Using AI-based chatbots for individualized teacher professional development: An empirical study of the in- service training programme at the University College of Teacher Education Burgenland

This research paper investigates the potential of AI-based chatbots to support teachers in identifying professional development (PD) opportunities tailored to subject-specific, pedagogical, and technological requirements. Drawing on the Technological, Pedagogical, and Content Knowledge (TPACK) framework, Self-Determination Theory (SDT), and reflexivity, we conducted a six-week field study with 1,125 teachers at the University College of Teacher Education Burgenland (Austria). A mixed-methods design was employed, integrating quantitative approaches (logistic regression, correlation) and qualitative techniques (content and sentiment analysis) to capture the breadth and depth of teacher–chatbot interactions. Results show a moderate positive correlation (ρ = 0.36, p < 0.05) between the specificity of user queries and user satisfaction, while targeted keywords (e.g., “digital didactics”) increased the likelihood of positive feedback by a factor of 2.05 (p < 0.01). Qualitative findings reveal that teachers have a pronounced interest in digital competencies, artificial intelligence, and inclusion, with 85% of user feedback on chatbot performance being positive. These findings suggest that AI-based chatbots can facilitate a more individualized, context-sensitive search for PD opportunities, thereby promoting teacher autonomy, competence, and relatedness. The paper discusses methodological and practical implications in the context of the EDEN Digital Learning Europe Annual Conference 2025 theme, “Empowering Inclusion, Innovation and Ethical Growth,” highlighting how AI-enabled PD tools align with broader European policy initiatives.