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GAI-Assisted Personal Discussion Process Analysis

  • Mu-Sheng Chen,
  • Tai-Ping Hsu,
  • Ting-Chia Hsu

摘要

Generative Artificial Intelligence (GAI) presents a promising avenue for educational enhancement, offering personalized learning experiences and fostering creativity, critical thinking, and problem-solving skills among students. However, its integration into education poses challenges, including limited comprehension of GAI’s capabilities and concerns about stifling creativity. This study explored the intersection of Bloom’s cognitive level and AI literacy to investigate students’ interaction patterns with GAI in problem-solving scenarios. Utilizing a university course as a testing ground, the research evaluated students’ problem-solving tendencies and online discussion behaviors. Results indicated a significant difference in problem-solving tendencies between high- and low-achieving students, with high achievers demonstrating more proactive exploration and critical analysis. Furthermore, online discussion analyses revealed that high achievers exhibited structured inquiry behaviors, starting from foundational knowledge acquisition to deep comprehension, integration, and comparative analysis, while low achievers tended to focus on immediate application without a strong foundation of understanding. These findings underscore the importance of fostering proactive inquiry skills and providing structured learning environments to maximize the benefits of GAI in education while mitigating its limitations. Further research is recommended to refine instructional strategies and optimize GAI integration for enhanced learning outcomes.