Chais2025_Heb_and_Eng-web

24E Examining AI-Focused Professional Development Challenges Proceedings of the 20th Chais Conference for the Study of Innovation and Learning Technologies: Learning in the Digital Era D. Olenik-Shemesh, I. Blau, N. Geri, A. Caspi, Y. Sidi, Y. Eshet-Alkalai, Y. Kalman, E. Rabin (Eds.), Ra'anana, Israel: The Open University of Israel "We Need More Than Tools": Examining AI-Focused Professional Development Challenges Through the DigCompEdu AI Supplement Framework Maayan Shay Sayag The Open University of Israel maayan.sayag@gmail.com Ina Blau The Open University of Israel inabl@openu.ac.il Orit Avidov-Ungar Achva Academic College The Open University of Israel avidovo@achva.ac.il " אנחנו צריכים יותר מכלים": בחינת ה אתגרים ב פיתוח מקצועי ממוקד בינה מלאכותית באמצעות מודל DigCompEdu AI Supplement אורית אבידב - אונגר המכללה האקדמית אחוה האוניברסיטה הפתוחה avidovo@achva.ac.il אינה בלאו האוניברסיטה הפתוחה inabl@openu.ac.il מעיין שי סייג האוניברסיטה הפתוחה maayan.sayag@gmail.com Abstract This study investigates the challenges that emerge in AI-focused teacher professional development (TPD) programs and their impact on teachers' AI competency development within the DigCompEdu AI Supplement framework. Utilizing semi- structured interviews with 22 high school teachers in Israel who participated in an entry-level AI-focused TPD program in their subject teaching area, the research identifies key themes affecting competency development: content-related barriers, critical content gaps, and operational challenges. Findings reveal that technical limitations, lack of subject-specific relevance, insufficient guidance on assessment practices and ethical considerations, and inadequate program structure hinder successful AI integration in teaching. The study proposes three significant modifications to the DigCompEdu AI Supplement framework: expanding existing assessment-related challenges to reflect developmental stages of AI integration, adding a new challenge category under Assessment for "Ensuring Authenticity and Originality of Students' Work", and introducing a new challenge category under Professional Engagement for "Differentiated Professional Development." These modifications address both theoretical gaps in the framework and practical needs in AI-focused TPD implementation. The results emphasize the importance of a staged approach to AI integration, beginning with fundamental challenges before advancing to more sophisticated applications, while underscoring the need for differentiated learning paths, greater emphasis on ethics and assessment, appropriate program timing and structure, and subject-specific content in TPD programs. These insights advance both the theoretical understanding of AI integration challenges and inform the development of more effective TPD programs that align with teachers' actual needs and readiness levels.