A Generative AI–Supported Production-Based Teacher Education Study: “Twice-Exceptional Digital Stories”

This study examines pre-service teachers’ processes of producing digital stories themed around twice-exceptional (2e) students using GenAI tools and the quality of the products that emerged in this process. Designed as a case study within qualitative research designs, the study was conducted with 54 third-year pre-service teachers studying at a faculty of education. During the seven-week production process, the pre-service teachers conducted a GenAI-supported literature review, created a story draft, wrote a script, prepared a storyboard, generated 3D visuals and animations, produced audio elements, and combined all components to obtain digital stories in video format lasting 60–120 seconds. The quality of the digital stories was evaluated by three experts using the “Graded Assessment Scale for Digital Stories.” It was determined that there was a high level of agreement among the experts and that the quality of the digital stories was high. Qualitative data regarding the pre-service teachers’ production process were collected through focus group interviews and analyzed using content analysis. As a result of the content analysis, four themes and fifteen categories were identified: “Emotional Experience Related to the Process,” “Technical and GenAI-Related Problems,” “Collaboration and Production Organization,” and “Learning Outcomes and Awareness Development.” The GenAI-supported production process contributed to shaping pre-service teachers’ pedagogical representations of 2e students within a strength-based and inclusive perspective. The technical challenges and problems experienced during the process, as well as difficulties in establishing and managing collaboration, provide important insights for production-based teacher education practices.