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AI in the Classroom

This guide covers artificial intelligence in the classroom, including how to incorporate AI into assignments and academic honesty issues that may arise from students' use of AI tools.

Assignment Considerations

Before assigning work that involves the use of AI tools, please read the information about privacy and other concerns with generative AI. Caines (2022) suggests to consider:

  • Not asking students to create accounts for AI tools and instead doing instructor demos;
  • Encouraging students to use burner email accounts (to reduce personal data collection) if they choose to use the tool;
  • Using one shared class login.

Assignment Ideas

One researcher commented on Meta's Galatica tool (which was taken offline after three days of demo and user feedback), saying, “You should never keep the output verbatim or trust it. Basically, treat it like an advanced Google search of (sketchy) secondary sources!” (Cranmer, 2022, as cited in Heaven, 2022). 

Students' digital and information literacy skills now need to expand to include AI literacy. Explore this topic with your students by designing assignments like:

  • Determining if writing was human-produced or machine-produced;
  • Discussing how AI tools work and what intelligence means for humans and machines;
  • Brainstorming how AI can be used in students' future professions, noting limitations and ethical considerations;
  • Examining the dataset used to train a particular AI tool (e.g., Who created it? How was it collected? If personal data was used, did individuals give consent? Is the data representative of the population using the tool? What biases may be present?);
  • Fact checking outputs by AI—trace claims to original source materials or find sources to refute claims;
  • Exploring the limitations of AI in your discipline;
  • Discussing how to resist automation bias like that found in Robinette et al.'s (2016) “Overtrust of Robots in Emergency Evacuation Scenarios” research (Toon, 2016). 

Ideas inspired by Long & Magerko (2020).

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 an AI response.
  3. Individually write a question prompt for the AI tool.
  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.)

References

References

Alexander, B. (2023, March 5). Experimenting with using ChatGPT as a simulation application. Bryan Alexander. Retrieved March 6, 2023, from https://bryanalexander.org/gaming/experimenting-with-using-chatgpt-as-a-simulation-application/

Bruff, D. (2023, January 5). A bigger, badder clippy: Enhancing student learning with AI writing tools. Agile Learning. Retrieved January 9, 2023, from https://derekbruff.org/?p=3995

Caines, A. (2022, December 29). ChatGPT and good intentions in higher ed. Is a Liminal Space. Retrieved January 6, 2023, from http://autumm.edtech.fm/2022/12/29/chatgpt-and-good-intentions-in-higher-ed/

Heaven, W.D. (2022, November 18). Why Meta’s latest large language model survived only three days online. MIT Technology Review. Retrieved on January 12, 2023, from https://www.technologyreview.com/2022/11/18/1063487/meta-large-language-model-ai-only-survived-three-days-gpt-3-science/

Long, D & Magerko, B. (2020, April). What is AI literacy? Competencies and design considerations [Research article]. CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, New York, NY, United States. https://doi.org/10.1145/3313831.3376727

Ofgang, E. (2022, December). What is ChatGPT and how can you teach with it? Tips & tricks. Tech & Learning. Retrieved on January 9, 2023 from https://www.techlearning.com/how-to/what-is-chatgpt-and-how-to-teach-with-it-tips-and-tricks

Toon, J. (2016, February 29). In Emergencies, Should You Trust a Robot? Georgia Tech News Center. Retrieved on January 12, 2023, from https://news.gatech.edu/news/2016/02/29/emergencies-should-you-trust-robot

Trust, T. (2023). ChatGPT & education [Google Slides]. Retrieved on January 6, 2023, from https://docs.google.com/presentation/d/1Vo9w4ftPx-rizdWyaYoB-pQ3DzK1n325OgDgXsnt0X0/edit?usp=sharing 

Watkins, R. (2022, December 18). Update your course syllabus for chatGPT. Medium. Retrieved on January 6, 2023, from https://medium.com/@rwatkins_7167/updating-your-course-syllabus-for-chatgpt-965f4b57b003

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