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Recent advances in artificial intelligence (AI) have significantly expanded the possibilities for educational research, especially in analyzing complex social interactions within classroom environments more efficiently. In my talk, I focus on AI-based approaches for classifying teachers’ verbal and nonverbal behaviors. Specifically, I highlight the use of computer vision techniques to analyze nonverbal immediacy, and the application of large language models (LLMs) to assess motivational messages delivered by teachers. I will also discuss the potential and limitations of these AI-driven methods, along with their ethical implications and relevance for educational practice. The talk provides an overview of our research conducted at the Science of Intelligence research center (2019–2025; www.scienceofintelligence.de) as well as ongoing work in my research group, Research on Instruction and Schools, at the University of Potsdam, within the new DFG-funded project Motivate! (www.uni-potsdam.de/en/dfg-projekt-motiv)
