Generative AI Pedagogy

Instructional methodology view:

Item	experiments	course	lead	GPT aspect
active learning methodology in lectures	synthesis of student questions, in real time open-response quizzes rather than multiple choice peer-instruction including GAI
short-cycle adaptive problem sets
analysis and insights from lab data
interactive student self-assessments.

For each participating course

Assess our assessments: run midterm and final exams of science courses through GPT-4 and grade the results. Compare to overall student performance.
Enhance our assessments. Solicit constructive feedback on the exam questions we submit.
Assess our homework: run homework assignments through GPT-4 and grade the results. Compare to overall student performance.
Enhance our assignments. Solicit constructive feedback on the homework we submit.
Ask (require?) students to use GPT-4 on selected assignments to get feedback and examples of how it can be used.
Course-specific chat-bots- what training data?
For large lecture classes- merge active learning with GPT
For sections- aggregation of questions,
For labs- try out data analysis methods and inference
Customized training assembly of material - what do we need to start to capture?
Advising and course selection
Khan academy