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.

翻译：问题解决在科学教育中具有核心地位，生成式人工智能（GAI）聊天机器人已成为支持学生科学问题解决的重要工具。然而，通用型聊天机器人（如ChatGPT）常直接提供现成答案，可能导致学生认知卸载。现有研究鲜少关注面向科学问题解决的定制化聊天机器人，亦未系统比较其与通用型聊天机器人在问题解决过程与表现上的差异性影响。为填补这一研究空白，我们基于苏格拉底式提问法开发了教学启发式定制GAI聊天机器人，通过引导性问题支持学生思考。本研究采用被试内平衡设计，48名中学生分别使用定制与通用聊天机器人完成两项科学问题解决任务，收集3297组学生-机器人对话数据并运用异质互动网络分析（HINA）进行解析。结果表明：（1）使用定制聊天机器人时，学生的交互强度与认知交互多样性显著高于使用通用聊天机器人；（2）学生更倾向于遵循定制聊天机器人的引导进行思考与反思，而更倾向于要求通用聊天机器人执行具体指令；（3）在解决方案质量这一表现指标上，两种聊天机器人条件未存在统计显著差异。本研究从理论上揭示：相较通用聊天机器人，定制聊天机器人不易引发认知卸载，反而能激发更高水平的认知投入，并为科学教育中GAI聊天机器人的设计与整合提供了实证依据。