Chais2025_Heb_and_Eng-web

Maayan Shay Sayag, Ina Blau, Orit Avidov-Ungar 27E (Bekiaridis & Attwell, 2024) to categorize challenges within the framework's competency areas. The unit of analysis was a statement (rather than a participant). The coding was not exclusive, allowing for mapping of challenges across multiple framework categories when relevant. To ensure inter-rater reliability, 20% of the data was independently analyzed by a second rater, with Cohen's Kappa coefficient of 0.73 indicating substantial agreement between raters. Findings and Discussion This study examines the challenges that emerge in AI-focused TPD programs through the lens of the DigCompEdu AI Supplement (Bekiaridis & Attwell, 2024), which specifically addresses educators' AI competencies. Analysis of the interview data yielded 338 unique statements that were categorized into three major themes: content-related barriers (49.1%, n=166), critical content gaps (32.2%, n=109), and operational challenges (18.6%, n=63). While most statements were coded to a single category, some challenges exhibited interconnections, particularly within operational challenges where aspects of group size, depth of content, and program structure frequently co-occurred. Each theme is analyzed in relation to the framework's designated challenge categories, highlighting how these obstacles manifest across different competencies and impact teachers' ability to effectively integrate AI in their professional practice. Theme 1: Content-Related Barriers in AI-Focused TPD Analysis of teachers' experiences revealed that the learning content in AI-focused TPD - specifically the AI tools introduced and their potential applications both generally and within specific subject areas - significantly affected their AI competency development. Two distinct but interrelated challenges emerged: Tools Limitations and Usage Barriers , and Perceived Lack of Value and Relevance Barriers . These challenges align with multiple categories in the DigCompEdu AI Supplement, particularly within Digital Resources and Teaching & Learning domains. Table 1 presents representative quotes illustrating these content challenges and their mapping to the competency areas. Table 1. Content-Related Barriers in AI-Focused TPD (n=166) DigCompEdu AI Supplement Challenges Representative Quote Sub-category 1.1: Tools Limitations & Usage Barriers (n=114) Digital Resources: • Technical Limitations and Reliability • Quality and Relevance of AI- Driven Content • Teacher Preparedness and Training Teaching & Learning: • Quality and Relevance of AI- Driven Content "I tried asking the chat to find another enzyme with a simpler measurement method... all the expected results were completely wrong." (T5) "Adapting it for civics can create much more work in lesson preparation than even relying on Google itself, mainly because the subject is very specific to Israel." (T22) "It couldn't create a proper pie chart - even for simple numbers like 30 versus 5 people. It's too much investment for something a child could easily understand." (T15)