#491: Human–AI Learning Alignment in Situated Contexts: A Human-Centered Framework

As generative artificial intelligence (AI) transforms education, many existing approaches to AI in education emphasize task completion while overlooking learner agency and the sociotechnical nature of learning. This gap limits our ability to understand how AI supports learning in situated contexts. In this paper, we define human–AI learning alignment and present TEACH-AI (Trustworthy and Effective AI Classroom Heuristics) as a learner-centered set of analytical dimensions spanning interactional, learning-oriented, and sociotechnical perspectives. Through an illustrative case analysis, we discuss how this perspective can be used to analyze AI-supported learning settings. This work contributes a conceptual foundation for understanding how generative AI supports learning in situated contexts.