Tutoring is one of the most consistently effective educational interventions, with high-dosage models showing especially strong results. Yet the field still lacks a systematic understanding of why tutoring works—particularly which instructional moves drive learning. The emerging area of “teacher move analytics” addresses this gap by analyzing discourse, feedback, and interaction patterns. Advances in NLP, multimodal analytics, and AI-assisted annotation make large-scale analysis possible, but progress is hindered by fragmented data, high annotation costs, and privacy concerns. 

The National Tutoring Observatory (NTO) offers a unifying infrastructure to overcome these barriers—enabling systematic analysis of tutoring, predictive and causal models of effectiveness, and the design of human–AI tutoring systems. By convening the LAK community, this workshop will help advance a shared agenda for uncovering the instructional moves that make tutoring and teaching instruction effective.

We encourage paper submissions related to:

• Examples of Methods and Implementations of AI Annotation in Learning Analytics Contexts

• Research on Understanding Teaching Behaviors and Practices in Authentic Learning Environments

Submission Guidelines

The workshop will feature presentations of selected papers alongside guided discussion sessions. We invite submissions of up to six pages in length that align with the workshop’s central themes, following the formatting requirements outlined in the conference proceedings. All submissions will undergo a single-blind review process, where authors are identified but reviewers remain anonymous. Reviewers will assess each paper on three criteria—relevance to the workshop’s themes, level of interest to the LAK community, and overall scholarly quality—using a three-point scale (-1, 0, 1). Based on these evaluations, reviewers will recommend acceptance or rejection and justify their decisions. Authors of accepted papers will be asked to present their work during the workshop. The call for papers timeline and details will be released once the workshop has been formally accepted.

Contact

All questions about submissions should be emailed to Kirk Vanacore -- kpv27@cornell.edu