Kolejnym gościem seminarium PAN-Metrics był prof. Okan Bulut (University of Alberta), który wygłosił prezentację pt. AI in Dialogue: The Promise and Practice of Chatbots in Teacher Professional Development.
Materiały z tego wystąpienia są dostępne tutaj.
Poniżej prezentujemy również sylwetkę prof. Okana Buluta, jak również abstrakt wystąpienia.
Abstrakt:
The increasing availability of conversational agents has created new opportunities for teacher professional development (PD). In a recent review study, we examined how chatbots have been used in the literature to support teacher training and ongoing development, and how these interventions have been evaluated. Specifically, we focus on two main questions: (a) What are the primary ways chatbots support teacher learning and development interventions? and (b) how are these chatbot-supported training programs assessed? In this talk, I will summarize our findings from existing research, highlighting the various roles chatbots play in providing access to resources, modeling best practices, and offering personalized feedback for teachers. We also identify common evaluation frameworks used to measure their effectiveness, from self- reported perceptions of usefulness to more formal measures of learning outcomes. The talk will conclude by exploring the untapped potential of chatbots to improve teachers’ assessment literacy, an essential area for effective classroom practice that is often underrepresented in traditional PD models.
Biogram:
Okan Bulut, Professor in the Measurement, Evaluation, and Data Science program and a researcher at the Centre for Research in Applied Measurement and Evaluation at the University of Alberta. He teaches courses on computational psychometrics, machine learning, and statistical modeling. He also regularly offers workshops and online courses on data mining, big data modeling, data visualization, and statistical analysis using R, SAS, and Python. His research focuses on the intersection of artificial intelligence (AI), learning analytics, and educational data mining. In particular, he applies AI-driven algorithms and natural language processing to extract insights from complex educational data and to develop personalized assessment and learning tools.