Mentigo: An Intelligent Agent for Mentoring Students in the Creative Problem Solving Process

要旨

Creative Problem-Solving (CPS) promotes creative and critical thinking while enhancing real-world problem-solving skills, making it essential for middle school education. However, providing personalized mentorship in CPS projects at scale is challenging due to resource constraints and diverse student needs. To address this, we developed Mentigo, an AI-driven mentor agent designed to guide middle school students through the CPS process. Using a dataset of real classroom interactions, we encoded CPS task stages, adaptive guidance strategies, and personalized feedback mechanisms to inform Mentigo`s dynamic mentoring framework powered by large language models (LLMs). A comparative experiment with 12 students and evaluations from five expert educators demonstrated improved student engagement, creativity, and task performance. Our findings highlight design implications for using LLM-based AI mentors to enhance CPS learning in educational environments.

著者
Siyu Zha
Tsinghua University, Beijing, China
Yujia Liu
Tsinghua University, Beijing, China
Chengbo Zheng
Hong Kong University of Science and Technology, Hong Kong, Hong Kong
Jiaqi Xu
university of California Los Angeles, Los Angeles, California, United States
Fuze Yu
Beijing University of Technology, Beijing, China
Jiangtao Gong
Tsinghua University, Beijing, China
YINGQING XU
Tsinghua University, Beijing, China
DOI

10.1145/3706598.3713952

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713952

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Creativity Support

G314+G315
6 件の発表
2025-04-29 23:10:00
2025-04-30 00:40:00
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