比较基于教学导向的定制与通用目的GAI聊天机器人对学生产生的科学问题解决过程和表现的影响：使用异质交互网络分析
Comparing the Impact of Pedagogy-Informed Custom and General-Purpose GAI Chatbots on Students' Science Problem-Solving Processes and Performance Using Heterogeneous Interaction Network Analysis
AI总结：
本研究通过异质交互网络分析比较了基于教学导向的定制与通用目的GAI聊天机器人对学生产生的科学问题解决过程和表现的影响，发现定制聊天机器人能提高学生的认知互动强度和多样性。
摘要：
问题解决在科学教育中起着关键作用，生成式AI（GAI）聊天机器人已成为支持学生科学问题解决的有前途的工具。然而，通用目的聊天机器人（如ChatGPT）往往提供直接的、现成的答案，可能导致学生认知卸载。先前研究很少关注定制聊天机器人促进学生科学问题解决，也未探讨它们如何与通用目的聊天机器人不同地影响问题解决过程和表现。为解决这一差距，我们开发了一个基于苏格拉底提问法的教学导向定制GAI聊天机器人，通过提示问题引导学生。本研究采用被试内平衡设计，48名中学生使用定制和通用目的聊天机器人完成两个科学问题解决任务。收集并分析了3297个学生-聊天机器人对话，使用异质交互网络分析（HINA）。结果显示：（1）学生在使用定制聊天机器人时表现出显著更高的互动强度和认知互动多样性；（2）学生更可能遵循定制聊天机器人提供的指导进行思考和反思，而倾向于请求通用目的聊天机器人执行特定命令；（3）在两种聊天机器人条件下，学生的问题解决表现（通过解决方案质量评估）无显著差异。本研究提供了新的理论见解和实证证据，表明定制聊天机器人比通用目的聊天机器人更少导致认知卸载，反而促进更大的认知参与。本研究还提供了关于GAI聊天机器人在科学教育中设计和整合的见解。
英文摘要：
Problem solving plays an essential role in science education, and generative AI (GAI) chatbots have emerged as a promising tool for supporting students' science problem solving. However, general-purpose chatbots (e.g., ChatGPT), which often provide direct, ready-made answers, may lead to students' cognitive offloading. Prior research has rarely focused on custom chatbots for facilitating students' science problem solving, nor has it examined how they differently influence problem-solving processes and performance compared to general-purpose chatbots. To address this gap, we developed a pedagogy-informed custom GAI chatbot grounded in the Socratic questioning method, which supports students by prompting them with guiding questions. This study employed a within-subjects counterbalanced design in which 48 secondary school students used both custom and general-purpose chatbot to complete two science problem-solving tasks. 3297 student-chatbot dialogues were collected and analyzed using Heterogeneous Interaction Network Analysis (HINA). The results showed that: (1) students demonstrated significantly higher interaction intensity and cognitive interaction diversity when using custom chatbot than using general-purpose chatbot; (2) students were more likely to follow custom chatbot's guidance to think and reflect, whereas they tended to request general-purpose chatbot to execute specific commands; and (3) no statistically significant difference was observed in students' problem-solving performance evaluated by solution quality between two chatbot conditions. This study provides novel theoretical insights and empirical evidence that custom chatbots are less likely to induce cognitive offloading and instead foster greater cognitive engagement compared to general-purpose chatbots. This study also offers insights into the design and integration of GAI chatbots in science education.
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