AI in the Classroom

Trust (2022) lists ways to engage students in critiquing and improving ChatGPT responses.

• Pre-service teachers might critique how a ChatGPT lesson plan integrates technologies using the Triple E Rubric or examine whether it features learning activities that support diversity, equity, accessibility, and inclusion. (This will help future teachers learn to critique TPT resources! )

• Computer science students might identify potential ways to revise ChatGPT generated code to reduce errors and improve output.

• Middle school students might critically review the feedback ChatGPT provides on their writing and determine what is most helpful to their own learning. 

• High school and college students could analyze, provide feedback on, and even grade text produced by ChatGPT as a way to prepare for peer review of their classmates’ work. 

Watkins (2022) suggests designing an assignment where students:

1. Identify a current issue in your field.
2. Develop a rubric with specific criteria upon which to judge a chatbot's response.
3. Individually write a question prompt for the chatbot.
4. In groups, compare the responses by applying the rubric.

Engage students in critical thinking by asking them to revise chatbot outputs. If you are hesitant to ask students to sign up for a chatbot account (see our privacy and free labor discussion), generate a few responses yourself and post these in your LMS course.

You can structure your assignment so students will:

• Use the Track Changes feature to mark up a chatbot output;
• Reflect on the chatbot output by noting what important details are missing;
• Research claims made in the chatbot output and add in appropriate citations;
• Expand on a particular section or claim; or
• Rewrite the output from the other side of the argument.

Ideas were inspired by Watkins (2022).

Chatbots can be a great tool at the beginning of projects. Students can ask a chatbot to:

• Generate 10 ideas for a paper about a specific topic;
• Create an outline for a paper;
• Create an outline for an infographic;
• Generate ideas for a podcast;
• List blog post ideas.

After using the chatbot for brainstorming, students can then craft their final project.

Educators can assess students' prompts to a chatbot to assess their knowledge. For this kind of assignment, students could ask the chatbot an initial question, and then follow up with additional prompts to hone a more accurate or holistic response. 

Students can respond to the output and create a new but similar output by stating something like, "Great, but this time include..."

Students act as the experts and guide the chatbot to the best response.

Idea from Bruff (2023).

Ask ChatGPT to design a board game or invention related to the course content and then have students build a physical or digital model for the design/invention. (ChatGPT can’t build the inventions it comes up with.)

Idea from Trust (2023).

Trust (2022) suggests to use ChatGPT to analyze how the bot generates text for different audiences. For example:

• Ask ChatGPT to explain a concept for a 5 year old, college student, and expert. Analyze the difference in the way ChatGPT uses language. 

Ofgang (2022) has a similar idea: use the chatbot to generate outputs to compare and analyze different genres or writing styles (e.g., Ernest Hemingway).

AI chatbots can enter into the role of a game simulator when given the right prompt as demonstrated by Bryan Alexander. Learners can practice critical thinking and decision making as they interact with the simulation. (Note the guardrails, biases, and limitations that Alexander points out in his blog post.)

Instructors can leverage social annotation to emphasize student voice, increase student motivation to complete assignments themselves, and deemphasize the need to turn to chatbots. 

In October 2023, Butler University hosted a workshop called "Leveraging social annotation in the age of AI" led by our Hypothesis customer success manager. To learn how to use Hypothesis, a social annotation tool, to decrease students' reliance on AI, review the resources from the workshop:

• Leveraging social annotation in the age of AI (slides)
• Leveraging social annotation in the age of AI (recording)

Here are some other links that might help you get started with Hypothesis:

1. Instructions: How to create an Hypothesis-enabled reading in Canvas Assignments
2. Annotation starter assignments (assignment instruction examples to use in or adapt for your course)
3. Video to share with students: annotation basics