Page Comparison

A: Incorporation of GAI into lecture-format STEM learning: 

1. Develop experimental active learning lecture modules that incorporate GAI capabilities, and devise methods to measure their effectiveness in student comprehension and retention. 
2. Use multi-shot learning to have GAI produce 'clicker' questions and active learning modules.
3. Have GAI do assessments of online active learning modules. 
4. Increase accessibility of course materials

1. Assess utility of synthesis of student-provided question content, in-class just-in-time learning
2. Assess utility of synthesize summaries of open-response clicker questions rather than multiple choice, for adaptive lectures
3. Assess utility of peer-instruction that includes GAI virtual partners
4. Assess utility of GAI-produced active learning modules
5. Compare restricted-content (textbook and lecture materials) vs. all-content GAI generated active learning modules. 

shared-edit document fed into GAI, results available to instructor. 

Multi-shot learning using restricted content and open 

PPT and math content upload as tokens

B: Develop and Exploit short-cycle adaptive problem sets with real-time feedback

1. produce a 'virtual tutor' that uses a script of desired learning goals to promote student learning
2. distinguish between conceptual mastery and ability to solve quantitative problems. To what extent can GAI do the math part? 

1. Assess learning effectiveness of rapid-feedback interactive learning, outside of lecture. 
2. assess zero-shot vs multishot training for virtual tutor effectiveness. 
3. Assess instructor burden compared to current methods. 

Ability to identify main topics, and embed in GAI interaction. 

Arithmetic needs to work. 

1. Assess effectiveness of using the combination of GAI and Jupiter notebooks to do guided data exploration. 

notebook and GAI integration

ability to access data files from instructional lab data collection. Does this mean a browser interface with access to local files? 

1. Assess utility of GAI in helping student prioritize where to focus to enhance their mastery of material. 

1. Assess impact of 'temperature' setting for student learning

1. Use things like modulated-friction example, Modulated Friction example , to help students learn how to assess and refine GAI produced material. 

15 a,b,c
Math 22

1. request a critique of exam questions
2. request answer key to HW and exam questions

1. upload Canvas course materials and any ppt from previous year, including student CUE evaluation narratives and restrict responses to that material. 

1. restricted-scope utility using uploaded content
2. integration with grading systems
3. integration with Canvas
4. automated sectioning tool
5. integration with Slack? 
6. multi-shot 

need to mesh student user account on GAI system with their HUID and course record. 

Instructor-level overview of 

P. Validation and verification tools and methods

1. Develop methods for assessing and refining GAI-produced code 

1. Assess level of expertise needed to get credible answers
2. Conduct iterative-engagement tests 

1. real-time access to URL's 
2. provenance tracking
3. code validation and verification 

1. refining GAI-produced code 

1. Assess level of expertise needed to get credible answers
2. Conduct iterative-engagement tests 

1. real-time access to URL's 
2. provenance tracking
3. code validation and verification 

Thanks for sending this email. I am very excited about this new technology. In fact, with Louis Deslauriers, we used some of it in my Physics 15B last semester.
I am currently writing a proposal for the Cottrell Scholars, where this will be featured, and I intend to use them in my incoming classes.
I will look at the links in your email. Have a wonderful summer, cheers,

Carlos