters.

The ultimate aim of a Sydney education will perhaps not be changed by the generative AI revolution. Indeed, it should become more real and relevant . Our assessments should require, encourage, rank, and reward the ability to use evaluative judgement on the quality, reliability and relevance of the resources our students use and the outputs they produce.

What now, and what next?

Consider the implications of AI co-pilots in your disciplinary context. Consider what impacts this will have on assessments, particularly written assessments.

Given the HESF requirements, ensure that select assessments are appropriately secured so that your unit and program can demonstrate student achievement of learning outcomes. For other assessments, consider the above guidance on adapting to and embedding AI.

Find out through industry and community groups and other stakeholders how AI is being used (or not) in your field, and where it is effective (or not). Use this to inform your decisions about teaching and assessment.

A working group at the University is drafting a green paper towards a potential University-wide AI strategy. This will seek to help guide the University along a path of ethical, equitable, responsible, and productive use of AI in all facets of the University's work. Wider consultations on this will be opened soon.

For further reading, consider these resources:

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ChatGPT is old news: How do we assess in the age of AI writing co-pilots?

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In the seven months since ChatGPT was released, the world of generative AI has progressed at an almost impossible pace. Trying to keep up with weekly updates on its impact on education has been like drinking from a firehose.

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How AI is Being Used in Higher Education

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How AI is Being Used in Higher Education

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How educators are using AI in the classroom

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To make sure AI benefits teachers and students, educators need to participate in its development, experts say

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Research

The Dark Side of ChatGPT: 6 Generative AI Risks to Watch

Gartner has identified six critical areas where the use of large language models such as ChatGPT can present legal or compliance risks that enterprise organizations must be aware of - or face potentially dire consequences. Organizations should consider what guardrails to put in place in order to ensure responsible use of these tools, the research firm advised.

"The output generated by ChatGPT and other large language model (LLM) tools are prone to several risks," said Ron Friedmann, senior director analyst in Gartner's Legal & Compliance Practice, in a statement. "Legal and compliance leaders should assess if these issues present a material risk to their enterprise and what controls are needed .... Failure to do so could expose enterprises to legal, reputational and financial consequences."

Risks to consider include:

Fabricated and inaccurate answers. Writing produced by generative AI is notorious for being both convincing and potentially incorrect at the same time, Gartner noted. "ChatGPT is also prone to 'hallucinations,' including fabricated answers that are wrong, and nonexistent legal or scientific citations," added Friedmann. "Legal and compliance leaders should issue guidance that requires employees to review any output generated by ChatGPT for accuracy, appropriateness and actual usefulness before being accepted."

Data privacy and confidentiality. Without the proper safeguards, any information entered into ChatGPT may become a part of its training dataset, Gartner pointed out. "Sensitive, proprietary, or confidential information used in prompts may be incorporated into responses for users outside the enterprise," said Friedmann. "Legal and compliance need to establish a compliance framework for ChatGPT use, and clearly prohibit entering sensitive organizational or personal data into public LLM tools."

Model and output bias. OpenAI has been transparent about its efforts to reduce bias in ChatGPT outputs. Yet bias and discrimination are "likely to persist," said Gartner. "Complete elimination of bias is likely impossible," but legal and compliance need to stay on top of laws governing AI bias, and make sure their guidance is compliant," asserted Friedmann.

Intellectual property and copyright risks. Because ChatGPT is trained on internet data - which by nature includes copyrighted material - its outputs "have the potential to violate copyright or IP protections," Gartner warned. Compounding the issue is the fact that ChatGPT does not cite sources for the text it generates. "Legal and compliance leaders should keep a keen eye on any changes to copyright law that apply to ChatGPT output and require users to scrutinize any output they generate to ensure it doesn't infringe on copyright or IP rights," said Friedmann.

Cyber fraud risks. "Bad actors are already misusing ChatGPT to generate false information at scale," Garter said, offering the example of fake reviews that can influence a consumer's purchasing decisions. "Moreover, applications that use LLM models, including ChatGPT, are also susceptible to prompt injection, a hacking technique in which malicious adversarial prompts are used to trick the model into performing tasks that it wasn't intended for such as writing malware codes or developing phishing sites that resemble well-known sites."

Consumer protection risks. Here, Gartner pointed to the importance of disclosing ChatGPT usage to consumers and making sure an organization's ChatGPT use complies with any legal regulations. As an example, the firm said, "the California chatbot law mandates that in certain consumer interactions, organizations must disclose clearly and conspicuously that a consumer is communicating with a bot."

More information is available to Gartner clients in "Quick Answer: What Should Legal and Compliance Leaders Know About ChatGPT Risks?" on the web here.

About the Author

About the author: Rhea Kelly is editor in chief for Campus Technology. She can be reached at [email protected] .

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The Dark Side of ChatGPT: 6 Generative AI Risks to Watch -- Campus Technology

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Gartner has identified six critical areas where the use of large language models such as ChatGPT can present legal or compliance risks that enterprise organizations must be aware of - or face potentially dire consequences. Organizations should consider what guardrails to put in place in order to ensure responsible use of these tools, the research firm advised.

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ChatGPT is a phenomenally powerful tool that has led the way in the rise of generative AI chatbots. However, exporting or saving your ChatGPT conversations in a useful format is not easy. Luckily, there are browser extensions to help you to achieve this easily and quickly.

Let's look at some of the best apps and extensions to help you get the most from ChatGPT.

ShareGPT is a browser extension that can be added to the most popular web browsers, including Microsoft Edge and Google Chrome. The premise of the extension is to allow easy sharing of ChatGPT chats with a single click.

It does this by creating a custom URL for each chat you wish to share. You create the URL by selecting the Share button that is added to the ChatGPT interface:

Clicking this button opens up a new tab with a custom URL containing a complete export chat record. This can then be shared with whoever you need.

Overall, we found this to be simple but effective. If you want a no-frills and easy-to-use way of sharing your ChatGPT conversations, this ticks all the boxes.

Although this is a Google Chrome extension, it also installs on Microsoft Edge. The installation was quick and simple. We installed it on both Edge and Chrome without any problems.

Download: ShareGPT (Free)

2. Export ChatGPT Conversation

There is a lot of hype surrounding Notion, the productivity and note-taking app. So, it is no surprise that there is a ChatGPT extension that can export your conversations directly into Notion.

One neat feature is that the app tidies up the formatting of your conversation before saving it into your Notion workspace. This app isn't just for Notion users, though-there are also options to download your chats as images or to copy them to your clipboard.

We tested its ability to directly export chats into Notion using the conversation below.

Once the chat is ready to export, you can access Export ChatGPT from the extensions drop-down from your browser (usually located to the right of the address bar). This brings up the dialog box shown below.

You will need to link your Notion account to the app, but this was easy. We found that the process was automatic if you had your Notion account open on the same browser.

Overall, if you are a Notion user, this delivers on all its promises. If you aren't a Notion user, there are probably better options. However, again it was simple to install on Microsoft Edge and Google Chrome.

Download: Export ChatGPT Conversation (Free)

This extension works with Chrome, Edge, and Firefox. However, the installation isn't available through the proprietary extension sources for the browsers in question. That said, it is a nice tool once installed and worth a little effort.

Installing an extension manually on Chrome or another browser isn't that difficult. The steps to do this are detailed below.

1. Download the appropriate version from the ChatGPT Export and Share download page.

2. Extract the zipped files to a folder on your computer. For example, here's how you extract files on Windows 10.

3. Open the browser you want to add the extension to and navigate to the extensions page. This can be done by clicking the Extensions icon and selecting Manage Extensions or typing the following into the address bar-chrome://extensions or edge://extensions.

4. Enable developer mode by switching the appropriate toggle switch. The picture below shows this in Microsoft Edge; Chrome users will find it at the top right of the page.

5. Install the extension by clicking the Load unpacked button and selecting the folder where you extracted the files. ChatGPT Export and Share should now be activated.

The first two steps are identical for Firefox, with the obvious exception that you select the Firefox version. After ChatGPT Export and Share is downloaded and extracted, the following steps will install it in Firefox.

1. Type about:debugging into the Firefox address bar.

2. Click This Firefox and then click Load Temporary Add-on.

3. Select the content_script.js from the extracted installer.

4. You should now have access to the extension on the ChatGPT website.

The unfortunate thing for Firefox users is that this extension will only be active as long as you keep Firefox open. If you close your browser, you must repeat the above steps each time you start Firefox. Not ideal!

Apart from that, this simple tool allows you to export your ChatGPT conversations as a PDF, weblink, or PNG file. Simple to use, with no bells and whistles, but there are easier-to-install tools that do the same function.

Download: ChatGPT Export and Share (Free)

4. ChatGPT Prompt Genius

If you are looking for an extension that does much more than just allow you to export your chats, then ChatGPT Prompt Genius might be right up your street. Among the nifty features that this extension includes is added functionality to the prompting process. There are plenty of extensions that can add useful functionality to ChatGPT.

However, this article will concentrate on its export and share features.

For exporting chats, the extension adds a Share & Export option to the ChatGPT sidebar. This allows you to select how you want to share your conversation. The options are:

The image below shows how these options can be selected when exporting your chat.

We liked the inclusion of Markdown language with this tool, which is very convenient if you are using text for web content. We tested each option, and they all worked perfectly with the link option, creating a unique, easily shared URL.

Overall, this tool was easy to install and worked exactly as intended. If you want to easily share your work and improve your prompting techniques at the same time, ChatGPT Prompt Genius might be the tool for you.

Download: ChatGPT Prompt Genius (Free)

Simplifying Sharing Your ChatGPT Conversations

For something that began almost as a curiosity, AI-generative chatbots have rapidly become an important and powerful tool. As their usage continues to rise exponentially, the need to easily export and share conversations will become increasingly critical.

The tools we covered here could be considered "early adopters" of a trend that can only go upwards. In the future, we can expect more functionality and features to become available as developers rush to take advantage of this burgeoning technology.

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4 Apps and Extensions to Export and Share Your ChatGPT History

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ChatGPT is excellent, but it doesn't make it easy to export or use your conversations elsewhere.

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Rather than pretend ChatGPT doesn't exist, Dr. Francine Berman told students in her Introduction to Public Interest Technology at the University of Massachusetts Amherst this spring that they could use the artificial intelligence (AI) tool to help them write their papers, if they wanted to.

Because Berman regularly assigns work that requires a good deal of personal reflection, ChatGPT wouldn't be able to generate complete papers for students, however, it could help with outlining and draft generation. ChatGPT might also offer editing advice or suggestions if students asked it to read their papers and provide suggestions.

"Those responses may or may not be useful, and they may or may not be better writing than yours, and they may or may not be correct," Berman, Director of Public Interest Technology at UMass, told students. "But you can often select things that strike you as working and then incorporate it back in your own writing, as you would in interacting with a human developmental editor."

However, Berman warned students that using ChatGPT had potential perils. "I made it clear to the students that ChatGPT's privacy policies aren't very good for the individual, and that the writing is often kind of mediocre," she says.

While staff members at OpenAI, which developed ChatGPT, were preparing Educator Considerations for ChatGPT, a web resource, they heard about Berman's approach and reached out to her for input.

Here's some of what Berman learned from using ChatGPT with her students.

Not Every Student Used ChatGPT and It Wasn't Always Helpful

Even though they were permitted to use ChatGPT to help hone their writing, not every student took that opportunity. "Some of them didn't like the privacy policy, or chose for whatever reason not to use it," Berman says.

Also, as anyone who has experimented with ChatGPT has likely found, the advice it offers can lead you astray. "It didn't always improve their writing," she said. "I had them show me samples of the stuff that they came up with and stuff that ChatGPT came up with."

However, there were also times when ChatGPT did help students. For example, it could provide a unified tone to group projects, and was particularly helpful to students who knew the course material well but struggled with writing mechanics.

"It was a game changer for students for whom English was not their first language," Berman says. "A lot of times those students have trouble with really subtle things like tense or verb agreement or plural [words]. ChatGPT helped smooth that out for them."

In the past, Berman might suggest students with these struggles go to the writing center, where a human tutor might provide similar feedback on their work. Used in this manner by students, Berman believes ChatGPT can act as a more responsive, if less personal, writing center tutor, even though she acknowledges that ChatGPT will not be replacing campus writing centers anytime soon.

Chat GPT Can Be A Co-Pilot Not The Pilot

Despite the potential Berman sees for using ChatGPT as a writing helper or AI editor, she believes human writing is vital.

"It's really, really important for all of us to write well. We need to share ideas. Even the well-written email is incredibly powerful," she says. "Students need to write. All of us need to write well."

By allowing students to work with ChatGPT, she hopes to teach them how to use it to improve their writing, not merely write for them. "My big point in helping the students with that is we live in a world where there is increasingly going to be more and more AI resources," she says. "We're in danger if we expect these resources to be the pilot, but I think that it will be more and more possible to have these resources be the co-pilot."

Human writers should still be the ones vetting the information AI generates and making the final decision, however, students need to learn and practice those vetting AI skills. "I wanted them to get some real-world examples of that in class because I think they're going to encounter that more and more," Berman says.

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A Professor Encouraged Students to Use ChatGPT. OpenAI Asked Her What She Learned

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Dr. Francine Berman permitted her students at UMass to use ChatGPT to help them write. Despite limitations, she found there were ways it could help edit student work.

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You would have to be on a deserted island without the Internet to miss the recent buzz around AI.

Artificial intelligence (AI) is a broad term that refers to the ability of machines to mimic human intelligence. AI can be used to perform a variety of tasks, such as recognizing objects, understanding language, and making decisions. Generative AI, however, is a type of AI that can generate content such as text, images, and music, similar to the large amounts of data it has been trained with.

AI can only perform tasks that it has been trained to do. It is important to note that generative AI models can also be used to create fake content, such as fake news and deep fakes. It is essential to be aware of generative AI's potential risks and use it responsibly.

The History of AI in the Classroom

The conversation around AI didn't just begin in 2023. The U.S. Department of Education initiated a project exploring the use of generative AI in 2020, partnering with Digital Promise to collect information and insights. Recently, the outcomes of that work were released by the U.S. Department of Education's Office of Educational Technology through Artificial Intelligence (AI) and the Future of Teaching and Learning: Insights and Recommendations. This report explains AI in education and gives a pros-and-cons summary, and suggests districts develop a policy defining parameters for AI use in education.

There is much to be learned about the uses of generative AI, but there is also a rich history of AI in education.

Artificial intelligence was born in the 1950s and used in various applications. ELIZA was one of the first programs to demonstrate the potential of AI as a natural language processing computer program used to manufacture doctor scripts to respond as a psychotherapist. The first time AI was used in education was in 1965 at Stanford University, with the PLATO computer program, which was developed to teach students basic math and science concepts. PLATO was one of the first computer-based learning systems, and it was a significant breakthrough.

Since then, AI has been used in various educational settings, from K-12 schools to universities. AI-powered tutoring systems can provide personalized instruction to students, and AI can also be used to create adaptive learning platforms that adjust to each student's individual needs.

Writing-to-read programs were often used in schools in the 1980s to help children learn to read. These typically used a combination of games and activities to teach the basics of reading, such as letter recognition, phonics, and sight words. Some popular writing-to-read programs from the 1980s include "Hooked on Phonics," "The Reading Blaster," and "JumpStart Reading." However, that writing-to-read programs need to be more complex and provide children with a more well-rounded education.

Despite the criticisms, writing-to-read programs remain popular, and many are still being sold today.

AI in Education Now

Many software apps and platforms currently being used in K-12 education use AI. Some of these are designed to help students with math, reading, or other subject areas.

Here are just a few examples:

Khan Academy is a nonprofit educational organization that provides free, personalized learning resources for students of all ages. Khan Academy uses its AI to personalize the learning experience for each student.

Knewton relies on AI to create personalized learning experiences for each student. It tracks your progress and recommends lessons based on your strengths and weaknesses.

SuccessMaker uses AI to create personalized learning experiences for each student. It tracks your progress and recommends lessons based on your strengths and weaknesses.

Dreambox applies AI to create adaptive learning programs that adjust to each student's individual needs. The program provides students with practice problems that are just challenging enough to help them learn and grow.

iReady also uses AI to create personalized learning programs by assessing students' skills and providing them with practice problems aligned with their needs. iReady also gives students feedback on their work and helps them track their progress.

Carnegie Learning uses AI to create personalized learning programs aligned with state standards. The program assesses students' skills and then provides them with practice problems aligned with their individual needs, plus gives students feedback on their work and helps them track their progress.

Each of these companies and more use AI to help students learn more effectively and reach their full potential by personalizing learning, making it more engaging, providing feedback, and collecting data to better drive instruction.

Most of these companies have peer-reviewed research validating their use to improve academic performance.

AI in Education Moving Forward

AI has the potential to revolutionize education by providing personalized learning experiences for each student. It can help students learn more effectively and efficiently by providing personalized instruction and adaptive learning.

Generative AI needs parameters, and its use should be included in the digital literacy curriculum. Students need to be able to distinguish between original and borrowed thoughts, and become critical thinkers and writers. AI can help with this development, but it can never replace the person's mind it is helping.

Want to learn more about generative AI? Check out these resources.
To share your feedback and ideas on this article, consider joining our Tech & Learning online community Correction 6/27/23: The original version of this article stated that SuccessMaker was owned by Pearson, which it no longer is. SuccessMaker is fully owned and produced by Savvas Learning Company. Pearson sold its U.S.-based K-12 curriculum business in February 2019.

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AI's Big Deal: AI in the Classroom Continues to Evolve

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The history of AI in the classroom, where it is now, and where it's going

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Despite the buzz surrounding it, the prominence of prompt engineering may be fleeting. A more enduring and adaptable skill will keep enabling us to harness the potential of generative AI? It is called problem formulation - the ability to identify, analyze, and delineate problems.

Prompt engineering has taken the generative AI world by storm. The job, which entails optimizing textual input to effectively communicate with large language models, has been hailed by World Economic Forum as the number one "job of the future" while Open AI CEO Sam Altman characterized it as an "amazingly high-leveraged skill." Social media brims with a new wave of influencers showcasing "magic prompts" and pledging amazing outcomes.

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Despite the buzz surrounding it, the prominence of prompt engineering may be fleeting. A more enduring and adaptable skill will keep enabling us to harness the potential of generative AI? It is called problem formulation - the ability to identify, analyze, and delineate problems.