The integration of generative AI (GenAI) in teaching and learning both is creating opportunities but also introducing significant risks concerning academic integrity, data privacy, and metacognitive development. Although institutional guidelines and GenAI literacy frameworks are providing some coherence, challenges remain in ensuring their adaptability across diverse stakeholders, contexts, and educational domains. My doctoral research examines current mental models of students and educators related to GenAI with the goal of co-designing a framework that accommodates diverse stakeholder perspectives and leads to effective integration of GenAI in technology education. Through a three-phase mixed-methods design, the study addresses three questions: What are the current mental models of GenAI use among students and educators in technology education? What external, institutional, experiential, and contextual factors influence mental model formation across the stakeholder groups? How can participatory co-design approaches bridge divergent mental models to develop an effective GenAI use frameworks? By addressing the research questions, my work will extend the current empirical literature on use of GenAI and lead to a practical and ethically grounded GenAI use framework for technology education.