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.
Gati Aher
PhD Candidate in Machine Learning, Carnegie Mellon University
Gati Aher is a PhD candidate in the Machine Learning Department in Carnegie Mellon University, advised by Professor Zachary Lipton. Gati’s research centers on developing tools for self-driven learning and applications of generative artificial intelligence that augment human capabilities.
