Paper Type
Short
Paper Number
1245
Description
This study investigates the integration of Socratic teaching methods in generative AI chatbots and its impact on enhancing student learning experiences and outcomes. Utilizing the Design Science Research (DSR) model, we propose a Socratic ChatGPT that employs questioning techniques. The research aims to address the current limitations of AI chatbots in educational settings, such as the risk of students' over-reliance on direct answers, by fostering deep thinking and active learning. A field experiment, supplemented by surveys and interviews, is adopted to evaluate the effectiveness of these chatbots. Although results are pending, this study promises to offer valuable insights into the potential of AI chatbots to revolutionize learning processes and provide practical implications in educational settings.
Recommended Citation
Ma, Tianyi; Chen, Runnan; LI, Andy Tao; and Liu, Hefu, "Socratic ChatGPT: Theory, Design, and Empirical Evaluations" (2024). PACIS 2024 Proceedings. 12.
https://aisel.aisnet.org/pacis2024/track14_educ/track14_educ/12
Socratic ChatGPT: Theory, Design, and Empirical Evaluations
This study investigates the integration of Socratic teaching methods in generative AI chatbots and its impact on enhancing student learning experiences and outcomes. Utilizing the Design Science Research (DSR) model, we propose a Socratic ChatGPT that employs questioning techniques. The research aims to address the current limitations of AI chatbots in educational settings, such as the risk of students' over-reliance on direct answers, by fostering deep thinking and active learning. A field experiment, supplemented by surveys and interviews, is adopted to evaluate the effectiveness of these chatbots. Although results are pending, this study promises to offer valuable insights into the potential of AI chatbots to revolutionize learning processes and provide practical implications in educational settings.
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Education