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Jeremiah, Spanish 5H, Course 1, student comments

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Jeremiah, Spanish 5H, Course 1, student comments

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-Rubric is biased to use AI, why is the color red used for the AI free category? Seems like that is negative.

-we should not move past yellow and we should not move too quickly with this initiative

-If AI is frowned upon by some teachers, why is AI-free marked as red?

-most kids seem to be in the yellow zone as they feel it helps them be efficient and move more quickly with assignments

-use of AI seems more like a threat than teaching us how to use it ("you will get a zero if you....")

-we aren't using our brains if we go to blue

-work product is better is we are at a #1

-worry that the info provided is not accurate

-if you care about your work, why are you leaving red zone?

-general info is okay, but if you push AI to explain things in more depth sometimes the info is not correct ("if i dig deeper into the information, it is not okay")

-some do not like the word empowered

-some kids do not want to go past brainstorming or asking for summaries

-should be age restricted - with younger kids having least amount of access

-AI is convenient if you know how to use it to your advantage

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A teacher is trying to use the PDF to PODCAST feature of Notebook LM. It worked for him, but when he posted it on Google Classroom, his students could not hear the Podcast.

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Can teachers/students try the free version now?

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Platforms that students are required to STAY LOGGED OUT of...

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Platforms that students are required to STAY LOGGED OUT of...

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Teachers and students are struggling with tools like ChatGPT and Perplexity because students must NOT log in due to data privacy issues. However, Perplexity prompts you to log in -- many students just click it. Also, you can't use the full features of ChatGPT, like "voice mode", without being logged in.

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AI Acceptable Use SCALE Feedback from Students

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AI Acceptable Use SCALE Feedback from Students

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From students in English class: (1) Seems like there is a very thin boundary between between 1, 2 and infinity -- if someone has a long chat with AI, there is not way to document that whole thing (2) The colors are not great -- would like to see more neutral colors (3) I have trouble imagining why a teacher would use "AI Empowered" on an assignment -- they felt like this level was removing the student from the assignment (4) You can't control how students are going to use AI -- students won't follow the boundaries of each level even if teachers try to set them (5) If AI brainstorms for you, then you are not thinking or using your own brain (6) The AI Empowered level has very positive language, but I don't see how it is positive for a learner (7) AI is not a good thing to use in an English class -- should be "O" all the time because it is focused on creativity and individual voice (8) Teachers should ask how students use AI on an assignment and provide feedback about how students are using it (9) The reality: most HS students are operating on a "1"-- if we make this more transparent, it will reduce anxiety in students

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Some of the sources that Perplexity pulls are blocked (like Harvard Review)

Many of the sources Perplexity (SEARCH) pulls are the same as what a simple Google search produces

If you want to use the Perplexity RESEARCH function, you need to be signed in

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How to Use ChatGPT as an Example Machine

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How to Use ChatGPT as an Example Machine

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Sponsored by Listenwise and Wipebook

This post was co-written by Sarah Levine.

Editor's Note: This post takes a pragmatic approach to ChatGPT while acknowledging some of the problems that have already arisen with the tool. Other ethical issues with the tool's development have been brought to light in recent weeks that are not mentioned here. It is our belief that teachers are most effective when they are informed and empowered, so we urge you to stay mindful of these complexities when making decisions for your own practice.

You have probably already heard about or tinkered with ChatGPT (the "GPT" stands for "generative pre-trained transformer"). ChatGPT is a chatbot (or "bot") powered by artificial intelligence (AI). You can have a conversation with it, prompt it to write essays, create recipes, make medical diagnoses, mimic famous authors, and code software. Its outputs are impressively human-like. In just five days, it gained one million users, a milestone that took Facebook ten months to achieve.

ChatGPT comes with risks: Students can now copy and paste a school writing assignment into the bot's dialogue window, and the bot will spit out an essay in a couple of minutes. Also, because ChatGPT gets most of its content and genre knowledge from the web, it can generate sexist, racist, or blatantly false information, all in an authoritative tone. For example:

The prompt entered for ChatGPT:
"Can you put seven blue balls and two red balls into a tube that holds eight balls?"

Text response generated by ChatGPT:
"Yes, it is possible to put seven blue balls and two red balls into a tube that holds eight balls. The total number of balls is nine which is less than or equal to the capacity of the tube."

As literacy researchers and former high school teachers, we recognize these risks. BUT: we don't think we can avoid ChatGPT and its family of AI tools. It is not just a future vision of learning; it is already here. And we are only scratching the surface of what AI will do in the next five to ten years. So this post is about one particular way that teachers can use ChatGPT to support kids' learning: Using ChatGPT as an example machine.

ChatGPT's ability to quickly produce a lot of examples of different kinds of texts makes it uniquely suited to learning strategies like concept attainment, inductive learning, or one that we'll focus on here called contrasting cases.

Why Multiple Examples Are So Important in Learning

The basic idea behind strategies like contrasting cases or concept attainment is that one example is not enough to help people learn about a thing (like an idea or a process). People need to compare multiple, contrasting examples.

Not coincidentally, ChatGPT is built on a similar type of machine learning. For example, for a computer to recognize an image of a dog, it has to process thousands of images of dogs - but also needs to process images of "not dogs," like cats, foxes, and wolves - to accurately construct a general definition and model of dog. In other words, to know what a dog is, you also need to know what it is not.

Across disciplines, teachers use multiple contrasting examples to help students develop mental models of processes and concepts. Social studies teachers provide examples of different types of governments, English teachers provide examples of different literary interpretations, and science teachers give examples to illustrate different types of energy. Students can sequence, rank, or categorize these examples in ways that help them understand underlying concepts.

But developing these examples can take a lot of time. ChatGPT can generate any number of contrasting examples in a few minutes. Then teachers can revise and perfect those examples, and have more time to dedicate to other creative lessons.

How to Get Good Examples from ChatGPT

To use ChatGPT as an example machine, teachers first need to know how to prompt it effectively. ChatGPT will do exactly what it is prompted to do and nothing more, so it's important to give it precise instructions. Here are steps to a general approach we have been using to prompt the bot:

1. Establish criteria: Think about the elements that define a strong example of the thing you want kids to learn about (You can draw from your rubrics or final assignments to do this).

2. Prompt: Prompt ChatGPT to create an example of whatever concept, process, or phenomena you are trying to teach.

3. Review and adapt: Review the bot's output and adapt it as you see fit.

4. Prompt for contrasting cases: Prompt it to create several non-examples, incorrect examples, or ambiguous examples. These are your contrasting cases.

5. Review and adapt: Review the outputs again and adapt them as you see fit.

Here's an example. With this one, our goal was to help students learn the underlying principles of kinetic and potential energy. We used ChatGPT to generate a range of different examples of kinetic and potential energy. Kids could sort these examples into categories and then explain their choices. In the screenshots below, the text next to the yellow icon is our prompt, and the text next to the green icon is ChatGPT's response. Following the process we introduced earlier:

Step 1 - Establish criteria: We wanted students to know that potential energy is energy that is stored, and kinetic energy is energy in motion.

Step 2 - Prompt: We asked ChatGPT to generate a list of five real-life examples of kinetic energy. (Click images for a larger view.)

Step 3 - Review and adapt: These examples looked pretty good. The fifth one - waterfall cascading down a cliff - might be a good example of both kinetic and potential energy. We could keep this one if we think our kids are ready for some ambiguity in the sorting exercise.

Step 4 - Prompt for contrasting cases: Next, we asked ChatGPT to generate examples of potential energy. These serve as our contrasting cases. (When prompting ChatGPT, you can basically talk to it as you would a person. For the most part, it remembers your previous prompts.)

Step 5 - Review and adapt: These examples also looked pretty good. We decided that we want to add one more ambiguous example that will increase the complexity of the contrasting cases. So we prompted ChatGPT:

We revised that example to simply read: "A car moving down a hill." That way, when we included it in our sorting exercise, students would have to do the work of defining the kinds of energy represented in the example.

Reviewing the outputs again, we noticed that three examples were very similar: a car moving down the highway (kinetic), a roller coaster at the top of the hill (potential), and a car moving down a hill (both). The similarities made these three examples a great illustration of contrasting cases, because students would need to come up with a nuanced rationale for why they represent different types of energy.

We could now mix up these examples on a Padlet or Google Slide, or we can print each one out on a separate piece of paper. Then students can debate with one another about each example, categorize them, and explain their choices. In their explanations, they would be constructing criteria that characterize each type of energy.

Using the example machine for different learning goals

Here are some ways to use ChatGPT to generate contrasting cases to help students understand underlying conceptual principles and build mental models. We have organized our examples based on three common learning goals: learning about processes, concepts, and arguments.

Examples to Explore Processes

Students learn about processes in many subjects. For example, they learn the steps for balancing chemical equations, solving mathematical inequalities, describing mitosis, or explaining how a bill becomes a law in the U.S. One way to help students learn the underlying logic of different processes is to generate contrasting cases of correct and incorrect sequences.

In the example below, we ask ChatGPT to provide a few contrasting cases to teach young students about the life cycle of a seed.

Step 1 - Establish criteria: First, we considered the steps we wanted students to understand.

Step 2 - Prompt: We prompted the bot to generate an accurate representation of that cycle. We also prompted the bot to write at the level of a five year-old, so we could ensure the explanation was accessible.

Step 3 - Review and adapt: We checked the bot's output to make sure it was accurate. We liked the initial result, so we kept it without revision.

Step 4 - Prompt for contrasting cases: In process learning, students need to know both what happens, and in what order. A logical activity is for students to have to move the steps from incorrect to correct order. Normally, we would re-organize the steps manually, but ChatGPT can do it faster.

We decided we also wanted a second contrasting case, so we asked ChatGPT to describe the seed's life cycle using the correct order, but leaving out steps. Now students would have to figure out what steps were missing: sprout growth and seed production. Again, this was something we would typically do ourselves, but giving the task to ChatGPT saved us some time.

Step 5 - Review and adapt: We liked these examples and decided to keep them without revision.

Just as with the activity about potential and kinetic energy, we could now present these contrasting cases to students either digitally or on paper, ask them to identify the most accurate representations, and then explain why. In doing so, students will start to develop "rules" about both the events in a seed's life and their order.

Using slight prompt modifications, teachers can change the order, accuracy, and completeness of the contrasting cases to deepen students' thinking about complex processes.

Adaptations for other subject areas:

Social studies: sequence historical events

Math: sequence steps in an approach to solving a proof

English: sequence key plot points in a novel

Examples to Explore Concepts

Teachers can also use ChatGPT to teach students to articulate principles that underlie complex concepts like authorial style, statistical variance, or separation of powers.

One of ChatGPT's coolest tricks is its ability to adopt the style of different writers or historical figures. It can also write in the style of different genres, like a cover letter, advertisement, or movie trailer. Creating contrasting cases with combinations of these outputs can make for a powerful teaching tool. In the example below, we wanted students to understand how different literary elements can contribute to authorial style, and to consider how those elements might affect their emotional responses to texts. We asked ChatGPT to produce texts in the style of different authors - all authors that were familiar to our students.

Using these contrasting cases, we could then ask students to match the review with the author, point to and name specific features of the writing that helped them identify the authors' styles, and then talk about the effects created by those different styles.

Step 1 - Establish criteria: We wanted students to understand that an author's style includes a combination of word choice, sentence structure, and attitude toward a topic. We wanted the examples to have different emotional effects.

Step 2 - Prompt: It would be easier for students to focus on style if the content of the text was similar. So we asked the bot to write about something students would be familiar with. We decided on a review of McDonald's in the style of three authors.

Step 3 - Review and adapt: In this review, ChatGPT used phrases like "dreary and tempestuous" and "wandering," which work well to represent Poe's language. The bot also did a good job creating a mood of gloom and foreboding. But we realized we wanted to emphasize Poe's punctuation (lots of exclamation points, for example). So we adapted our prompt.

Well, the bot went a little overboard with the exclamation points, so we might revise one more time.

Step 4 - Prompt for contrasting cases: Next, we wanted to generate our contrasting cases, so we asked ChatGPT to rewrite the reviews in the style of other authors that our students have read. We started with Sandra Cisneros.

Step 5 - Review and adapt: We didn't think Cisneros' characters would moralize about McDonald's, so we asked the bot to revise. We also realized that a lot of Cisneros' work is written in present tense. Making the change to present tense would give our students another element of style to consider and analyze. We prompted the bot again.

We might go for another round of revision, but we think this one is beginning to capture the style of Cisneros' narrators.

We tried for another example, this time turning to Zora Neale Hurston and Their Eyes Were Watching God for our model.

We thought some of the phrasing was a little obvious, and when we compared this example with some of Hurston's prose, we noticed that Hurston sometimes includes short, simple sentences in between longer ones. We adapted our prompt.

Now, here is another example where we prompted ChatGPT to provide some contrasting cases. This time, we used the bot in the context of a social studies unit on forms of government. In the example, ChatGPT's first response was pretty good. In this example, we will show you one way that we had to revise our initial prompts to generate more useful responses.

Step 1: Establish criteria: We wanted students to know that in a representative democracy, citizens vote in free and open elections to choose government leaders. In representative democracies, the rule of law applies equally to all citizens.

Step 2: Prompt:

Step 3: Review and adapt: In our first attempt, ChatGPT wrote a pretty accurate description. However, since we ultimately wanted students themselves to identify the types of government described in each example, we needed ChatGPT to remove the term "representative democracy." We also wanted it to add the criteria that rule of law applies to all citizens. So we had to revise our prompt.

Step 4: Prompt for contrasting cases: Next, we needed ChatGPT to generate contrasting cases. In other words, we wanted it to describe other types of governments besides representative democracy, including monarchy and communism. Importantly, because we wanted students to understand representative democracy, we also wanted a contrasting case that showed a different type of democracy. So, we prompted ChatGPT to include a description of direct democracy. Having learned our lesson in our last prompting attempt, we also prompted the bot to leave out the names of the governments themselves.

Step 5: Review and adapt: We liked these examples, but after reading them through a few times, we decided that they might be boring for kids. We decided to revise them so that each offered a specific scenario that students could connect with different forms of government.

We could print these examples on cards, give them to students, and ask them to identify the kinds of governments described in these examples. We could also go a step further and ask students to rank the descriptions based on the degree of power given to people in each example. This would require students not only to identify the characteristics of representative democracies but also understand its relationship to other forms of government. There are many variations to these types of sorting activities, and using contrasting cases will help students build rich mental models. ChatGPT magnifies our ability to use contrasting cases by creating useful examples more quickly than we could by ourselves.
Adaptations for other subject areas:

Science: "Write a description of the gaseous planets but do not use the term "gaseous." Now do the same for the ice giants and terrestrial planets."

Math: "Make up a math problem about rate, time, and distance, and then, using a character named Sam, describe three different ways that Sam tried to solve the problem. Have two solutions be correct, and one solution be incorrect."

Examples to Explore Arguments

One of the most important skills taught students learn in all subject areas is the ability to evaluate and construct arguments. In English class, students might write essays about whether Troy, from August Wilson's Fences, is a sympathetic character; in social studies, they might consider multiple causes and effects of World War I; in biology, they might make their case for whether a virus is a living organism. We can use ChatGPT to generate examples of arguments with contrasting structures or types of evidence, then students can evaluate each argument's effectiveness. For such a lesson design, we would use the five steps we described earlier:

1. Establish criteria for strong argument

2. Prompt

3. Review and adapt

4. Prompt for contrasting cases, including weaker or stronger evidence, or different structures

5. Review and adapt again

We could also use the bot to address a long-standing problem when it comes to teaching students to build arguments: Sometimes we ask students to write an argument about a text, but we do not give students anyone to argue with. In this case, ChatGPT can provide a contrasting case for a student to push back against.

For example, imagine that a high school class has just finished reading Fences. The teacher would like kids to consider the role of the fence as a potential symbol in Wilson's play. Instead of asking students to write an argument about the role of fences in the play, the teacher could offer students a ChatGPT-generated argument that students could respond to.

This argument in itself becomes a contrasting case for students to reflect on and respond to. They can agree with some of the interpretation, build on some parts of it, and refute other parts. In this way, their argument becomes more authentic. They might even direct their response to the bot.

We might also offer students an opposing argument about Fences:

With these two arguments in hand, we could ask students to debate the merits of each, search the text for supporting evidence, and write about perspectives beyond just these two. Doing so would help students consider multiple interpretations of complex texts and develop and refine their own arguments.

Adaptations for other subject areas:

Science: Generate summaries of competing scientific theories

Social Studies: Generate different arguments explaining cause and effects of historical events

Before ChatGPT, teachers might spend hours searching for or writing suitable examples of arguments like these. Now, we are learning how to prompt ChatGPT to generate these arguments to suit our teaching purposes.

What's Next?

There's so much more this example machine can do to help us save time and employ our creativity so that we can better serve our students. Here are a few additional prompts that create other kinds of examples:

Rewrite this paragraph at a 6th grade reading level

Use more complex vocabulary

Translate this sentence into Spanish, and then Vietnamese

With all of its possibilities in mind, a reminder: There are lots of ways that ChatGPT can create problems for teachers. The technology is still young, and it does not know when it is wrong. For instance, when we first asked ChatGPT to generate interpretations of Fences, it made up lines from the play. When we asked it to talk about the short story "Linoleum Roses," by Sandra Cisneros, it added characters that do not exist in that story, and offered unsupportable interpretations of the text. Part of our job now is to help students understand both what the tool can do and what it can't.

Want some ideas for what to DO with these examples once you have them? Three instructional strategies that would work beautifully with multiple examples like these are contrasting cases, concept attainment, and inductive learning.

Come back for more.
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How to Use ChatGPT as an Example Machine

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To learn any concept well, students need to experience multiple examples of that concept, and ChatGPT can help you generate those examples fast.

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Check out this Presentation designed by Andrea Nash.

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Generative AI at Harvard (Faculty Voices)

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Generative AI at Harvard (Faculty Voices)

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The videos in this library, created by the Office of the Vice Provost for Advances in Learning (VPAL), explore the myriad ways Harvard faculty use generative AI tools to support and enhance teaching, learning, and research. Scroll through the video pages below or filter by topic to learn more.

VPAL welcomes Harvard faculty, staff, and students to submit a request to record a video demonstrating how they have experimented with generative AI in their classrooms and/or coursework via this brief survey.

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Harvard GenAI Library for Teaching and Learning The videos in this library, created by the Office of the Vice Provost for Advances in Learning (VPAL), explore the myriad ways Harvard faculty use generative AI tools to support and enhance teaching, learning, and research. Scroll through the video pages below or filter by topic to learn more.

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Using ChatGPT to get ideas for which song to choose for final project in Spanish

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Using ChatGPT to get ideas for which song to choose for final project in Spanish

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🎤 Top 10 School-Appropriate Enrique Bunbury Songs

1. Lady Blue – A poetic and emotional song with introspective lyrics, widely considered one of his best.

2. Frente a Frente (with Tulsa) – A beautiful cover of the Jeanette classic, melancholic but clean.

3. ...Y al final – Reflective and heartfelt, with no explicit content.

4. El extranjero – A song about identity and change, metaphorical but appropriate.

5. Aunque no sea conmigo – A romantic duet with lyrics about longing, widely respected and suitable.

6. Los restos del naufragio – Symbolic language, no inappropriate content.

7. De todo el mundo – A mellow rock track with poetic themes.

8. Cuna de Caín – Rich in imagery, clean in language.

9. Infinito – A softer ballad from his early solo work.

10. El camino del exceso – Although the title references "excess," the song itself is metaphorical and non-explicit.

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Using ChatGPT to correct and explain correction for vocabulary list and definitions 

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Using ChatGPT to correct and explain correction for vocabulary list and definitions 

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Sure! Below is your original text, with each sentence corrected in bold, followed by an explanation of each correction in English:

1. Un lugar para aprender para los niños pequeños.

"Chicos" can mean boys or kids informally, but "niños" is more natural and standard in this context.

2. Un lugar para aprender para los niños pequeños.

Same sentence repeated; correction remains the same.

3. Un lugar para aprender después del colegio.

"Despues" → "después" needs an accent. Also, a space was missing before it.

4. Un lugar para aprender en un edificio escolar.

"Edifico" → "edificio" (spelling correction).

5. Un lugar para jugar deportes.

"Que jugar" → "para jugar" is the correct structure for expressing purpose.

6. Un lugar que da anuncios.

"Dice anuncio" → "da anuncios" (we say "give announcements" in Spanish).

7. Un lugar que tiene muchos cuartos y es grande.

"Muchos cuartos" is fine, but needs the verb "tiene" to be complete.

8. Una parte del campus donde estacionas tu carro.

"Un parte" → "Una parte" (part is feminine); "parque tu caro" → "estacionas tu carro" ("parquear" is used in some countries, but "estacionar" is more standard; also, "caro" means expensive — you meant "carro").

9. Un papel que te permite entrar al edificio.

"Entrar el edificio" → "entrar al edificio" (you need "a + el" = "al" for entering a place).

10. Otras personas en la clase.

"El clase" → "la clase" (clase is feminine).

11. Los árboles y muchas cosas verdes.

"El arboles" → "Los árboles" (correct article and plural form); "muchos cosas" → "muchas cosas" (cosa is feminine).

12. Una cosa que es muy larga, muy alta.

"Mas largo" → "muy larga" (gender agreement with "cosa"; "más" = more, "muy" = very).

13. Una cosa que es muy pequeña, muy corta.

"Mas pequeno" → "muy pequeña" (again, gender agreement and correct adjective).

14. Una cosa que se crea en el futuro o se ve en el futuro.

"Es crear" → "se crea" (passive voice); "mirar" → "ver" is more natural here.

15. Una cosa que nació o fue creada recientemente.

"Es nacio o crear fresco" → "nació o fue creada recientemente" ("fresco" doesn't mean recent — "recientemente" or "nueva" are better).

16. Una cosa del pasado.

Correct, no change needed.

17. Cuando tienes información.

"Tu tengo" → "tienes" (correct conjugation for "tú tener").

18. Cuando el maestro le dice algo al estudiante.

"Dice una cosa a el estudiante" → "le dice algo al estudiante" (correct indirect object pronoun and smoother phrasing).

19. Cuando haces deporte.

"Hace" → "haces" (correct conjugation for "tú hacer").

20. Cuando lees muchos libros.

"Lear" → "lees" (conjugation of "leer").

21. Cuando estás presente en la clase.

"To es" → "estás" (correct form of "tú estar").

22. El lugar donde los estudiantes asisten a clase.

"El estudiantes asistir a el clase" → "los estudiantes asisten a clase" (correct article, verb conjugation, and preposition).

23. Cuando muchos estudiantes están juntos.

"Esta junto" → "están juntos" (plural verb and agreement).

24. Algo relacionado con la escuela.

"Relacionada con la escuela" is better than "relacionado" only if referring to a feminine noun, but "algo" is masculine, so keep "relacionado".

Would you like me to reformat all the corrected sentences into a clean list for study purposes?

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The timing of this AI Pilot has not been great for me, since I teach 3 sections of juniors in honors precalc and there are MANY absences this week and next due to AP exams. As it is, I am behind with my curriculum and do not want to give up precious class time. So, I have not been able to roll out the AI pilot according to the suggested timeline. Cameron is going to assist me later this week to try a smaller pilot with the students who are in class.

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FEEDBACK from students on "Power Outage" AI assignment -- Spanish

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FEEDBACK from students on "Power Outage" AI assignment -- Spanish

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"In general, I do not tend to use AI on assignments, so using it here made it feel quite underwhelming as an assignment, and I think I would’ve learned more about both the power outage and gotten more spanish practice if I had done it myself."

"I found this assignment to be a good experience because experimenting with AI is always fun. While sometimes I find new technologies to be confusing, I like to play around with them in a non-stressful environment like this. I just used Chat GPT to create information for me, and I went off of that. My work and the assignment were very quick and easy. I asked AI to write an article, create questions, and clarify things for me. The assignment was very relaxing and super easy to complete. I would like to do more work like this in the future because sometimes smaller, individual assignments are a nice change of pace. ¨

"Using AI for this assignment made collecting information quick and easy but also mindless. By not actively searching and sifting through articles, I felt that I didn’t really do that much besides tell AI what I needed. It did not feel like learning. When I asked Chat GPT to create an article in 500-550 words it did. When prompted, it also churned out key vocabulary words, sample questions, and open-ended questions. The article itself was pretty thorough and gave a good description on what happened, including the causes of the power outage, and how people were affected. The 80-20 rule seems like too much AI and not enough of the person completing the work. I think a person should do their research themselves and if they can’t find something or don’t understand something, then they should go to AI. AI did a thorough job creating the components of this assignment, but I could have done just as good a job, even if it meant spending more time on it. The appeal to AI is that it is a huge time saver but constantly using AI might decrease someone’s attention span for an assignment. When you use AI, you could lose natural creativity and not develop the same research skills as without it. AI is not going to go away. I think it is important to use AI responsibly so that you are benefiting, but not cheating yourself out of your own thinking!"