GPTutor: Great Personalized Tutor with Large Language Models for Personalized Learning Content Generation
May 16, 2024 Β· Declared Dead Β· π ACM Conference on Learning @ Scale
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Authors
Eason Chen, Jia-En Lee, Jionghao Lin, Kenneth Koedinger
arXiv ID
2407.09484
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.CY
Citations
17
Venue
ACM Conference on Learning @ Scale
Last Checked
4 months ago
Abstract
We developed GPTutor, a pioneering web application designed to revolutionize personalized learning by leveraging the capabilities of Generative AI at scale. GPTutor adapts educational content and practice exercises to align with individual students' interests and career goals, enhancing their engagement and understanding of critical academic concepts. The system uses a serverless architecture to deliver personalized and scalable learning experiences. By integrating advanced Chain-of-Thoughts prompting methods, GPTutor provides a personalized educational journey that not only addresses the unique interests of each student but also prepares them for future professional success. This demo paper presents the design, functionality, and potential of GPTutor to foster a more engaging and effective educational environment.
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