2023-2024 Winner

Artificial Mentors for Student-Driven Projects

Helping mentorless high school students elevate their projects to their fullest potential

Carnegie Mellon University

United States of America
Track:
21st Century World
Award Level:
Catalyst Award

Project Description

Artificial Mentors for Student-Driven Projects is a web-application that provides personalized reflective conversations and active elaboration with feedback exercises that students can use to refine their project proposals and explore relevant technical concepts. Our tool uses generative artificial intelligence to automatically generate adaptive and personalized elaboration practice. Elaboration with feedback is an educational technique known to improve memory and comprehension by connecting new information to what students already know. We believe that the benefits of elaboration with feedback will drive students to use our tool over and over again. The rich interaction data collected by our tool could guide educational practice and policy by providing insight on how students choose to design their projects, what frustrates them, and how they envision their projects helping their careers and communities.

Meet Our Team

Gati Aher

PhD Candidate in Machine Learning, Carnegie Mellon University

Zachary Lipton

Professor of Machine Learning, Carnegie Mellon University and CTO, Abridge

Robin Schmucker

PhD Candidate in Machine Learning, Carnegie Mellon University

Tom Mitchell

Founders University Professor, Machine Learning Department, Carnegie Mellon University

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