Projects

The OAK Lab studies how people learn, with the goal of building better learning technology. We investigate practice-first approaches, where students engage with problems before formal instruction, and translate those findings into adaptive learning tools tested at scale, from college classrooms to underserved regions like rural Uganda.

1. Learning Mechanisms: Practice, Feedback, and Discovery

We study the cognitive and motivational processes that drive learning, with a focus on how learners acquire knowledge through practice, feedback, and discovery rather than passive instruction. Using controlled experiments, we examine how learners infer abstract rules, regulate their learning, and retain knowledge over time—identifying when and why specific learning experiences lead to durable understanding.

Researchers: Michael Asher, Julia Conti, Gillian Gold

2. Intelligent and Adaptive Learning Systems

Building on these mechanisms, we develop precise computational models of learning and use them to design AI-driven systems that adapt to individual learners. This research integrates learning science, data analytics, and human-centered design to model knowledge, generate practice and feedback, and personalize learning experiences at scale.

Researchers: Yumou (James) Wei, Meng Cao, Gillian Gold, Jess Turner

3. Learning at Scale and Across Contexts

Taking these systems into the field, we translate cognitive and computational models into educational interventions that function in real classrooms and diverse learning contexts. This line of research examines how instructional designs and learning technologies perform at scale, across institutions, and across linguistic and cultural settings, with an emphasis on access, inclusion, and real-world impact.

Researchers: Phenyo Moletsane, Meng Cao, Michael Asher, Yumou (James) Wei