Machine Learning in Science Education Panel Discussion
Monday, Sep. 30, 2024
3:30-5:30 pm ET

Machine Learning is rapidly influencing many spheres of human activity. As part of the CMSA Mathematics and Machine Learning Program, this panel discussion will explore current and future uses of Machine Learning in science education. Panelists will make brief presentations, which will be followed by discussion and audience questions.

Gregory Kestin (Harvard University)
AI-Supported Activities: Design Principles and Impact on Student Learning

Logan McCarty (Harvard University)
Surveying the Landscape: Teaching and Learning with AI

Alexis Ross (Massachusetts Institute of Technology)
Adaptive Teaching towards Misconceptions with LLMs

Ilia Sucholutsky (New York University)
Why should machines have human-like  representations? Towards  student-centric AI tutors

Organizers:

• Dan Freed (Harvard University and CMSA)
• Michael Douglas (CMSA)