TY - GEN
T1 - GAI-Assisted Personal Discussion Process Analysis
AU - Chen, Mu Sheng
AU - Hsu, Tai Ping
AU - Hsu, Ting Chia
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - Generative Artificial Intelligence education
KW - lag sequential analysis
KW - problem-solving tendency
KW - student behavior pattern
UR - http://www.scopus.com/inward/record.url?scp=85200438879&partnerID=8YFLogxK
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U2 - 10.1007/978-3-031-65884-6_20
DO - 10.1007/978-3-031-65884-6_20
M3 - Conference contribution
AN - SCOPUS:85200438879
SN - 9783031658839
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 194
EP - 204
BT - Innovative Technologies and Learning - 7th International Conference, ICITL 2024, Proceedings
A2 - Cheng, Yu-Ping
A2 - Pedaste, Margus
A2 - Bardone, Emanuele
A2 - Huang, Yueh-Min
PB - Springer Science and Business Media Deutschland GmbH
T2 - 7th International Conference on Innovative Technologies and Learning, ICITL 2024
Y2 - 14 August 2024 through 16 August 2024
ER -