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ABSTRACT
The rapid advancement of Generative Artificial Intelligence Technology has increasingly drawn attention to its potential applications in the educational sector. This study aims to investigate the effects of Situational Interactive Teaching, facilitated by generative artificial intelligence, on students’ learning outcomes and flow experiences. A series of experiments were designed to compare the performance of a Generative Artificial Intelligence-supported Situational Interactive Teaching Method with a Traditional Video Interactive Teaching Method. Data was collected using research tools such as questionnaires and test questions to assess students’ cognitive levels, learning effectiveness, flow experiences, and subjective evaluations during the instructional process. The analysis revealed distinct differences between the two teaching methods. The findings suggest that compared to traditional teaching methods, Generative Artificial Intelligence-supported Situational Interactive Teaching significantly improves students’ learning outcomes in cognitive, skill, and affective domains, while also enhancing flow experiences. These positive effects are not limited by individual student differences, indicating broad applicability. Furthermore, this teaching approach can foster a positive feedback loop between learning effectiveness and flow experience. In conclusion, this study confirms the effective application of generative artificial intelligence technology in legal education, providing empirical evidence for the promotion of this innovative teaching model in the educational field.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Supplementary material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/02188791.2024.2305161
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Notes on contributors
S.J. Shi
S.J. Shi, female, is a postgraduate student in Education Technology, School of Network Education, Beijing University of Posts and Telecommunications. Her main research interest is intelligent education technology and application.
J.W. Li
J.W. Li is a associate professor at Beijing University of Posts and Telecommunications. His main research interest is intelligent education technology and application.
R. Zhang
R. Zhang is a professor at Beijing University of Posts and Telecommunications . Her research interests include virtual reality technology and application, educational metaverse,intelligent education technology and application, etc.