The rise of generative AI (GenAI) tools is profoundly reshaping higher education, particularly in engineering disciplines. This technological shift raises pressing questions about institutional policy (what uses of GenAI should be permitted or guided), curriculum design (how to integrate GenAI literacy), and pedagogy (how to teach meaningfully in the presence of these tools).

The dominant institutional response to these challenges tends to be top-down: expert committees of faculty members produce guidelines and recommendations, often without substantial input from students or the workplace. While well-intentioned, this unilateral approach risks overlooking the perspectives of those most directly affected by the changes—especially students—and those who will employ our graduates—the workplace.

In this presentation, I propose and illustrate a more participatory, action-oriented model of curriculum research. At the heart of this approach is the active involvement of students as co-researchers. In one course, for example, industrial engineering students collaborate with the teacher in exploring the role of GenAI in the workplace through a survey and interviews. Students critically reflect on their findings and formulate recommendations for how GenAI competencies could be meaningfully embedded into their curriculum. As they write their research papers, we also explore, hands-on, how GenAI tools can support their academic work—jointly discovering strengths, limitations, and ethical pitfalls.

This collaborative model equips students with GenAI literacy and encourages them to participate meaningfully in rethinking their education. By engaging students and external stakeholders as partners in curriculum development, we move toward a more adaptive, inclusive, and context-sensitive response to the challenges of GenAI in higher education.

Keywords: Technology, generative Artificial Intelligence, curriculum development, action research.