GAI-Assisted Personal Discussion Process Analysis

Mu Sheng Chen, Tai Ping Hsu, Ting Chia Hsu*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationInnovative Technologies and Learning - 7th International Conference, ICITL 2024, Proceedings
EditorsYu-Ping Cheng, Margus Pedaste, Emanuele Bardone, Yueh-Min Huang
PublisherSpringer Science and Business Media Deutschland GmbH
Pages194-204
Number of pages11
ISBN (Print)9783031658839
DOIs
Publication statusPublished - 2024
Event7th International Conference on Innovative Technologies and Learning, ICITL 2024 - Tartu, Estonia
Duration: 2024 Aug 142024 Aug 16

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14786 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Conference on Innovative Technologies and Learning, ICITL 2024
Country/TerritoryEstonia
CityTartu
Period2024/08/142024/08/16

Keywords

  • Generative Artificial Intelligence education
  • lag sequential analysis
  • problem-solving tendency
  • student behavior pattern

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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