Encouraging responsible GenAI use in software engineering education: A design-oriented model
Vəhid Gəruslu, Zafar Jafarov, Aytan Movsumova, Atif Namazov, Huseyn Mirzayev · Journal of Systems and Software · 2026
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. This paper proposes a design-oriented conceptual model (named Guide-AI-Ed ) to support instructors in reasoning about how course and curriculum design choices may encourage responsible GenAI use in software engineering education. Using a design-based research approach, we applied the Guide-AI-Ed 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. In the course-level case, instructor observations and student artifacts indicated increased critical engagement with GenAI, reduced passive reliance, and improved awareness of validation practices. In the curriculum-level case, the model guided integration of GenAI learning outcomes across multiple modules and levels, enabling longitudinal scaffolding of AI literacy. The Guide-AI-Ed model has served as both a design scaffold and a reflection tool. It has helped us align GenAI-related pedagogy with SE education goals. It can offer a transferable approach to align GenAI integration with SEEd goals and can support broader curriculum innovation in response to rapidly evolving GenAI capabilities.