Context: As generative AI (GenAI) tools such as ChatGPT and GitHub Copilot become pervasive in education, concerns are rising about students using them to complete rather than learn from coursework-risking overreliance, reduced critical thinking, and long-term skill deficits. Objective: This paper proposes and empirically applies a causal model to help educators scaffold responsible GenAI use in Software Engineering (SE) education. The model identifies how professor actions, student factors, and GenAI tool characteristics influence students' usage of GenAI tools. Method: Using a design-based research approach, we applied the model in two contexts: (1) revising four extensive lab assignments of a final-year Software Testing course at Queen's University Belfast (QUB), and (2) embedding GenAI-related competencies into the curriculum of a newly developed SE BSc program at Azerbaijan Technical University (AzTU). Interventions included GenAI usage declarations, output validation tasks, peer-review of AI artifacts, and career-relevant messaging. Results: TBD Conclusions: TBD

翻译：背景：随着ChatGPT和GitHub Copilot等生成式人工智能（GenAI）工具在教育领域的普及，人们日益担忧学生可能利用这些工具直接完成课业而非从中学习——这可能导致过度依赖、批判性思维减弱以及长期技能缺失的风险。目标：本文提出并实证应用一个因果模型，以帮助教育工作者在软件工程（SE）教育中构建负责任的GenAI使用框架。该模型揭示了教授行为、学生因素及GenAI工具特性如何影响学生对GenAI工具的使用。方法：采用基于设计的研究方法，我们在两种情境中应用了该模型：（1）修订贝尔法斯特女王大学（QUB）软件测试课程四年级的四个综合性实验作业；（2）将GenAI相关能力嵌入阿塞拜疆技术大学（AzTU）新开设的软件工程学士学位课程体系。干预措施包括GenAI使用声明、输出验证任务、AI产出的同行评审以及与职业相关的引导信息。结果：待补充 结论：待补充