Visual Arts Teacher Candidates’ AI-Supported Visual Arts Lesson Plan Practices and Views

This study aims to examine teacher candidates’ views on AI-supported art teaching practices and to analyze a sample of lesson plans related to these practices. The research was designed as a case study. The participants were selected through criterion sampling, one of the purposive sampling methods. In this context, 21 pre-service visual arts teachers were included as participants. The data were collected through semi-structured interview forms, documents (lesson plans), AI-supported artistic products, and related outputs. The research data were analyzed using descriptive analysis. Within this framework, four themes were identified: “AI Tools and Application Experience,” “AI-Supported Lesson Plans and Practices,” “The Contribution of AI Tools to Art Education,” and “Implementation Process and Teacher Candidates’ Views.” The findings reveal that teacher candidates used a variety of AI tools in their lesson plans and practices, including Midjourney, Gencraft, Stability.AI, AR Drawing Sketch, Add Animation, Tensor.art, AR Real Animals, Adobe Firefly, and several AI-based mobile applications. The results indicate that teacher candidates gained various pedagogical benefits during the implementation of their lesson plans in classroom settings. Specifically, they employed AI tools to guide the learning process, structured activities to support permanent learning, and ensured a balanced integration of traditional methods with AI. AI-based lesson plans and practices not only enriched students’ learning experiences but also emerged as a significant instrument for enhancing teacher candidates’ pedagogical and technological competencies.