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Session Type: Symposium
The use of artificial intelligence (AI) has garnered immense attention from educators and researchers. Despite the increasing interest, little attention has been paid to how to integrate research on teaching and learning into AI-based educational tools and applications. Many of the current applications of AI in education fall short of providing solutions to complex educational problems, which can perpetuate existing problems or create new challenges. In this session, we will share cutting-edge research on AI applications that have successfully integrated research on teaching and learning into their designs. This symposium will shed light on how AI can be used to offer quality solutions that have overcome the limitations of prior approaches, rather than amplifying current educational problems.
Innovative Artificial Intelligence Solutions for Improving Online Professional Development for Teachers: Multi-Agent Large Language Models - Kaiqi Yang, Michigan State University; Yasemin Copur-Gencturk, University of Southern California; Ahreum Han, University of Southern California; Harvey Li, Michigan State University; Jingxian Li, University of Southern California; Jiliang Tang, Michigan State University
Assessing Teachers' Content and Pedagogical Content Knowledge with an LLM-Based Grading System - Yucheng Chu, Michigan State University; Yasemin Copur-Gencturk, University of Southern California; Harvey Li, Michigan State University; Jiliang Tang, Michigan State University
Automatic Lesson Plan Generation via Large Language Models with Self-Critique Prompting - Zitao Liu, Jinan University
Improving the Effectiveness of an Intelligent Pedagogical Agent Through Explainable AI (XAI) - Min Chi, North Carolina State University