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Generative Artificial Intelligence (GenAI) is shifting the types and uses of computing tools in classrooms, necessitating study of how and what decisions are made about the use of AI in courses. All teachers will need to understand and be able to make important choices about GenAI for their learners. In this project, 25 teacher educators took an AI professional development course, and this paper describes their reflections and final projects. Participants at two large southeastern universities represented teacher preparation programs across all grade bands and disciplines. The shared practices the teacher educators used revealed ways GenAI can be a tool to support, not replace, a teacher. Limitations of GenAI applications are also discussed. The inclusion of all teacher educators in the project, and not just “faculty”, enabled more participation, along with the flexible timing of the online course, and personalization of the final project. 

This study explored the dynamics and key factors influencing the development of computer science education (CSEd) pathways in teacher preparation at 10 higher education institutions in the United States. Through cross-case analysis, the findings highlighted that personal commitment and leadership from CSEd champions played a key role in initiating and maintaining CSEd efforts. Other factors acted as a double-edged sword, serving as enablers in some cases and barriers in others. These factors include funding sustainability, stakeholder buy-in, and state-level policies, which could support or complicate CSEd implementation depending on their flexibility and alignment with institutional needs. The study concluded that successful CSEd pathway development requires multifaceted, holistic consideration, balancing leadership, institutional support, and systemic alignment. These insights offered valuable guidance for teacher educators, policymakers, and institutions aiming to expand CS teacher capacity for equitable K–12 computing education.