Advancing the Science of Human and AI Tutoring through Shared Infrastructure: A Collaborative Workshop

High-quality tutoring is among the most impactful instructional interventions in education. However, these programs remain difficult to scale effectively, and the specific “moves” underlying quality tutoring are understudied due to historical data scarcity. Despite extensive research, progress is hindered by challenges in data de-identification, multimodal analysis, and the predictive modeling of student outcomes. The emergence of Artificial Intelligence is fundamentally shifting the capacity to scale and study tutoring, offering transformative potential alongside significant pitfalls. This workshop, led by the National Tutoring Observatory, the SCALE Initiative, and the LEVI HAT project, brings together researchers, providers, and practitioners to explore human and AI tutoring systems. Featuring sessions on open-source data, infrastructure benchmarks, and synthetic students, the workshop aims to foster collaboration that ensures the future of instruction is grounded in rigorous empirical science.