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100 000+ Ukrainian & Russian Single Women for Dating! Discover true love with J4L, the premier Ukrainian dating site. Join for free to connect with verified Ukrainian singles. Safe, secure, and user-friendly.

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in romana

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No question if they’re too fancy for you to handle. If you always want to go the extra mile to get what you want. Ensure your experience onsite is smooth sailing. https://j4l.com works its magic to get you what you want, if you really want it, you get it. Your special lady could be just a click away. Stellar customer support is at your fingertips. The site typically offers video streaming featuring amazing creatures live. You feel the king, and you’re the king. Send a few free messages and see how it goes. A well-written letter is a grand leap towards great relationships.

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Considering interviews I am concerned about feelings and humanness to a person when sharing their stories rather AI telling them

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It should be used not because it’s fun but also for something you care about!

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Supports in thinking beyond

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[Online Seminar] Advancing Language Education with AI

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[Online Seminar] Advancing Language Education with AI

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This seminar offers insights into leveraging AI technologies in language education to develop student-centred assessments and foster student engagement and personalised learning. Take advantage of this opportunity to stay ahead in the ever-evolving landscape of AI and language education.

Join now: https://www.aiforeducation.net/

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Advancing Language Education with AI (20240419)

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Don’t just chat(GPT): turn on critical interrogation

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Critical thinking is often seen as the antidote to generative AI. But what if educators took it one step further back and aimed to encourage students’ curiosity? Giuseppe Cimadoro explains

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Chat GPT: displacing older approaches to cheating?

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Chat GPT: displacing older approaches to cheating?

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This might not be the right place for this, but its a different lens though which to look at concerns around Chat GPT.

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For the past nine years, Collins, a 27-year-old freelance writer, has been making money by writing assignments for students in the U.S. - over 13,500 kilometers away from Nanyuki in central Kenya, where he lives. He is part of the " contract cheating " industry, known locally as simply "academic writing." Collins writes college essays on topics including psychology, sociology, and economics. Occasionally, he is even granted direct access to college portals, allowing him to submit tests and assignments, participate in group discussions, and talk to professors using students' identities. In 2022, he made between $900 and $1,200 a month from this work.

Lately, however, his earnings have dropped to $500-$800 a month. Collins links this to the meteoric rise of ChatGPT and other generative artificial intelligence tools.

"Last year at a time like this, I was getting, on average, 50 to 70 assignments, including discussions which are shorter, around 150 words each, and don't require much research," Collins told Rest of World. "Right now, on average, I get around 30 to 40-something assignments." He requested to be identified only by his first name to avoid jeopardizing his accounts on platforms where he finds clients.

In January 2023, online learning platform Study surveyed more than 1,000 American students and over 100 educators. More than 89% of the students said they had used ChatGPT for help with a homework assignment. Nearly half admitted to using ChatGPT for an at-home test or quiz, 53% had used it to write an essay, and 22% had used it for outlining one.

Collins now fears that the rise of AI could significantly reduce students' reliance on freelancers like him in the long term, affecting their income. Meanwhile, he depends on ChatGPT to generate the content he used to outsource to other freelance writers.

While 17 states in the U.S. have banned contract cheating, it has not been a problem for freelancers in Kenya, concerned about providing for themselves and their families. Despite being the largest economy in East Africa, Kenya has the region's highest unemployment rate, with 5.7% of the labor force out of work in 2021. Around 25.8% of the population is estimated to live in extreme poverty. This situation makes the country a potent hub for freelance workers. According to the Online Labour Index (OLI), an economic indicator that measures the global online gig economy, Kenya accounts for 1% of the world's online freelance workforce, ranking 15th overall and second only to Egypt in Africa. About 70% of online freelancers in Kenya offer writing and translation services.

John Kamau, who has offered contract cheating services since 2014, disagrees with Collins' assessment. "Work will still be there because even editing the AI-generated text to avoid detection takes a lot of time and effort," he told Rest of World. "So, I don't think it's as simple as saying, with AI, students in the U.S. will just do [the assignments] themselves." Kamau, who doubles as a sales agent with a Nairobi-based construction supplies company, expects more schools will limit and block the use of tools like ChatGPT as AI tech improves. "Academic writers will still have their work. But it will have a positive effect [on] writers who can collaborate with ChatGPT and use it as a guide," he said.

Alfred Ongere, founder of consulting company AI Kenya, told Rest of World thatthe rise of large language models (LLMs) like ChatGPT will disrupt the supply of academic writers in Kenya. "On one hand, writers and other freelancers have realized the powerful capabilities of LLMs such as ChatGPT, and are using them in their work," he said. "This means they can now spend more time being creative, and have better articles because of the time ChatGPT saves them. On the negative side, this will mean [fewer] jobs as their clients and origin of supply shift to ChatGPT and other AI tools to have their work done." So far, higher education institutions in the U.S. have avoided outright bans on the use of ChatGPT. Instead, colleges, including Yale University, have issued guidelines and recommendations for staff on the use of AI, leaving it to teachers to decide how ChatGPT will be used in their classes.

"The most I made in a month last year was $296. In March, I could barely get 10 assignments ... I didn't even hit $74."

Wade Brian, a third-year finance student, provides contract cheating services on the side. He told Rest of World he does not use ChatGPT to write entire essays, as that might cost him his credibility - and future assignments. Instead, he restricts its use to sourcing content, much like Google.

Brian agrees that lately, work has been slow. "When I started last year, as a literal amateur, in the first month, I did 30 assignments," he said. "As I got better, I was doing up to 60 assignments a month. The most I made in a month last year was 40,000 Kenyan shillings [$296]." In March, Brian got barely 10 assignments. "It's not that I haven't been looking [for gigs]. I didn't even hit 10,000 Kenyan shillings [$74]," he said.

The rise of generative AI tools has made the work of educators harder. Christopher Kanan, an associate professor in the department of computer science at the University of Rochester, has started giving in-person, in-class quizzes due to the popularity of ChatGPT.

"It just becomes harder to sort out who knows what and who's getting help from things like ChatGPT," he explained on the university's website, even as he made it clear that AI tools are not going anywhere and would rapidly evolve.

Others, like Ethan Mollick, an associate professor at the University of Pennsylvania's Wharton School, have chosen to take a more open approach to ChatGPT in class. "The truth is, I probably couldn't have stopped them even if I didn't require it," he told NPR.

Meanwhile, the freelancers in Kenya who help American students cheat now compete for a smaller portion of the pie.

"The first quarter of the year used to be part of the high season because students are back in college for their semesters, and they have a lot of assignments," Adrian Nyanga, a freelancer who's been in the industry for four years, told Rest of World.

"But I've seen a dip in the assignments available this year, so there are no longer high and low seasons. It's bad," he said. "Remember, there are so many writers who have joined the industry in the past few years, and it was already getting harder to get gigs, but there are even fewer now, especially with AI."

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AI is taking the jobs of Kenyans who write essays for U.S. college students

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For the past nine years, Collins, a 27-year-old freelance writer, has been making money by writing assignments for students in the U.S. - over 13,500 kilometers away from Nanyuki in central Kenya, where he lives. He is part of the " contract cheating " industry, known locally as simply "academic writing."

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Shaban Ahmed

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Many students struggle with getting started, so it helps to offer some useful starting sentences and statements. However, the small print will always be that it needs to be checked carefully.

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How can #AI help you give better feedback for learning & save you time

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How can #AI help you give better feedback for learning & save you time

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ChatGTP, MS Co-pilot and other tools pride themselves in their ability to summarise information. Use it for Feedback and Co-creation!

AI tools can be very helpful when it comes to giving feedback for learning to large cohorts and when it comes to co-creating lecture content with students.

To co- create, instruct students to read around the subject, research it or discuss a problem based learning task and then ask them using polling software what area of the subject they want addressing in your lecture. You can then have the AI tool summarise the responses in an instant and then structure your lecture around this summary- making it move relevant to the majority of students. In the same way you can invite students even in large cohorts to post questions about a lecture you have already delivered and then have their questions summarised and give summary feedback for learning that addresses the issues of mist students even in large cohorts. Have a play with it and try it out! It does also do some basic lesson plans :)

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How can #AI help you give better feedback for learning & save you time

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ChatGTP, MS Co-pilot and other tools pride themselves in their ability to summarise information. Use it for Feedback and Co-creation! AI tools can be very helpful when it comes to giving feedback for learning to large cohorts and when it comes to co-creating lecture content with students.

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We may get repeated tropes (which may not be applicable to the particular question set, or even not true) with little real analysis. A lot of IELTS-style 'manufactured' writing.

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It would be good to share any guidance for students.  Any examples out there?

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Content Generation with ChatGPT & Midjourney

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Content Generation with ChatGPT & Midjourney

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An introductory but practical online talk for the hottest topic. Register freely at: https://aiforeducation.net

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Content Generation with ChatGPT & MidJourney

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GPT-4 Learning Assistant in the Khan Academy

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GPT-4 Learning Assistant in the Khan Academy

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This is a demo of the new GPT-4 learning assistant in the Khan academy which is a companion on the student learning jourmey, offering dialogue and tutoring when the student asks questions. There are also tools for educators for rapid creation of learning content. This is the first example of using generative AI in teaching and learning which shows promise. It could also be used in blended learning scenarios as well as online only. Unfortunately uou can only try it out if you are in the US.

See my post on LinkedIn

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ChatGPT is a revolution in education.

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Second, some tertiary providers have explored banning ChatGPT, and other AI tools, with the support of AI detection tools. These AI detection tools are not 100 per cent accurate and can be worked around. My concern is that students will spend more time attempting to circumvent the system than learning the content.

Alex Sims is an associate professor in the University of Auckland's department of commercial law and an associate at the UCL Centre for Blockchain Technologies.
If you found this interesting and want advice and insight from academics and university staff delivered direct to your inbox each week, sign up for the THE Campus newsletter.

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ChatGPT and the future of university assessment

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Second, some tertiary providers have explored banning ChatGPT, and other AI tools, with the support of AI detection tools. These AI detection tools are not 100 per cent accurate and can be worked around. My concern is that students will spend more time attempting to circumvent the system than learning the content.

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Perplexity is a free AI-powered answer engine that provides accurate, trusted, and real-time answers to any question.

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I have always jumped at any opportunity for technology to help me. As soon as text to speech became more usable it was implemented into how I read and digest journals. Likewise with ChatGPT I have tried taking a few hard to read paragraphs from journals and had them altered into something more digestible to understand.

While I don't think it should replace areas within academia, it definitely can be adapted and utalised when fully understood.

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using Ai as a bootstrap for the coding within Network Automation, this has improved the ideas and concepts I can cover with the students

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using Ai as a bootstrap for the coding within Network Automation, this has improved the ideas and concepts I can cover with the students

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Embrace it and link it with the development of students digital capabilities.

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Embrace it and link it with the development of students digital capabilities.

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This semester i have encouraged students to use it and then write a reflective blog about their experiences. The one rule to emerge so far is that students must always acknowledge the use of Chatgpt and include it as a reference.

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I have one student who struggles to start writing - he will just continue to read instead.  He is therefore using ChatGPT to help initiative the writing process.  I think it must help improve his confidence when it comes to writing.

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I have one student who struggles to start writing - he will just continue to read instead.  He is therefore using ChatGPT to help initiative the writing process.  I think it must help improve his confidence when it comes to writing.

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04 April at 14:00 (UTC+8) marks the 3rd workshop delivered by Dr. Leon Lei from The University of Hong Kong as part of the AI in Education project.

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Analysis of the Connection of United Nations Sustainable Development Goals with the Educational Resources

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I find it difficult sometimes to write emails to people that I haven't met before or for situations that are abstract for me. ChatGPT has now helped a couple of times by combining my notes of the scenario into a logical email. I usually rewrite this quite a bit, but it gives me the options/generic phrases that are used in these situations. It's almost like a modelling tool for me.

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The assumption seems to be that students can access AI tools as and when they want, or need to. But, even in countries that do have ready access, unless a user has a paid subscription, access isn't guaranteed. What should educational institutions or tutors do to ensure that some students are not disadvantaged by limited or an inability to access an appropriate AI tool when they need to?

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Role of Academia to assist with using AI for Good and protect against National and Institutional International Security risks

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Role of Academia to assist with using AI for Good and protect against National and Institutional International Security risks

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In the absence of a Global AI Governance, 69 countries have some 800+ National AI policies & strategies according to OECD AI Policy Observatory (https://oecd.ai/en/dashboards/overview)

Given the above context, How can Academia assist with using AI for Good and protect against National and Institutional International Security risks?

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OECD's live repository of AI strategies & policies - OECD.AI

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APT23: Implications and Ethical Dimensions of using Artificial Intelligence in Higher Education Teaching, Learning and Assessment

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APT23: Implications and Ethical Dimensions of using Artificial Intelligence in Higher Education Teaching, Learning and Assessment

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CALL FOR PAPERS open until 5 May 2023 https://reflect.ucl.ac.uk/aptconference/

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Advance HE session Tuesday 14 March - Navigating the opportunities and threats of AI tools in eduation

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Advance HE session Tuesday 14 March - Navigating the opportunities and threats of AI tools in eduation

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https://advance-he.zoom.us/rec/share/xHUNuW4GJH5iSPhBcap6Hp1su9sOL4TEvviNV04GdN6pNAFuWao-GsqORwqbsb2C.rVyoH-teHPUHpzRX

Passcode: 5$#SU&Q+

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Our libguide of AI resources, including for teachers, parents, ethics & integrity, SDG's and tools accessible without ChatGPT. https://learn.wab.edu/innovation/ai/teachers

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It shows students what they need to do in an essay - both in terms of basic structure, and what it misses - the critical, human aspect.

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It shows students what they need to do in an essay - both in terms of basic structure, and what it misses - the critical, human aspect.

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ChatGPT for students with Dyslexia? Expert Opinion: Examining the use of ChatGPT as an Assistive Technology Tool for Students with Learning Disabilities

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Experts in the field of Learning Disabilities (dyslexia, dyscalculia, dyspraxia and dysgraphia) share their opinions on the use of ChatGPT as an assistive technology tool for students with learning disabilities.

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Artificial Intelligence and the Modern University – lessons from history.

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Introduction In a matter of 100 years, from the late 18th to the late 19th Century, the industrial revolution heralded a dramatic transformation of society, especially the organisation of labour. Though the effects of the industrial revolution continue, many observers suggest today we are going thro

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Demo the limitations of ChatGPT in searching for citations and including references in answers.
Look at usefulness to creat search strings - test them out compared to ur own constructed searches

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Supercharge your students’ learning outside the classroom.

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Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it... learn for themselves. [ https://expertsystem.com/machine-learning-definition/

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To continue Professor Philippe De Wilde's opinion on how academic work has been gradually tending towards mediocrity, and how ChatGPT is now regurgitating the same body of text, thus perpetuating said mediocrity, it follows that, as computers and AI are becoming smarter, so do we, humans become ever dumber in turn. The good news for us, currently living and thinking members of the species, is that at least we can say with pride: we represent the pinnacle of human intelligence - it's been a long climb, and it's all downhill from here! :D

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UCLA professor on 'How ChatGPT Can Improve Education, Not Threaten it'

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UCLA professor on 'How ChatGPT Can Improve Education, Not Threaten it'

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"The time when a person had to be a good writer to produce good writing ended in late 2022, and we need to adapt."

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To read the news, the sanctity of everything from college application essays to graduate school tests to medical licensing exams is imperiled by easy access to advanced artificial intelligence like ChatGPT, the AI chatbot that can produce remarkably clear, long-form answers to complex questions. Educators in particular worry about students turning to ChatGPT to help them complete assignments. One proposed solution is to roll back the clock to the 20th century, making students write exam essays using pen and paper, without the use of any Internet-connected electronic devices. The University of California, Los Angeles, where I teach, is considering making it an honor code violation to use ChatGPT for taking an exam or writing a paper.

That's the wrong approach. This semester, I am telling the students in my class at the UCLA School of Law that they are free to use ChatGPT in their writing assignments. The time when a person had to be a good writer to produce good writing ended in late 2022, and we need to adapt. Rather than banning students from using labor-saving and time-saving AI writing tools, we should teach students to use them ethically and productively.

To remain competitive throughout their careers, students need to learn how to prompt an AI writing tool to elicit worthwhile output and know how to evaluate its quality, accuracy and originality. They need to learn to compose well-organized, coherent essays involving a mix of AI-generated text and traditional writing. As professionals working into the 2060s and beyond, they will need to learn how to engage productively with AI systems, using them to both complement and enhance human creativity with the extraordinary power promised by mid-21st-century AI.

In addition to the sound pedagogical reasons for treating ChatGPT as an opportunity and not a threat, there are practical ones as well. It simply isn't feasible to effectively ban access to this technology. Honor code or not, many students will be unable to resist the temptation to seek AI assistance with their writing. And how would an educational institution enforce a ChatGPT ban? While there are tools aimed at detecting text produced by AI, future versions of AI will get better at emulating human writing-including to the point of emulating the style of the particular person who is using it. In the resulting arms race, the AI writing tools will always be one step ahead of the tools to detect AI text.

Enforcement of a ChatGPT ban would also inevitably produce the injustice of false positives and false negatives. Some students who use ChatGPT despite a ban would, through luck or thanks to careful-enough editing of AI-generated text, avoid having their writing flagged as AI-assisted. Worse, some students would be falsely accused of using ChatGPT, triggering enormous stress and potentially leading to punishment for a wrong they did not commit.

And what of the argument that learning to write well provides benefits that go well beyond writing? Writing a good essay from scratch requires careful, often painstaking, thought about organization, flow and communication. Learning to write without AI does indeed promote focused, disciplined thinking. But learning to successfully combine unassisted and AI-assisted writing to create truly good essays also requires these qualities.

Writing is a craft worthy of enormous respect, one which few of us ever master. But most students don't aspire to become professional writers. Instead, they are preparing for careers where they will write to further goals beyond the production of writing. As we do today, they will write to communicate, explain, convince, memorialize, request and persuade. AI writing tools, when properly used, will help them do those things better.

When I was a middle and high school student in the late 1970s and early 1980s, I was told that professional success required good "penmanship" and the ability to perform long division by hand. By the time I entered the professional workforce in the late 1980s, technology advances had rendered those skills obsolete. Education culture can be very slow to change, as evidenced by the fact that many schools today still force children to learn long division-a task they will never have to perform anywhere outside of school. With AI writing, educators should stay ahead of the technology curve, as opposed to lagging decades behind it.

The upshot: I am helping my students to prepare for a future in which AI is simply another technology tool as opposed to a novelty. I am also telling them that they are solely and fully responsible for the writing they turn in bearing their name. If it's factually inaccurate, that's on them. If it's badly organized, that's on them. If it's stylistically or logically inconsistent, that's on them. If it's partially plagiarized, that means that they have committed plagiarism.

In short, I'm encouraging my students to become responsible, aware users of the AI technologies that will play a profoundly important role over the course of their careers. The AI writing, so to speak, is on the wall.

This is an opinion and analysis article, and the views expressed by the author or authors are not necessarily those of Scientific American.

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How ChatGPT Can Improve Education, Not Threaten It

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A professor explains why he is allowing students to incorporate ChatGPT into their writing process instead of banning the new technology

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Turnitin launches AI detection to help educators identify when AI writing tools such as ChatGPT have been used in students' submissions.

Academic integrity in the age of AI writing

Over the years, academic integrity has been both supported and tested by technology. Today, educators are facing a new frontier with AI writing and ChatGPT.

Here at Turnitin, we believe that AI can be a positive force that, when used responsibly, has the potential to support and enhance the learning process. We also believe that equitable access to AI tools is vital, which is why we're working with students and educators to develop technology that can support and enhance the learning process. However, it is important to acknowledge new challenges alongside the opportunities.
We recognize that for educators, there is a pressing and immediate need to know when and where AI and AI writing tools have been used by students. This is why we are now offering AI detection capabilities for educators in our products. Learn More About Our AI Detector

AI writing indicator keeps educators informed

Gain insights on how much of a student's submission is authentic, human writing versus AI-generated from ChatGPT or other tools.

AI writing reporting with powerful results

Robust reporting identifies AI-written text and provides information educators need to determine their next course of action. We've designed our solution with educators, for educators.

Check student essays as you do today

AI writing detection complements Turnitin's similarity checking workflow and is integrated with your LMS, providing a seamless, familiar experience.

Turnitin's AI writing detection capability available with Originality, helps educators identify AI-generated content in student work while safeguarding the interests of students.

Learn more about Originality

Turnitin AI Innovation Lab

Welcome to the Turnitin AI Innovation Lab, a hub for new and upcoming product developments in the area of AI writing. You can follow our progress on detection initiatives for AI writing, ChatGPT, and AI-paraphrasing.

Understanding the false positive rate for sentences of our AI writing detection capability

We'd like to share more insight on our sentence level false positive rate and tips on how to use our AI writing detection metrics.

Read more

Understanding false positives within our AI writing detection capabilities

We'd like to share some insight on how our AI detection model deals with false positives and what constitutes a false positive.

Read more

Trouble viewing? View the video on YouTube or adjust your cookie preferences.

Helping solve the AI writing puzzle one piece at a time

AI-generated writing has transformed every aspect of our lives, including the classroom. However, identifying AI writing in students' submissions is just one piece in the broader, complex, ever-evolving AI writing puzzle.

Read more

Teaching in the age of AI writing

As AI text generators like ChatGPT quickly evolve, our educator resources will, too. Curated and created by our team of veteran educators, our resources help educators meet these new challenges. They are built for professional learning and outline steps educators can take immediately to guide students in maintaining academic integrity when faced with AI writing tools.

The Turnitin Educator Network is a space to meet, discuss and share best practices on academic integrity in the age of AI.

Join the conversation here

Learn more about AI writing in our blog

Written by experts in the field, educators, and Turnitin professionals, our blog offers resources and thought leadership in support of students, instructors, and administrators. Dive into articles on a variety of important topics, including academic integrity, assessment, and instruction in a world with artificial intelligence.

Stay up to date with the latest blog posts delivered directly to your inbox.

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Turnitin AI tools in the news

Never miss an update or announcement. Visit our media center for recent news coverage and press releases.

Cheat GPT? Turnitin CEO Chris Caren weighs in on combating A.I. plagiarism | CNBC Squawk Box

Since the inception of AI-generated writing, educators and institutions are learning how to navigate it in the classroom. Turnitin's CEO Chris Caren joins 'Squawk Box' to discuss how it is being used in the classroom and how educators can identify AI writing in student submissions.

Trouble viewing? View the video on YouTube or adjust your cookie preferences.

Schools Ban ChatGPT amid Fears of Artificial-Intelligence-Assisted Cheating

U.S. educators are debating the merits and risks of a new, free artificial intelligence tool called ChatGPT, which students are using to write passable high school essays. So far, there isn't a reliable way to catch cheating. Matt Dibble has the story.

Trouble viewing? View the video on YouTube or adjust your cookie preferences.

Some U.S. schools banning AI technology while others embrace it | NBC Nightly News

ChatGPT, an artificial intelligence program, can write college-level essays in seconds. While some school districts are banning it due to cheating concerns, NBC News' Jacob Ward has details on why some teachers are embracing the technology.

Trouble viewing? View the video on YouTube or adjust your cookie preferences.

Testing Turnitin's New AI Detector: How Accurate Is It?

BestColleges

Artificial intelligence, it seems, is taking over the world. At least that's what alarmists would have you believe. The line between fact and fiction continues to blur, and recognizing what is real versus what some bot concocted grows increasingly difficult with each passing week.
Read more

The Sky Is Not Falling: Turnitin Urges Educators to 'Meet the Moment' of ChatGPT

THE Journal

In this episode of THE Journal Insider podcast, host and THEJournal.com editor Kristal Kuykendall welcomes two former teachers who have been working on AI writing tools at Turnitin, a plagiarism-detection software used by thousands of K-12 schools and institutions of higher education.
Read and listen

How ChatGPT will reshape the future of the high school essay

Fast Company

ChatGPT, an AI-powered "large language" model, is poised to change the way high school English teachers do their jobs. With the ability to understand and respond to natural language, ChatGPT is a valuable tool for educators looking to provide personalized instruction and feedback to their students.
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Meet us in person to discuss AI writing detection

We are attending larger and smaller events to ensure we'll have the opportunity to discuss academic integrity in the age of AI writing with you in person. Here's a list of events that Turnitin has already participated in, or will be participating in this year. Looking forward to seeing you there!

MBO Digitaal Conferentie, September 21-22, Ulft, Netherlands
World Academic Summit, 26-28 September 2023, Sydney, Australia
Campus Innovation, September 27-29, Hamburg, Germany
tawiab 2023: Tagung wissenschaftliche Abschlussarbeiten und Hochschulschriften-Repositorien, September 28, Vienna, Austria
ACO-TEC 2023, September 28-29, Vienna, Austria
Digital Universities: MENA, 9-11 October, Riyadh, Saudi Arabia
EDUCAUSE Annual Conference, 9-12 October 2023, Chicago, USA

EDUtech Europe, October 10-12, Amsterdam, Netherlands
Digital Universities: Europe, 23-25 October 2023, Barcelona, Spain
THE Campus Live US, 8-9 November 2023, Los Angeles, USA
SURF Onderwijsdagen, November 14-15, Den Bosch, Netherlands
NCTE, 16-19 November 2023, Columbus, OH, USA
THE Campus Live UK, 6-7 December 2023, UK
Online Educa Berlin 2023 (OEB), November 22-24, Berlin, Germany

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Turnitin AI Innovation Lab | New AI tools from Turnitin

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Turnitin is your resource for the latest AI tools to help teachers and students fairly and effectively utilize artificial intelligence in education.

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Educate them on how to use it. How it works. What it is good at. What it is currently bad at.

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Educate them on how to use it. How it works. What it is good at. What it is currently bad at.

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Computational bias is embedded in it & causal reasoning is not.

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Computational bias is embedded in it & causal reasoning is not.

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It's good to help map out initial ideas and then go on to refine them

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It's good to help map out initial ideas and then go on to refine them

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It's good for getting an idea about what concepts people associate together.

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It's good for getting an idea about what concepts people associate together.

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Using ChatGPT to create graded reading exercises.

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My experiment with using ChatGPT to create graded reading texts with comprehension questions.

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My experiment with using ChatGPT to create graded reading texts with comprehension questions.

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AI text generators and teaching writing - WAC Clearinghouse, curated by Anna Mills

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AI text generators and teaching writing - WAC Clearinghouse, curated by Anna Mills

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What do teachers who assign writing need to know about AI text generators? How should we change our pedagogical practices, given the recent advances in AI Large Language Models (LLMs) such as OpenAI's ChatGPT? How should teachers participate in shaping policies around these technologies in our departments, institutions, and society?
As teachers who assign writing, we need to reckon with the possibility that our students may use writing generators to produce essays or parts of essays. These tools do not produce writing copied from human sources; the AI origin appears to be not reliably detectable either by human readers or by software.
To shape our individual and institutional responses to this new technology, writing teachers and scholars need more information about the kinds and quality of AI-generated text we can expect in response to common types of essay prompts. For example, we may want to design prompts that AI text generators are unskilled at performing, or we may want to find ways to use these generators pedagogically. Either way, as faculty responsible for teaching writing as impactful, ethical intellectual activity, we need to know what AI generators are capable of. And we need to understand the forms of bias and error that emerge in AI-generated writing.

Shared Resources

Opportunities to Engage and Participate

The resources collected here serve as catalysts for inquiry, discussion and collaborative research as we respond to this major change in the kind of writing assistance available to our students.

Suggested Citation

Mills, Anna (Curator). AI Text Generators and Teaching Writing: Starting Points For Inquiry. 2022. Last Updated February 14, 2023.

Authorship and Credits

Anna Mills ( armills@marin.edu) teaches English at College of Marin and previously taught at City College of San Francisco for 17 years. She is the author of an Open Educational Resource (OER) textbook, How Arguments Work: A Guide to Writing and Analyzing Texts in College, which has been praised on OER review sites and used at over 45 colleges. She is the recipient of an Open Education Research Fellowship and currently serves as the English Discipline Lead for the Academic Senate of the California Community Colleges OER Initiative. Anna earned a master's degree from Bennington College in Writing and Literature with a focus on nonfiction writing. Her essays have appeared in journals such as The Writer's Chronicle, The Sun, and Salmagundi. Recently, she has focused on exploring how writing instructors can respond to the accessibility of large language models. Follow her at @EnglishOER.

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AI Text Generators and Teaching Writing: Starting Points for Inquiry

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What do teachers who assign writing need to know about AI text generators? How should we change our pedagogical practices, given the recent advances in AI Large Language Models (LLMs) such as OpenAI's ChatGPT? How should teachers participate in shaping policies around these technologies in our departments, institutions, and society?

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In my tests, ChatGPT has been very good at spotting and correcting English language errors. It can also explain the corrections (though not always well). This could be very helpful for scholars and students who use English as an Additional Language (inclusivity benefit).

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I've read of people using it to
- learn how to code
- create foreign language practice activities, e.g. reading comprehension questions or gapfill exercises
- create practice interview questions, e.g. for a viva

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Quick guide for staff (Edinburgh Napier University)

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Quick guide for staff (Edinburgh Napier University)

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Concerns over GDPR relating to the location of ChatGDPR servers (outside of the European Union), implications of sending student work for it to mark, is the student's work then absorbed into the data that ChatGPT uses, and can it be plagiarised? What are the implication of IP for people who submit content for review/assessment etc? Many concerns.

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First of a series of briefings from the expert AI and education group with all the latest information and guidance in this fast-moving area. Published February 2023.

In November 2022 an artificial intelligence (AI) tool, ChatGPT, was released which caused widespread interest and concern across the education sector because of its ability to create plausible answers to assignments, construct essays, and write computer code, all in seconds. Since its launch, many institutions have reported that students have attempted to pass off AI-generated work as their own, and some are banning it. It is likely that some UCL students will use this and similar tools, and it is essential that all teaching staff are alert to this, and aware of what actions to take.

UCL has considerable internal expertise, and has convened a group of colleagues who are shaping our response to this challenge, and ensuring we are well-placed take advantage of the many opportunities posed by this fast evolving technology. This Briefing has been compiled by this group and outlines some immediate advice and actions for teaching staff, together with an explanation of the technologies, their strengths and limitations.

In each briefing we will report on the work of the core expert group and include progress reports on series of workstreams. We will also invite colleagues to join a work stream if they have a particular interest in its work.

We can't cover everything in this first briefing, so we thought it would be helpful to offer some practical tips based on the best available guidance to date. Note, discussion on these AI tools is evolving fast. So, we will ensure we update you further in each briefing.

Contact your Faculty Learning Technology Lead or your Arena Faculty contact if you would like further advice.

UCL's position

Whilst AI technologies such as ChatGPT are disruptive, especially for assessment,a blanket prohibition on their use or engaging in an arms race to try to outwit or detect them is not a productive strategy. Their use is already widespread in some workplaces and students and staff will need to be supported to use them ethically and transparently.

Our current advice to teaching staff is to be clear with students what you regard as a permissible use of AI in your particular assignment, and how they should acknowledge that use.

Background

In December 2022, we sent out an initial statement on the use of AI tools in education and assessment [UCL login required]. This was in response to growing interest in one highly publicised tool: ChatGPT. Since then, we have established an expert group of UCL colleagues, co-chaired by Prof Kathleen Armour (Vice Provost Education and Student Experience) and Prof Steve Hailes (Head of Computer Science) to steer us through some of the complexities of this issue.

The expert group met in January. AI technology - as exemplified by ChatGPT - is evolving fast, so we thought it would be helpful to distribute regular briefing papers for staff who teach and assess students. The education sector worldwide is grappling with the best ways to mitigate its challenges and take advantage of its opportunities so in addition to drawing on our UCL expertise, we are also keeping abreast of (and contributing to) wider sector developments.

The expert group is:

Developing guidance for students, to be released in the next couple of weeks.

Working on ethical and regulatory responses.

Developing resources, running workshops and planning support for staff who would like help with designing teaching and assessment activities in the light of AI.

Looking to the future and seeking to lead the sector in its response to these exciting technologies.

Sector response

Predictably, the development of these tools has led to speculation about 'the death of the essay', and concerns about the integrity of open book exams and take-home papers. Some have even claimed these tools present an existential challenge to HE as we know it. As has been widely noted, plagiarism detection tools are lagging behind, making their use in detection less useful than in the past. Yet, while these tools should not cause us to overreact, there is a need to interrogate our teaching, assessment and feedback practices in light of these developments. Staff will need generic information and also subject-specific guidance; indeed, some subject associations are now considering both the challenges and the future opportunities.

What are we talking about here?

Large language models and ChatGPT

Following the recent publicity around ChatGPT and similar tools, technical developments in AI have started to overlap the world of education. ChatGPT is an example of an emerging technology called a 'large language model', and it is useful to understand a little more about them, as it shines light on their current limitations.

To be specific, ChatGPT is a user-friendly, chat-bot style Web tool based on GPT-3, a proprietary large language model built by the firm OpenAI. GPT stands for 'generative pre-trained transformer', referring to its creation of output, the way it is trained before used and does not dynamically learn (although its deployment may collect data for future rounds of training), and the type of machine learning model used - transformers have seen success in natural language processing.

ChatGPT predicts the next character in a sequence. Give it some text, and it will give you some more. GPT-3 has been trained on text from the Web, from books and from Wikipedia, costing an estimate $4.6m (and 500 metric tonnes of CO2) to train its 175 billion parameters, in addition to large total sums on small army of outsourced contractors who check prompts is to steer the model away from reproducing illegal or harmful content.

We can expect language models both from OpenAI and other firms and research groups to be rapidly integrated into many other tools and technologies. OpenAI has been using GPT-3 as a basis for other systems, including the image generation ('AI art') system DALLE-2 and the code-generation tool GitHub CoPilot, and OpenAI's synthetic content detection tool, 'AI Text Classifier'. The company also offers GPT-3 as a paid service for other companies to make their own software using, which has led to writing assistants (e.g. copy.ai) and other tools. They have agreed a multi-billion dollar partnership with Microsoft, who suggest they will make OpenAI's large language models available in MS Word. Many other firms and research groups have similar technologies to GPT-3 (e.g. Google's LAMBDA/Sparrow/GLaM, BigScience's BLOOM). These are currently unreleased or less publicised, but heavy competition means that tomorrow, the conversation could move quickly from ChatGPT to another tool entirely.

Functionality and limitations

Large language models attempt to capture and regurgitate the general patterns in text without producing the exact same text they were trained upon. This means its results are plausible, but lack understanding. Large language models frequently generates things that copy the form of text they have been trained on, so may be grammatically or syntactically correct, but as they do not capture meaning or 'understand', are often confidently wrong. Despite what it might appear, these models are not (yet) searching the Internet in real-time, but are drawing on statistical patterns captured at the moment of training. They will not know the weather today, or the current Prime Minister, as they are restricted to patterns they capture at the point of training. As language models reproduce patterns in text, they also have tendencies to reproduce unwanted biases, toxic speech, or specific worldviews.

This does not mean the technology is useless. Commentators have noted that this 'fake intelligence' can be practically useful in many domains. It can highlight grammatical errors, expand or summarise prose, or even help with ideation and writer's block. Yet navigating the difference between utility and meaning can be hazardous. Bender et al. note that 'the human tendency to attribute meaning to text, in combination with large [language models'] ability to learn patterns of forms that humans associate with various biases and other harmful attitudes, leads to risks of real-world harm'.

With the release of ChatGPT, this type of technology reached a turning point: no longer will we live in a world without a chatbot at least this convincing - and it already has functionality enough to be useful. GPT-3 is the third version of GPT, originally released in 2020 with 175 billion parameters; GPT-2 came out in 2019 with 1.5 billion parameters. The difference between these two is the difference between something useable and something largely of academic interest. We already know that ChatGPT hit 1 million users within just a week, and language models' fast integration in other tools may see the numbers of users interacting with them in some form soaring. If those users add value to the process of evaluating the quality of the outputs, then we could see those outputs improve significantly over time.

ChatGPT rarely fails to produce text that looks like it could have been generated by a human - it is plausible in that sense. However, because GPT-3 does not really have a deep understanding of the entities about which it is generating text, the output may be inaccurate or meaningless in human terms, or may reflect the biases inherent in the subject material on which it was trained, a common problem with this type of AI. Human input helps correct some of the more egregious of these failings, but the GPT-3 heritage of ChatGPT can still become obvious if it is pushed.

The final limitation of ChatGPT again derives from GPT-3, most specifically the P (pre-trained) part of it. In short, GPT-3 was trained at a fixed point in time. Because it is only periodically re-trained (GPT-4 is rumoured to be on the way), the model is invariably out of date to a greater or lesser extent. It has no mechanism to search the web for current information, for example. Since GPT-3.5 was released in 2021, it does not embody any data from past that point in time.

We do not yet know where GPT-4 or GPT-5 or .... will put us, nor how others will seek to add value to GPT-x as ChatGPT has added value. If history is anything to go by, advances are likely to be inexorable and the technology will soon be embedded in everyday life, most particularly working life.

Trying out ChatGPT

Perhaps the first thing to try is...asking ChatGPT! Students certainly are.

Assessment Expert, Prof Mike Sharples (Open University) overheard students talking about ChatGPT, so he decided to ask ChatGPT to come up with guidelines for students:

Note these are not UCL's guidelines, but rather an example of ChatGPT.

AI-generated guidelines on best practices [generated by ChatGPT, 28 January]

Understand the limitations of the AI system: generative AI systems are language models, not knowledge bases dot they may not produce accurate or reliable information and should not be used as the sole source for research or assignments.

Use the AI as a supplement: Use the AI system to supplement not replace your own critical thinking and research. Verify the information generated by the AI system with other sources before using it in your work.

Cite your sources: If you use information generated by the AI system in your work, be sure to cite it as a source. Plagiarism is a serious issue and academic integrity is of the utmost important.

Be aware of ethical concerns: Be aware of ethical concerns surrounding the use of AI systems and strive to use some responsibly and in an ethical manner.

Communicate with your instructors: If you are unsure about how to use the AI system or have concerns talk to your instructors. They can provide guidance and advice on how to use the AI system effectively

Continuously evaluate and improve: Continuously evaluate the effectiveness of using AI systems in your education and adapt accordingly. Provide feedback to improve the AI system for future use.

Embrace the opportunity to learn: Use AI systems as an opportunity to learn more about technology, AI and its impact on society and the future.

This is not a bad start. In particular, it reminds us that students are using ChatGPT, so finding ways to ensure they are using it transparently and ethically is the task ahead of us.

Practical steps you can take now

Be clear with your students about permissible use in your context

A legitimate use of AI tools might be to help students summarise and analyse complex materials, extract key findings, break writers' block, all in preparation for a piece of assessed work. One of the UCL group has created this ' sand pit ' with some great examples of their strengths and weaknesses. Whilst we might feel that this is the kind of activity that students should be doing unaided, the reality is that these tools can save a great deal of time and effort, and so are extremely attractive assistive technologies for students - and indeed for educators - alike.

As a teacher, be really clear how far, if at all, they may use AI tools, and that they must clearly acknowledge their use.

If you suspect that a student has used AI unfairly in an assessment

When submitting work in AssessmentUCL or Moodle students accept the following statement:
By submitting this assessment, I confirm that all the work is my own unless collaboration has been specifically authorised. I understand that any form of Academic Misconduct is strictly prohibited, including the use of essay mills, homework help sites, plagiarism, collusion, falsification, impersonation or any other action which might give me an unfair advantage.
If you suspect that a student is trying to pass off AI-generated output as their own work then the regulations in the Academic Manual (9.2.1 g, h and m) apply.

Upcoming exams and assessments 2022/23

Short answer questions

If you are concerned that students might use this technology to create responses to short-answer questions, consider the following:

Check previous, similar exam questions to those you are setting on chatGPT to understand how responses vary. In general, staff should ensure their current questions remain confidential, and it is best not to paste them into online services, particularly as these services typically claim rights to use and publish the information contributed to them.

Ask for any short answer question to take an example from a recent paper or perhaps the specifics of a lab experiment or data set encountered on the course. This means some tweaks to the questions, but not a radical assessment overhaul.

Consider how much an essay or (more likely) short answer question is recall/ fact based. What 'higher order' adjustment (e.g. including data synthesis or analysis) could you make?

Consider how you can add a twist or subtle nuance to a question which would be required to be identified by the student and engaged with to get higher marks. Such nuances are currently more difficult for an AI system to pick up on, as the common signal of the topic of the question can outweigh the subtlety.

Students' writing skills

If you are concerned that students might use this technology to mask weaknesses in written communication, then engage with them in order to educate them about what is/is not acceptable:

When sharing a brief or talking through a written assessment:  be completely open about our awareness of rapid and significant advances and availability of text (and image) generation tools (think about Grammarly, for example).

Discuss with students their perceptions- ask them to compare/ contrast with e.g. calculators, spell checkers, translators, even Google search.

Identify where, at programme/departmental level, your students are being asked to discuss the extent to which using a tool like ChatGPT could be considered dishonest? Where is the line? Is generating a framework cheating? An entire essay? What do they think the quality will be like?

Show them a generated response, point out the blandness of the style and say that they frequently contain factual errors that are a real give-away!

Point out that detection tools already exist, many much more sophisticated ones are in development and, predictably, a web-based sub-culture of ways to 'fool' the detection systems is also growing along with debates about the wisdom of letting AI tools determine human authorship! Whatever way you anyone engages with these tools our counsel would be to be wary and sceptical about claims and potentials.

Mention that it is likely that contract cheating companies/ essay mills would almost certainly be employing these tools themselves so, in many ways, employing such techniques/ shortcuts is even less wise these days and may even be easier to detect through detection tools.

To make it more difficult for students to use AI tools unfairly:

Consider ways you could ask for a response other than prose or short text; e.g. label a diagram, create a flow chart

Use image-based prompts; e.g. ask for a commentary, explanation, speculation, or description with implications.

Build in requirement that responses draw on a specific text, lecture, lab session, experiment, field trip or other source specific to the course

Ask for responses, arguments, challenges, concerns, issues with content from slides or multimedia source

Ask for rationalised opinions

Require specific bibliographic references - large language models are currently unable to accurately cite work, and often create fictionalised, plausible references, although this may change.

Longer term: revisions for 2023/24

It is easy to assume that a return to many more in-person, hand-written and invigilated exams may provide a solution but it's worth remembering that assessment, where this is the dominant or principal type of assessment, may be iniquitous, inauthentic and/ or unscalable/ unsustainable. In-person exams should be considered as just one potential response to the challenges tools like ChatGPT are provoking.

Consider the range of assessments for your module or programme, and discuss in teams whether the current design really measures what you want it to measure, whether there is unnecessary load, and how else you might ascertain understanding/ development/ achievement.

Consider how 'knowledge-based' your assessments are. Where you expect a relatively simple fact recall, what is the justification for this? And rather than being a stand-alone question, could the knowledge recall be embedded into an assessment that also tests students' abilities to compare, use and analyse this knowledge?

Strongly recommend reviewing the wording in modules and, where possible, building in 'ambiguity of format'. So, for example, consider using 'submissions' or 'artefact' for 'written essay'.

Consider variety in assessment format - interactive short oral assessments can be scalable and actually more efficient for both student and assessor. An equivalent to a substantial piece of writing might be conducted in 20 mins (including producing feedback) for example. Think portfolios of short pieces.

Assessment decisions and planning

For 23-24, it is unlikely we will be able to increase the number of seats available at the ExCeL. We have made progress in diversifying our assessment in recent years, and, rather than revert to traditional exams, would like to encourage colleagues to build on this and shift to alternatives to examinations. This might involve creative, reflective, collaborative, data-based, media-rich and generally more authentic and real world challenges. Colleagues in Arena and Digital Education are keen to work with teaching teams on assessment design.

Some types of assessments are more susceptible to the use of these tools, and colleagues may want to consider their assessment designs both in the immediate term (for coursework and examinations this session), and their plans for next session. Note that for the current 2022-23 assessment period it is not possible to change from coursework to exam, or vice versa.

Key dates

Guidance and suggestions on some approaches are outlined below - and there is a short window of time to make changes:

Exam papers

The Central Assessment Team deadline for exam papers is Friday 10 March and departments will have earlier deadlines in place. This means that you have some limited time available to amend your exam questions. Please review your questions and consider whether students might be able to use AI tools to gain an unfair advantage. Guidance below.

Coursework for this session

If you have not yet published coursework assignments for current modules, consider whether students might be able to use AI tools to gain unfair advantage, and consider how you might modify the assignment to improve its integrity. Guidance below.

Assessment planning for 2023/24 - Curriculum Data Task

Departments are currently working on the CDM task confirming assessment patterns for 2023/24 which is due for completion on Tuesday 28 February. It is possible that assessments may require re-thinking in the light of rapid developments in AI. There will be a further opportunity in July to tweak this. We are also looking at redacting the granular assessment information that is publicly displayed in the module catalogue, for example as Coursework/Exam.

Try out ChatGPT for yourself - enter a sample past exam question (please don't use a real one) or writing task and see what it comes up with.

If need be, consider amending your exam questions or written assessment tasks to make them more difficult for an AI tool to answer convincingly (suggestions in the Briefing).

Make clear to your students what is acceptable use of AI in the context of your assignments, and what is not. Tell your students that you are aware of AI tools and that they must not try to pass off work created by such tools as their own as this would constitute academic misconduct. Point them to UCL's guidance on academic integrity and to the Academic Manual (section 9.2.1 g, h and m).

If you suspect that a student has used AI without acknowledging its use, then the Academic Misconduct regulations apply and an investigatory viva would be used to establish authorship.

Be aware of upcoming exam deadlines - exam papers are due on 10 March so you have a limited window in which to refine questions to make them more robust.

Start thinking about assessment redesign for next year - this will be the focus of a subsequent briefing.

Contact your Faculty Learning Technology Lead or your Arena Faculty contact if you would like further advice.

UCL facilities

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AI, education and assessment: staff briefing #1

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First of a series of briefings from the expert AI and education group with all the latest information and guidance in this fast-moving area. Published February 2023. In November 2022 an artificial intelligence (AI) tool, ChatGPT, was released which caused widespread interest and concern across the education sector because of its ability to create plausible answers to assignments, construct essays, and write computer code, all in seconds.

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At every turn, academic integrity has been both supported by and tested by technology. And, for nearly 25 years, Turnitin has been at the forefront of academic integrity and writing technology, evolving with and adapting to the needs of the global education community. As with any commitment to growth and innovation, it is important to acknowledge new challenges and new opportunities.

Today, facing a new frontier with AI writing and ChatGPT, educators and institutions are calling on Turnitin for guidance and support.

Turnitin AI

AI is firmly in our DNA at Turnitin, with AI functionality built into our solutions dating back to 2015. Fundamentally, we believe that AI can be a positive force and that equitable access to AI tools is vital. When used responsibly, AI has the potential to support and enhance the learning process. However, we recognize that for educators, there is a more pressing and immediate need to know when and where AI and AI writing tools have been used by students.

AI writing

Lately, there has been a surge of interest and concern surrounding ChatGPT, the increased sophistication of its capabilities, and the rapid advancement of AI writing tools. While AI writing tools have the potential to expand on original thoughts and ideas, they also have risks similar to contract cheating, when students represent AI-assisted writing as their own. This becomes both a challenge and an opportunity for the education community, one that we have prepared for and are ready to support educators in taking on.

Our AI writing roadmap

While the buzz is recent, for us, the focus on AI writing is not new. For the last two and a half years, we have been researching and developing technology to recognize the signature of AI-assisted writing. Today, some of those technologies are in the trial stage, while others are market-ready.

So, what does that mean with regard to the question on everyone' s mind: "Can Turnitin detect ChatGPT writing?" We have technology that can detect AI-assisted writing and AI writing generated by tools such as ChatGPT today.

Turnitin Originality , an in-market product that investigates the authenticity of student work, can detect some forms of AI-assisted writing and report on indicators of contract cheating. And, other recent product enhancements are detecting AI writing in our research and development labs.

We will incorporate our latest AI writing detection capabilities- including those that recognize ChatGPT writing-into our in-market products for educator use in 2023.

We plan to add enhanced product features beyond detection designed to support pedagogical practices that foster original thinking, and work with customers to enhance technologies that help them evaluate whether a student's work is their own. Like AI, we are advancing quickly, and we will continue to support the education community as they embrace elements of AI-assisted writing while still upholding high standards of academic integrity.

Where do we go from here?

The rise and viral adoption of ChatGPT and other emerging AI writing tools has brought about a number of questions-primarily because we are witnessing the shift in real time. But, it is important to recognize that the presence of AI writing capabilities does not signal the end of original thought or expression if educators set the right parameters and expectations for its use.

The next step is a critical one. Educators, administrators, students, and technology partners have an opportunity and a responsibility to participate openly and honestly in the AI-assisted writing dialogue, to preserve integrity and trust in the education community and beyond. We are actively working with customer advocates and partners to address new and evolving needs, further our collective understanding of current AI writing capabilities, and acknowledge when its use benefits or detracts from student learning.

We encourage you to have these discussions at your institution now and set achievable standards and expectations for your students around the acceptable use of AI-assisted writing tools.

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At every turn, academic integrity has been both supported by and tested by technology; in this post we address AI-writing.

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Firstly - apologies if someone else has already shared this ... the Autumn Caines
Prior to (or instead of) using ChatGPT with your students

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Consider how this integrates and reinforces values of academic intergrity

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Consider how this integrates and reinforces values of academic intergrity

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Challenges our methods of assessment and the way we pose questions for essays, dissertation,

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Challenges our methods of assessment and the way we pose questions for essays, dissertation,

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This may trigger or provide opportunity on how we plan assessments. Could knowledge acquisition be assessed by other means rather than essay,could we build more personal refection portfolios that scaffold learning. Best Sukhtinder

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Independent thinking goes down, false interpretations may occur

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Independent thinking goes down, false interpretations may occur

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It can be helpful for some staff to get over that "blank paper" scenario - get it to outline the basics, then you can tweak for your own module etc., for time strapped, often new, staff, it's a huge challenge to think about starting to plan a module that's new to them. (Of course, better option is find Andy Clegg & get enABLEd :)

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How will ChatGPT transform creative work? The Guardian, 26 Jan 2023, 15min

https://teachinginhighered.com/podcast/teaching-writing-in-an-age-of-ai/ 37min & blog post: https://www.insidehighered.com/blogs/just-visiting/freaking-out-about-chatgpt%E2%80%94part-i

https://teachinginhighered.com/podcast/how-artificial-intelligence-is-impacting-higher-education/ 45min

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Every learner needs to know about these tools - they do give learners a productivity advantage

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Students are so enthusiastic about ChatGPT, let's not disappoint them.

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Students are so enthusiastic about ChatGPT, let's not disappoint them.

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The whole AI world lacks inclusivity: only 10% women, paid less than men, most AI designers are paid >£100k plus stock options, this cuts them off from a large part of society. Lack of political diversity in the AI world.  

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The whole AI world lacks inclusivity: only 10% women, paid less than men, most AI designers are paid >£100k plus stock options, this cuts them off from a large part of society. Lack of political diversity in the AI world.  

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I encourage my students to use it, but also to do an effort to transcend ChatGPT output.

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I encourage my students to use it, but also to do an effort to transcend ChatGPT output.

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Not that supportive of critical thinking.

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Not that supportive of critical thinking.

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Ultimately, its use by students as a tool to bypass proper study, but failing to realise the long-term implications of lack of knowledge gained owing to such use, whereas the tool is really no substitute for actual learning for success in the real world.  

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Ultimately, its use by students as a tool to bypass proper study, but failing to realise the long-term implications of lack of knowledge gained owing to such use, whereas the tool is really no substitute for actual learning for success in the real world.  

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Comprehend a law or business student using the tool to submit an essay, but lacking the depth of study, coming into practice and failing to deliver, either for a client or demonstrate level of knowledge expected. E.g. Lack of good spelling and sentence formation skills leads to dependence on the web tool "Grammarly".

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My assignments are based on personal experiences and reflection.  Asking about the impact of learning and how that might influence future actions will need to be central, with supporting evidence.

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My assignments are based on personal experiences and reflection.  Asking about the impact of learning and how that might influence future actions will need to be central, with supporting evidence.

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It can summarise/paraphrase info and difficult terms - great for accessibility and supporting neurodiversity!

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It can summarise/paraphrase info and difficult terms - great for accessibility and supporting neurodiversity!

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Can either automate or augment.  Augment is a better use of this technology to aid creativity.  However, it should be used in small does as automation is prone to vulnerabilities not least in bias through insufficient training data and errors in detecting subtleties and interpreting natural language, hidden meaning and context.

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It's a calculator that sometimes provides apparently accurate answers.

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It's a calculator that sometimes provides apparently accurate answers.

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Where does the incentive to think for oneself go? It makes it so easy to just reproduce information without having to think about it and coast along through a course. 

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Where does the incentive to think for oneself go? It makes it so easy to just reproduce information without having to think about it and coast along through a course. 

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‘There is no standard’: investigation finds AI algorithms objectify women’s bodies

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Guardian exclusive: AI tools rate photos of women as more sexually suggestive than those of men, especially if nipples, pregnant bellies or exercise is involved

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Do you think GPT or AI may replace teachers some day ?

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Controversial - what about lecturers using ChatGPT to create content? 

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Controversial - what about lecturers using ChatGPT to create content? 

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Focus more on process of learning (and failing) and not just the products of learning.

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Focus more on process of learning (and failing) and not just the products of learning.

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Innovative approach to ML online assessment needed!

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Innovative approach to ML online assessment needed!

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On Modern Languages degrees, we don't expect original thinking in assessment tasks, but accurate and effective use of the target language. I have no doubt that with the current assessment diet chatbots could graduate in Modern Languages in the UK with a 2:1:(

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Think piece for curriculum teams

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On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?

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On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?

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The past 3 years of work in NLP have been characterized by the development and deployment of ever larger language models, especially for English. BERT, its variants, GPT-2/3, and others, most recently Switch-C, have pushed the boundaries of the possible both through architectural innovations and through sheer size. Using these pretrained models and the methodology of fine-tuning them for specific tasks, researchers have extended the state of the art on a wide array of tasks as measured by leaderboards on specific benchmarks for English. In this paper, we take a step back and ask: How big is too big? What are the possible risks associated with this technology and what paths are available for mitigating those risks? We provide recommendations including weighing the environmental and financial costs first, investing resources into curating and carefully documenting datasets rather than ingesting everything on the web, carrying out pre-development exercises evaluating how the planned approach fits into research and development goals and supports stakeholder values, and encouraging research directions beyond ever larger language models.

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On the Dangers of Stochastic Parrots | Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency

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The past 3 years of work in NLP have been characterized by the development and deployment of ever larger language models, especially for English. BERT, its variants, GPT-2/3, and others, most recently Switch-C, have pushed the boundaries of the possible both through architectural innovations and through sheer size.

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Timnit Gebru discusses the misleading framings of artificial intelligence, her experience of getting fired by Google in a very public way, and why we need to avoid getting distracted by all the hype around ChatGPT and AI image tools.

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Timnit Gebru discusses the misleading framings of artificial intelligence, her experience of getting fired by Google in a very public way, and why we need to avoid getting distracted by all the hype around ChatGPT and AI image tools.

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Paris Marx is joined by Timnit Gebru to discuss the misleading framings of artificial intelligence, her experience of getting fired by Google in a very public way, and why we need to avoid getting distracted by all the hype around ChatGPT and AI image tools.

Timnit Gebru is the founder and executive director of the Distributed AI Research Institute and former co-lead of the Ethical AI research team at Google. You can follow her on Twitter at @timnitGebru.

Tech Won't Save Us offers a critical perspective on tech, its worldview, and wider society with the goal of inspiring people to demand better tech and a better world. Follow the podcast (@techwontsaveus) and host Paris Marx (@parismarx) on Twitter, and support the show on Patreon.

The podcast is produced by Eric Wickham and part of the Harbinger Media Network.

Also mentioned in this episode:
Please participate in our listener survey this month to give us a better idea of what you think of the show: https://forms.gle/xayiT7DQJn56p62x7Timnit wrote about the exploited labor behind AI tools and how effective altruism is pushing a harmful idea of AI ethics.Karen Hao broke down the details of the paper that got Timnit fired from Google.Emily Tucker wrote an article called "Artifice and Intelligence."In 2016, ProPublica published an article about technology being used to "predict" future criminals that was biased against black people.In 2015, Google Photos classified black women as "gorillas." In 2018, it still hadn't really been fixed.Artists have been protesting AI-generated images that train themselves on their work and threaten their livelihoods.OpenAI used Kenyan workers paid less than $2 an hour to try to make ChatGPT less toxic.Zachary Loeb described ELIZA in his article about Joseph Weizenbaum's work and legacy.Support the show

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don’t fall for the ai hype w/ timnit gebru

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‎Tech Won't Save Us: Don't Fall for the AI Hype w/ Timnit Gebru on Apple Podcasts

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Paris Marx is joined by Timnit Gebru to discuss the misleading framings of artificial intelligence, her experience of getting fired by Google in a very public way, and why we need to avoid getting distracted by all the hype around ChatGPT and AI image tools. Timnit Gebru is the founder and executiv...

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ChatGPT - Rethinking And Advancing Assessment Methods - March 2023

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Join this webinar for a discussion on the challenges presented by AI and the opportunity to tackle issues such as plagiarism with authentic assessment.

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Whether students who use AI/ChatGPT will bypass learning, shortcutting the time required to think deeply, reflect and write to develop understanding. Or whether AI/ChatGPT can be integrated to support the learning process

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Discuss broader purpose of learning and academic integrity

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Discuss broader purpose of learning and academic integrity

# data[].attributes.body
Develop with students shared understanding of purpose of programme/module, and how ChatGPT/AI can contribute to learning

# data[].attributes.headline
Automated Essay Writing: An AIED Opinion - International Journal of Artificial Intelligence in Education

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Automated Essay Writing: An AIED Opinion - International Journal of Artificial Intelligence in Education

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Essay Writing with Transformer AI Systems

Essays have formed part of academic assessment since the early 19th century, when students in some European universities were required to write scholarly papers for discussion in seminars (Kruse, 2006). Academic essays continue to be a mainstay of assessment in schools, colleges and universities because they are easy to set, assess depth of understanding, and train students in how to express an argument. In recent years, the scope of written assignments has expanded to include narrative, argumentative, reflective, expressive, responsive and analytical papers.

The widespread practice of setting written assignments as coursework has been criticised as laborious and unfair (Race, 2018). It is also subject to contract cheating through "essay mills" that sell written assignments to order, at fees of up to £400 for writing a 20-page essay1. A study by Newton ( 2018) found that 15.7% of students surveyed admitted to paying someone else to write an assignment. Now, an unintended consequence of generative "Transformer" AI systems such as GPT-3 is that they democratise cheating. A student can generate an entire essay in seconds, at a cost of around 50 US cents2. Equally worrying, would-be academic researchers can call on these systems to generate articles for submission to conferences and journals.

How do such Transformer AI systems work? How can we detect whether an academic essay has been written by an AI? Could any good come from widespread use of such technology? What does this mean for the AIED community?

How Does a Transformer AI Work?

Take time to read this brief undergraduate student essay on "A Critique of Learning Styles". If this were your student, how would you assess the written work? What mark would you give? What are its strengths and weaknesses?

The construct of "learning styles" is problematic because it fails to account for the processes through which learning styles are shaped. Some students might develop a particular learning style because they have had particular experiences. Others might develop a particular learning style by trying to accommodate to a learning environment that was not well suited to their learning needs. Ultimately, we need to understand the interactions among learning styles and environmental and personal factors, and how these shape how we learn and the kinds of learning we experience.
Learning Styles and Learning Modes
In the 1970s, learning styles became an important feature of educational practice. In the 1990s, "learning modalities" became a major focus of learning style research. This is the idea that we process information in different ways. For example, some individuals may be auditory learners, benefiting from listening to lectures and using recorded materials. Others may be visual learners, who gain from using visual materials such as textbooks, handouts, and computer graphics. Still others may be kinesthetic learners, who benefit from learning by movement and doing. Numerous experiments have been conducted to test this idea, and a number of different classifications of learning modalities have been proposed.

In a review of this research, Dunn and Dunn (1997) found that the evidence does not support the idea that people have a particular learning mode that is dominant or that they process information in a particular way. In their study, the authors found that when students were given a particular instructional treatment, they could be classified in a particular learning modality category. But when they were given a different instructional treatment, they were classified in a different category. In a follow-up study in which they gave students a number of instructional treatments, Dunn and Dunn found that students could be placed in a particular category in some treatments, but not others.

Dunn and Dunn also found that the results varied by age. Older students generally fit the results of more than one modality, whereas younger students were more likely to fit the results of just one modality. This led them to conclude that style preferences are learned over the course of development. This is consistent with the idea that people are flexible in responding to the way they are taught.
References
Dunn, R., & Dunn, K. (1997). Learning styles: Research and practice. Journal of Research in Education, 7(2), 139-151.

The entire essay was written by GPT-3, a Transformer AI program. It was given the prompt "The construct of 'learning styles' is problematic because" and it generated the rest, including heading and citation. The text shown here is the first attempt. The reference at the end was generated by adding the prompt "References" to the end of the text and resubmitting.

Gaining access to GPT-3 is straightforward. Anyone with internet can sign up to the OpenAI website3, gain an account, click the "Playground" tab, type a prompt such as the title of an essay, set the maximum length of output (up to 4000 language "tokens", or approximately 3000 words) and click the Submit button. A few seconds later, the system produces a typed and formatted text. Some companies are already promoting AI-based essay writing services4.

GPT-3 works like a highly trained text completer of the kind found on mobile phones and email interfaces. Instead of looking back at the last few characters and using these to predict the next word or two, it can attend to the previous 750 words it has written, to continue an entire short story, blog, or student essay. The same program can also summarise a scientific article in simpler language, write a review, translate languages, and answer general questions. In short, a Transformer AI is a general-purpose language machine.

How Can We Detect Whether An Essay is Written by a Transformer AI System?

Plagiarism software will not detect essays written by Transformers, because the text is generated, not copied. A Google search shows that each sentence in the essay above is original. Two plagiarism detectors each indicated over 95% original text5.

What better way to discover whether the essay is written by human or machine than to ask GPT-3? Here is its response when presented with the essay above and the prompt "Was that essay written by a human or a computer?".

It is difficult to say for certain, but it seems more likely that it was written by a computer. The language is very technical and does not seem to flow smoothly. In addition, the ideas are presented in a very concise, bullet-point style, which is often seen in computer-generated texts.

Impressive, yet it gave a similar response when presented with the introduction to a highly-cited research paper written by Sharples (Sharples, 2010), claiming it "does exhibit some characteristics that are often associated with AI-generated text, such as a lack of clear authorial voice and a somewhat stilted, awkward style of writing". Rather than attempt further embarrassing comparisons, we note that any sufficiently powerful program to determine whether a piece is written by human or machine could frequently be outwitted by an equally powerful AI text generator, in a futile computational arms race.

Humans fare no better than machines at detecting AI-generated essays. In a small study by EduRef.net6, college professors were asked to grade essays produced by human writers and by GPT-3, without being informed that any piece was generated by machine. For a Research Methods topic, the machine-written essay was given a grade of C, while the human essays were graded B and D. For US History, machine and human were given similar grades. For a Law essay, GPT-3 was graded B-, while the human essays ranged from A- to F. For one topic, Creative Writing, the machine essay was failed, while human-written essays were graded from A- to D+. The professors gave similar written feedback to the machine productions as to human writers.

A comprehensive study of state-of-the-art methods to determine if a piece of extended text is human-written or machine-generated concludes that "humans detect machine-generated texts at chance level" and that for AI-based detection "overall, the community needs to research and develop better solutions for mission-critical applications" (Uchendu et al., 2021). Students employ AI to write assignments. Teachers use AI to assess and review them (Lu & Cutumisu, 2021; Lagakis & Demetriadis, 2021). Nobody learns, nobody gains.

On the surface, our sample text appears to be a mediocre to good (though very short) student essay. It is correctly spelled, with good sentence construction. It begins with an appropriate claim and presents a coherent argument in support, backed up by evidence of a cited research study. The essay ends with a re-statement of the claim that learning styles are flexible and change with environment.

But look more closely and the paper falls apart. It references "Dunn, R., & Dunn, K. (1997). Learning styles: Research and practice. Journal of Research in Education, 7(2), 139-151." There is a journal named Research in Education, but no issue 7(2) in 1997. Dunn & Dunn did publish research on learning styles, but not in that journal. GPT-3 has fashioned a plausible-looking but fake reference. The program also appears to have invented the research study it cites. We can find no research study by Dunn and Dunn which claims that learning styles are flexible, not fixed.

To understand why a Transformer AI program should write plausible text, yet invent references and research studies, we turn to the seminal paper written by the developers of GPT-3. In a discussion of its limitations, the authors write: "large pretrained language models are not grounded in other domains of experience, such as video or real-world physical interaction, and thus lack a large amount of context about the world" (Brown, et al. 2020, p.34). Transformers are models of language not experiential knowledge. They are not designed to be scholarly - to check academic references and ensure that evidence is grounded in fact. In human terms, they are essentially inexperienced, unthinking and amoral. They have no ability to reflect on what they have written, to judge whether it is accurate and decent.

OpenAI has provided an add-on to GPT-3 that filters bad language. However, it is unlikely that the company will produce tools to check for accuracy. Its focus is on artificial general intelligence not education. Other companies could, in the future, provide tools to check generated references for accuracy or add genuine references to an article. But these would not overcome the fundamental limitation of Transformer language models such as GPT-3: that they have no internal inspectable model of how the world works to provide a basis for the system to reflect on the accuracy and scholarship of its generated work. Research is in progress to develop explainable neural AI (Gunning et al., 2019) and hybrid neural/symbolic AI systems (Garcez & Lamb, 2020) that might address this problem.

Could Any Good Come from Widespread Use of Such Technology?

Transformer AI systems belong to an alternative history of educational technology, where students have appropriated emerging devices - pocket calculators, mobile phones, machine translation software, and now AI essay generators - to make their lives easier. The response from teachers and institutions is a predictable sequence of ignore, resist, then belatedly accommodate.

It will be hard to ignore the growing number of students who submit assignments written by AI. Turnitin, the leading plagiarism checking company, admits that "we're already seeing the beginnings of the oncoming AI wave ... when students can push a button and the computer writes their paper" (Turnitin, 2020). As we have already indicated, resisting AI-generated assignments by deploying software to detect which ones are written by machine is likely to be a futile exercise. How, then, can we accommodate these new tools?

Teachers could restrict essay assignments to invigilated exams, but these are formal and time consuming. Alternatively, they could set reflective and contextualised written assignments that could not be generated by AI. For example, a teacher could set each student an independent research project, then ask for a written report on that specific project, give the student feedback on the report, then ask for the student to write a critical reflection on the feedback and issues raised by the project.

An imaginative way to incorporate AI-generated text into teaching could be for the teacher to employ Transformer AI to generate a set of alternative essays on a topic, then ask students to critique these and write their own better versions. Or set a complex question then ask each student to generate AI responses to the question and for the student to evaluate these responses in relation to the marking criteria. The student would then write an integrative essay drawing on the AI answers to address the original question.7

Transformer AI can be a tool for creative writing. For example, the student writes a first paragraph, the AI continues with the second paragraph, and so on. The AI writing partner helps maintain a flow of words and also takes the story in unexpected directions, to which the student must respond. Generating a few alternative continuations to a story may help a student writer see creative writing not as a linear progression, but an exploration of a space of possibilities.

AI assisted writing exercises could focus on skills of critical reading, accuracy, argumentation and structure. Assignments where AI is not allowed could be assessed for style, expression, voice and personal reflection.

Additionally, teachers could explore with students the ethics and limits of generative AI. How does it feel to interact with an expert wordsmith that has no intrinsic morals and no experience of the world? Is writing with AI tantamount to plagiarism (Fyfe, 2022).

What Does This Mean for the AIED Community?

Reviewers for IJAIED will not be able to avoid the challenge of assessing whether a submitted article has been written with the aid of an AI system. As an exercise, we generated an entire short research paper. First, we chose at random the title of a real paper published in IJAIED: "Domain-Specific Modeling Languages in Computer-Based Learning Environments: a Systematic Approach to Support Science Learning through Computational Modeling" (Hutchins et al., 2020). Then we used GPT-3 to generate three alternative Abstracts, just from the title. We chose a generated abstract for a "review paper". Then, we added to the abstract the heading "Introduction" and requested GPT-3 to generate the paper. We followed with a prompt of "Discussion" and then "References", which GPT-3 added in neat APA format. Finally, we presented GPT-3 with just the newly generated Abstract and requested it to generate a new title for the paper. It responded with: "Using Domain-Specific Modeling Languages to Support Science Learning: A Review of the Literature".

The result is an original 2,200 word "academic paper" produced in under five minutes. The output can be read at https://t.co/RTxogLRlJT. It will probably not pass a first Editor's review but is a harbinger of a flood of papers generated with the aid of AI. IJAIED will not be the only journal to receive papers produced wholly or partly by AI, but we are well placed to lead a debate on how to detect and deal with them.

A related issue is how to respond to genuine papers in the general area of AI Transformer systems in education. Should we publish papers on new tools to automate essay writing, or software to detect AI-generated essays? Where is the dividing line between promoting competition between AI generators and detectors, and enabling new forms of academic writing assisted by generative AI?

This could be a pivotal time for education, as students equip themselves with powerful new AI tools that substitute for what some perceive as the drudgery of assessment. These will not just write essays for students but answer complex questions and generate computer code (Bombazine et al., 2021). An education system that depends on summative written assessment to grade student abilities may have reached its apotheosis.

Every new educational technology arrives with affordances and limitations. AI Transformer technology is a powerful general-purpose language model that is already becoming embedded in education through chatbots, text summarisers, language translators, and now essay generators and tools for creative writing. The AIED community is well placed not only to debate the application of these systems to education, but to design new generative AI tools for writing, reasoning and conversation for learning.

Acknowledgements

I wish to thank Judy Kay for valuable comments on a draft of this article.

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Institute of Educational Technology, The Open University, Milton Keynes, UK

Mike Sharples

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Correspondence to Mike Sharples.

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Sharples, M. Automated Essay Writing: An AIED Opinion. Int J Artif Intell Educ 32, 1119-1126 (2022). https://doi.org/10.1007/s40593-022-00300-7
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Keywords

Transformer AI

Plagiarism

Assessment

Text generation

Generative AI

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Automated Essay Writing: An AIED Opinion - International Journal of Artificial Intelligence in Education

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This opinion piece emerged from research for the book, Story Machines: How Computers Have Become Creative Writers, by Mike Sharples and Rafael Pérez y Pérez, published by Routledge. While thinking of ways to promote the book, I realised that students could employ AI story generators to write essays.

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Support students to critically evaluate digital tools - advantages/disadvantages.

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Could be helpful to students in developing their learning through critical reading and reflection

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Unlocking the Potential of Language Generation Tools in Higher Education: A Progressive Approach to Assessment Reform

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Lisa Gray, Senior Consultant, Learning, Teaching and Assessment. PebblePad The proliferation of AI tools such as ChatGPT in Higher Education has prompted a discussion on their potential implications- particularly on assessment practices. While some may view these tools as a disruption to traditional pedagogical paradigms, it's important to consider them as opportunities for rethinking and advancing assessment methods.

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One of the skills we are often trying to teach is how to evaluate work, chatGPT offers a good opportunity for this (have them look at a chatGPT output and pick out the mistakes).

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QAA briefs members on artificial intelligence threat to academic integrity

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QAA has published a briefing note to support members in tackling challenges to academic integrity which have been brought about by the rise of artificial intelligence (AI) tools.

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As it has been programmed by (bias) humans, then the quality of the "information" or responses is questionable.

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My concern is how to help Educational leaders to support teachers in primary & secondary education (k-12) to embrace using a tool for education rather than fighting to lock it down.  How can we support schools to be more proactive and thereby undermine the nefarious uses.

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My concern is how to help Educational leaders to support teachers in primary & secondary education (k-12) to embrace using a tool for education rather than fighting to lock it down.  How can we support schools to be more proactive and thereby undermine the nefarious uses.

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If you push it it becomes inaccurate, or even misleading

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can it be used for transcription?

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It's a great way to get an introduction, particularly if you ask it for its sources.