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Summer 2024 - Extension of prototype active learning and HW modules to all of intro STEM curriculum, with assessments. 
                            Development sprint for course modules. 

Fall 2024 - First offering of GAI-empowered courses across entire introductory Harvard STEM curriculum. Prepare for second national workshop. 

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Instructional methodology viewpoint:  (pick 8 experiments for Fall 2023)

ItemexperimentscoursesleadGPT aspect neededValidation criteria

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. Develop first-generation tools 
  1. synthesis of student-provided questions, in real time
  2. open-response quizzes rather than multiple choice
  3. peer-instruction including GAI
  4. Sequential interaction on course prompts






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




C: Assist with analysis and gain insights from lab data. 




D: interactive student self-assessments. 




E: In-class group consultation (peer instruction) with ChatGPT participation




F: capturing and submitting GAI-enabled work for evaluation by course staff




G: automated evaluation of understanding of material, by evaluating answers to questions we provide. 




H: Ascertain subject-level mastery needed to exploit natural-langauge-driven code development.
         Try out a non-analytic problem and assess the results. 
  1. modulated-friction example. Modulated Friction example

15 a,b,c
Math 22


numerical solution code
I: incorporate into HW and assessments the ability to perform calculations, as pioneered by Khan Academy


arithmetic capability
J: incorporate course-specific training inputs and give that high weighting


custom training inputs
K: Automation of grading and assessments of student competence. 


sequential prompts run open loop, no adjustment
L: dynamic tutoring


sequential prompts with iterative adjustment 
M: GAI assisted generation and refinement of course instructional and assessment materials- HW, exams, quizzes, etc. 
  1. request a critique of exam questions
  2. request answer key to HW and exam questions




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