Chais2025_Heb_and_Eng-web

26E Examining AI-Focused Professional Development Challenges absent is a comprehensive examination of the challenges that emerge in AI-focused TPD programs and their impact on teachers' AI competency development through systematic theoretical frameworks, such as the recently developed DigCompEdu AI Supplement. This study addresses this gap by investigating the specific challenges that emerge in AI- focused TPD programs and their effect on teachers' AI competency development through the lens of the DigCompEdu AI Supplement. The study explored the following research question : What challenges emerge in AI-focused TPD programs that affect the development of teachers' AI competencies as conceptualized in the DigCompEdu AI Supplement? Methodology This qualitative study utilized semi-structured interviews to examine teachers' experiences in an AI-focused TPD program. This approach was chosen for its ability to provide an in-depth understanding of teachers' experiences and the complexities of developing AI competencies in educational settings (Creswell & Poth, 2018). Participants and Context This study examined an entry-level AI-focused TPD program conducted by the Israeli Ministry of Education's Pedagogical Secretariat. The program was implemented through multiple parallel courses across various subject areas. While based on a generic curriculum designed by educational technology and AI integration experts, each course was adapted by subject-area instructors (experienced teachers and pedagogical mentors) to meet the specific needs of different disciplines. Course sizes varied, ranging from approximately 30 to 60 participants per subject area, with hundreds of teachers participating across all courses. Each course comprised 30 hours of instruction delivered through both synchronous and asynchronous sessions. The curriculum covered fundamental GenAI concepts, text-to-text and text-to-image tools, GenAI applications in educational design software, and subject-specific implementations, emphasizing responsible AI use in education. The participants completed the program during spring-summer 2024. From this broader sample, 22 high-school teachers were selected for in-depth interviews using purposive sampling to ensure representation across different disciplines (sciences, humanities, and social sciences). The participants represented varied career stages: early career (0-5 years, n=5), middle career (6-12 years, n=7), and late career (13 or more years, n=10). Many held additional leadership roles within their schools, such as subject-matter or pedagogical coordinators. The sample also represented various geographic regions across Israel and different socioeconomic contexts, with teachers working in schools classified as high (n=9), medium-high (n=9), and medium-low (n=5) socioeconomic status. While a few participants had limited initial experience with AI tools, for the vast majority this TPD program served as their entry point into AI integration in education. Research Tools and Procedure Semi-structured interviews were conducted via Zoom videoconferencing within three weeks of program completion. The interviews, lasting 40-60 minutes, explored participants' experiences with the TPD program, development of AI competencies, and their implementation attempts. Data analysis followed a hybrid approach combining inductive and deductive thematic analysis (Fereday &Muir-Cochrane, 2006). Initial inductive analysis followed Braun and Clarke's (2006) six-phase method, identifying emerging themes related to challenges in AI-focused TPD. This was followed by deductive analysis using the DigCompEdu AI Supplement framework