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Research Assistants

Using LLMs for Supplementary Teaching Materials

This project will study how Large Language Models (LLMs) can be used to individualize standard teaching materials and to generate supplementary teaching materials for quantitative courses. Part of the goal is to tailor the learning experience outside the classroom to diverse group of students. This will include:

  1. Alternative explanations of concepts, including different difficulty levels.
  2. Generation and tailoring of different forms of content. This can also include visual, audio and video, and integrating with different tools such as Qualtrics and Latex.
  3. Evaluation of problem sets their difficulty level.
  4. Typical mistakes for a problem, and feedback on them.
  5. Feedback on solutions.

Requisite Skills and Qualifications

Strong background is probability/statistics and coding in Python. Background/interest related to LLMs and education would be preferred.