Chais2025_Heb_and_Eng-web

30E Examining AI-Focused Professional Development Challenges integration, such as using AI for grading and data analysis. However, our findings reveal that teachers face more immediate and fundamental challenges that are not addressed in the current framework. This suggests the need to expand these existing categories to reflect different stages of AI integration, from basic implementation to advanced applications. Moreover, the findings suggest the need for a new challenge category under Assessment : " Ensuring Authenticity and Originality of Students' Work ". This prominent challenge, which includes developing strategies to identify AI-generated work and creating appropriate assessment methods for an AI-enabled environment, represents a distinct concern that is currently absent from the framework's categories (Langran et al., 2024; UNESCO, 2023). The second gap centered on insufficient ethical guidance, leaving teachers without a clear understanding of AI-specific privacy concerns and ethical implications. This aligns with recent literature emphasizing the need for comprehensive AI literacy among educators that goes beyond technical skills to include ethical considerations (UNESCO, 2023). The absence of structured ethical guidelines left teachers equating AI-related challenges with general technology issues, highlighting a critical gap in current TPD programs. Finally, teachers emphasized the lack of pedagogical guidelines for classroom implementation. While they gained familiarity with various AI tools, they lacked concrete strategies for meaningful integration into their teaching practices. This gap was particularly evident in their struggle to move beyond surface-level applications to develop pedagogically sound, subject- specific implementations, echoing findings about the challenges teachers face in translating theoretical knowledge into effective teaching practices (Ding et al., 2024; Kong & Yang, 2024). Theme 3: Operational Challenges in TPD Structure and Timing Analysis of teachers' experiences revealed significant operational challenges that hindered their AI competency development in the TPD program. These challenges centered around three main areas: group size and participant heterogeneity , limited depth and focus on training content , and TPD structure, duration, and timing . The findings highlighted a critical gap in the DigCompEdu AI Supplement regarding differentiated professional development , specifically, the need to address varying technical proficiencies, learning paces, and professional needs within AI-focused TPD programs. Table 3 presents representative quotes illustrating these operational challenges and their mapping to the framework competency areas. Table 3. Operational Challenges in TPD Structure and Timing (n=63) DigCompEdu AI Supplement Challenges Representative Quote Sub-category 3.1: Group Size and Participant Heterogeneity (n=24) Professional Engagement: • Differentiated Professional Development Digital Resources: • Teachers’ Preparedness and Training "The group was too heterogeneous - from tech experts to complete beginners like me." (T3) "With 60 people at different levels discussing different topics, from technical issues to curriculum, it was really challenging." (T16)