GPTutor: Great Personalized Tutor with Large Language Models for Personalized Learning Content Generation

被引:3
作者
Chen, Eason [1 ]
Lee, Jia-En [1 ]
Lin, Jionghao [1 ]
Koedinger, Kenneth [1 ]
机构
[1] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA
来源
PROCEEDINGS OF THE ELEVENTH ACM CONFERENCE ON LEARNING@SCALE, L@S 2024 | 2024年
基金
美国国家科学基金会;
关键词
Personalized Learning; Adaptive Learning; Large Language Models; ChatGPT; Prompt Engineering;
D O I
10.1145/3657604.3664718
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页码:539 / 541
页数:3
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