Human Teacher

Research on human teachers is exploring how humans teach effectively, particularly in novel contexts like robot training and online education. Current work focuses on understanding the dynamics of human teaching, including how teachers adapt to student or robot errors and how to leverage AI to enhance teaching effectiveness, often employing large language models (LLMs) and Bayesian methods to personalize instruction and provide feedback. This research aims to improve learning outcomes across various domains by optimizing teaching strategies and developing AI tools that complement, rather than replace, human instructors, ultimately impacting educational practices and human-robot interaction.