generative AI ideas for teaching and learning

Discipline: Multidisciplinary

Compare Exam Questions

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. Image: Midjourney “Exam Question –no person”

Evaluate AI Output

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 […]

Predict Where AI Excels

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. Image: Midjourney “Predict –no person”

Ask 20 Questions of AI

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.  Image: Midjourney “20 Questions”

Socially Annotate OpenAI’s privacy and service Terms 

Socially Annotate OpenAI’s privacy and service Terms 

Use an annotation tool like Hypothesis to have students read and comment upon the TOS of a chatbot like ChatGPT. Do this before you ever ask them to use one of these tools as a way of interrogating what is happening with our data when we engage with generative AI. Image: Midjourney “Annotation –no person”