AI RESEARCH

Tutor Move Taxonomy: A Theory-Aligned Framework for Analyzing Instructional Moves in Tutoring

arXiv CS.CL

ArXi:2603.05778v1 Announce Type: new Understanding what makes tutoring effective requires methods for systematically analyzing tutors' instructional actions during learning interactions. This paper presents a tutor move taxonomy designed to large-scale analysis of tutoring dialogue within the National Tutoring Observatory. The taxonomy provides a structured annotation framework for labeling tutors' instructional moves during one-on-one tutoring sessions. We developed the taxonomy through a hybrid deductive-inductive process.