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Students' Perceived Roles, Opportunities, and Challenges of a Generative AI-powered Teachable Agent: A Case of Middle School Math Class

Authors
Yukyeong Song,
Jinhee Kim,
Zifeng Liu,
Chenglu Li,
Wanli Xing
Date
Publisher
arXiv
Ongoing advancements in Generative AI (GenAI) have boosted the potential of applying long-standing learning-by-teaching practices in the form of a teachable agent (TA). Despite the recognized roles and opportunities of TAs, less is known about how GenAI could create synergy or introduce challenges in TAs and how students perceived the application of GenAI in TAs. This study explored middle school students perceived roles, benefits, and challenges of GenAI-powered TAs in an authentic mathematics classroom. Through classroom observation, focus-group interviews, and open-ended surveys of 108 sixth-grade students, we found that students expected the GenAI-powered TA to serve as a learning companion, facilitator, and collaborative problem-solver. Students also expressed the benefits and challenges of GenAI-powered TAs. This study provides implications for the design of educational AI and AI-assisted instruction.
Study at a glance
  • Question: How do middle school students perceive the roles, benefits, and challenges of generative AI teachable agents in math?
  • Setting and data: An authentic middle school math classroom with 108 sixth-grade students
  • Method: Classroom observations, focus-group interviews, and open-ended surveys
Why it matters

Advancements in generative AI boost the potential of teachable agents for learning-by-teaching. However, less is known about how generative AI creates synergy or introduces challenges in teachable agents, and how students perceive their application.

Key findings
  • In a math class of 108 sixth graders, students expected generative AI teachable agents to serve as learning companions, facilitators, and collaborative problem-solvers.
  • Students identified benefits to using generative AI-powered teachable agents in their learning.
  • Students also reported challenges when using generative AI-powered teachable agents in the classroom.

Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.

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