Per Urlaub and Michael S. Strano share the positive impacts and the challenges associated with using generative AI in MIT subjects.
Per Urlaub is Professor of the Practice in German and Second Language Studies, and the Director of Global Languages at MIT.
Michael S. Strano is Carbon P. Dubbs Professor in Chemical Engineering at MIT, as well as the Founder and Lead Principal Investigator for the Center for Enhanced Nanofluid Transport and for Disruptive and Sustainable Technology for Agricultural Precision.
Chapters:
0:00 INTRODUCTION
1:14 PER URLAUB
2:14 Why incorporate AI in education
4:12 Pedagogical framework: Zone of proximal development
7:25 Interactive guidance from AI
8:19 Use case - Critical reflection on AI-powered translations
11:02 Use case - Role playing with an AI coach
12:31 Use case - AI as a writing tutor
17:30 Designing opportunities to reflect critically
18:29 MICHAEL S. STRANO
19:22 About 10.65 Chemical Reactor Engineering
20:08 Why use AI for 10.65 problems
22:11 Copilot to save time for students
23:34 Pre-class engagement with Copilot
23:56 Use case - Looking up details
24:39 Use case limitation - Specific-problem types
26:04 Use case limitation - Ambiguous problems
26:43 Use case limitation - Programming
27:26 Post-class engagement with AI
28:20 Lessons from student feedback
30:08 Iteration and next steps
31:36 DISCUSSION & Q/A
31:58 Student experience and comfort with AI
35:13 Structuring prompts
37:51 Critical thinking
42:02 Learning over time
46:48 Deciding on goals
48:42 Reading and technology
MIT Open Learning:
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