AI 中文总结
该研究探究了入门物理学习者的认识论信念与其聊天机器人偏好的关联，发现偏好组合型聊天机器人的学生认识论信念更复杂，但相关差异经Bonferroni调整后无统计学意义，为物理教育聊天机器人设计提供启示。
AI 中文摘要
不断发展的技术传统上影响着教学实践，生成式AI是有望变革高等教育的此类技术之一。本研究调查了入门学生对聊天机器人行为的偏好与其围绕物理学的认识论信念之间的关联。研究背景为一个定制的在线波浪模块，其中包含与聊天机器人集成的模拟。学生的聊天机器人偏好通过三个选项（引导式探究、直接答案、以及探究与答案的组合）进行收集，其认识论信念则通过标准化的物理科学认识论信念评估（EBAPS）调查进行测量。结果显示，偏好“组合”型聊天机器人（即最初引导学生进行探究，在明确要求时提供答案）的学生，表现出比偏好提供答案型聊天机器人的学生更复杂的认识论信念。值得注意的是，在偏好引导式探究型聊天机器人和偏好答案导向型聊天机器人的学生之间，未观察到EBAPS总分的关联。此外，在应用Bonferroni调整后的显著性水平后，观察到的差异不再具有统计学意义。本文讨论了这些结果对物理教育中聊天机器人的设计和教学应用的启示。
英文摘要
Evolving technologies have traditionally influenced pedagogical practices and Generative AI is one such technology that promises to transform higher education. In this study, we investigate the association between introductory students' preferences for chatbot behavior and their epistemological beliefs surrounding physics. Our context involves a custom built online module on waves containing simulations integrated with a chatbot. While students' chatbot preferences were captured through three provided options (guided-inquiry, direct answer, and a combination of inquiry and answer), their epistemological beliefs were captured through the standardized Epistemological Beliefs Assessment for Physical Sciences (EBAPS) survey. Results highlight that students who preferred chatbots that initially engage them in guided-inquiry but provide answers when explicitly sought (`Combination'), demonstrated sophisticated epistemological beliefs than those who preferred answer-providing chatbots. Notably, we did not observe any association between the EBAPS' total scores among students who preferred guided-inquiry and those who preferred answer-oriented chatbots. Furthermore, the observed differences did not remain statistically significant after applying a Bonferroni-adjusted significance level. Implications of these results for the design and instructional use of chatbots in physics education are discussed.
CommentsProceedings of the 2026 Physics education research Conference
