E86 Can Generative AI Mentor Pre-Service Teachers? (short paper) Proceedings of the 21st Chais Conference for the Study of Innovation and Learning Technologies: Learning in the Digital Era I. Blau, A. Caspi, Y. Eshet-Alkalai, N. Geri, Y. Kalman, D. Olenik-Shemesh, Y. Sidi, & N. Brandel (Eds.), Ra'anana, Israel: The Open University of Israel Can generative AI mentor Pre-Service teachers? Exploring a chatbot led cognitive apprenticeship-based discourse (short paper) Yogev Shani Tel Aviv University yogevshani@mail.tau.ac.il Idit Adler Tel Aviv University iditadler@tauex.tau.ac.il האם בינה מלאכותית יוצרת יכולה לחנוך פרחי הוראה? בחינת שיח מבוסס מודל חניכה קוגניטיבית המונחה על ידי צ'אטבוט )מאמר קצר( עידית אדלר אוניברסיטת תל אביב iditadler@tauex.tau.ac.il יוגב שני אוניברסיטת תל אביב yogevshani@mail.tau.ac.il Abstract This study examined the discourse between pre-service teachers (PSTs) and TeachPal, a Generative Artificial Intelligence (GenAI)-based chatbot designed to foster reflection and self-regulated learning within the Cognitive Apprenticeship Model framework. TeachPal was implemented in a simulation-based course combining in-class instruction and collaborative simulated scenario tasks. Using discourse analysis, we analyzed 60 chatbot-led interactions between TeachPal and 15 PSTs to characterize both PSTs’ and TeachPal’s contributions to reflective dialogue. Results show that TeachPal successfully prompted PSTs to reflect on their instructional practices but struggled to sustain meaningful, non-repetitive discourse, limiting the depth of reflection and engagement. PSTs rarely initiated or elaborated on TeachPal’s feedback, while TeachPal’s responses were often generic or overly affirming. These findings reveal both the potential and current limitations of GenAI-based mentoring in teacher education and highlight the need for more structured, less repetitive PST-GenAI discourse to fully leverage its capacity for supporting reflective professional learning. Keywords: Cognitive Apprenticeship Model, Discourse Analysis, Generative Artificial Intelligence, Pre-service teachers, Self-regulated learning. Introduction and theoretical background Supporting pre-service teachers (PSTs) in fostering their students’ self-regulated learning (SRL), the active, constructive process whereby learners set goals for their learning and then attempt to monitor, regulate, and control their cognition, motivation, and behavior (Pintrich, 2000, p. 453), is a central challenge. This goal can be achieved through the Cognitive Apprenticeship Model (CAM), an
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