Considerations for Using AI in the Classroom

Ask 20 Questions of AI: In small groups, students collaborate to write 20 questions for a text-generating AI about how it works. In a larger group, they consider what the AI’s responses mean for academic integrity, authority, validity, trust, or other important ideas in your course. 

Analyze AI Perspectives: The instructor asks the text-generating AI to respond to a prompt as a specific person – e.g., a historical figure. Students then critique the AI’s response, drawing on their interpretation of the person’s perspective. 

Predict Where AI Excels: Individually students construct one question or prompt on a specific topic that they think text-generating AI can respond to successfully, and another prompt or question they think AI responds to unsuccessfully. In a larger group, students share their work to identify characteristics of prompts to which AI struggles to respond. For a related lesson outline, see Critical Analysis Across AI Tools & Stereoptypes from the AI Pedagogy Project at Harvard’s metaLAB.

Compare Exam Questions: Individually students write one multiple choice exam question and ask text-generating AI to write a second. In a larger group, students analyze which submitted questions are AI-written, which are human-written, and evaluate which provide a better assessment of learning.

Evaluate AI Output: The instructor uses AI to generate work, like a thesis, short analytical paper, theater dialogue, computer code, image, or even musical composition. In groups students analyze the sample work created by AI, with particular attention to evidence, sources, perceived bias, or other important elements for your course. Students can then revise it for improvement in groups, and share back revisions for comparison. For an example lesson outline, see Correct a Bad Essay from the AI Pedagogy Project at Harvard’s metaLAB.

Rubric Calibration with AI Writing: The instructor uses AI to generate an essay, thesis, or other written work. Groups then use a rubric to evaluate the AI’s work, and suggest changes or improvement to the rubric. This can help students think about how they define high-quality work, and how a rubric might help identify AI-generated work. 

Planning and Evaluating AI Use: Students create a plan for using AI within a specific assignment, like a scaffolded research paper, where they articulate for which steps it is valuable and appropriate to use AI, and when original thought and creativity are needed and why. This activity works best when sequenced with other activities that explore AI capabilities.

AI Drafting Process: Students use AI to generate a draft of a simple writing assignment. Students then analyze the AI’s writing, focusing on accuracy, bias, or other characteristics important in your course. You may also ask students to improve the AI’s draft to complete a second draft.

AI Feedback: Students ask AI to evaluate an initial draft of a short writing assignment, asking AI to focus on a specific element. Students then incorporate any valuable feedback into their work, and share their revisions with a small group. This can help students get another perspective on writing quickly, while encouraging them to consider that feedback critically.

AI Thesis Revision: Students use AI to quickly generate thesis statements on a variety of topics. Individually students revise these statements and share two that are strongest to a group for feedback, including what prompts they provided the AI and what revisions they made to each statement. Students use AI to “get started” by quickly generating ideas, and then leverage their own skills to refine and improve.

Writing with Images: Students or instructors use image-generating AI as part of a reflective writing, freewriting, or creative writing process in any language. Students can use AI to quickly visualize descriptions from their writing, or students or instructors can use AI to generate images that prompt elaboration in writing. For an example lesson outline for generating images, see AI Image Remixing from the AI Pedagogy Project at Harvard’s metaLAB.

Co-create Class Expectations: Students collaborate to suggest “ground rules” for using AI within a specific course or assignment. As a class, consider specific tasks where AI is helpful, tasks where AI is unhelpful, when students and instructors think using AI is cheating, and if and how students should cite AI in their work. Ultimately the class will produce documented expectations with the instructor for using AI. For an example lesson outline related to co-creating and discussing expectations, see Debating the Ethics of Generative AI from the AI Pedagogy Project at Harvard’s metaLAB.

Structure an AI Discussion: Based on the “structured academic controversy” model, students are assigned a stance related to using AI in the classroom. Groups collaborate to develop arguments for one perspective and take turns presenting while the other team listens actively and then summarizes the arguments they heard. Individually or in a large group, students then reflect on what they learned, how their personal stance may differ from the stance they were assigned, and whether or not their personal position has changed.

Make Instructor Expectations Clear: Whatever your aims for using (or prohibiting) the use of AI within your classroom, make your expectations clear to students at the semester’s start. This may include adding a statement to your existing academic integrity statement, and reviewing expectations with students in class. Students should also have the option to not use any tool that requires personal information shared with a third party not contracted by the University.