Joseph Jay Williams is a researcher and consultant in cognitive science and online education. His academic work consists of cognitive science research to understand how people learn â€“ through experiments or A/B tests, construction of assessments, and statistical modeling. His practical work consists of consulting to improve and evaluate learning from online educational resources â€“ like EdX videos, K-12 text lessons and Khan Academy's interactive math exercises.
In blending scientific research and applications he draws on theories and methodology from research he has done, his synthesis of scientific findings from cognitive science, education, and behavior change research, reviews of evidence-based best practices for teaching and learning, practical experience as a statistics tutor, evaluations of educational technology products & authoring tools for e-learning, and experience as a science and technology mentor for startups in a Haas Business School entrepreneurship class.
He is currently at Stanford University in the Lytics Lab, Office of the Vice-Provost of Online Learning, and Graduate School of Education. He received his PhD from UC Berkeley's Psychology Department in Experimental and Computational Cognitive Science. He worked with Tania Lombrozo on laboratory experiments that investigated why prompting people to explain "why?" promotes their learning, and proposing the novel Subsumptive Constraints Account of explanation and learning. He worked with Tom Griffiths on using Bayesian statistics and methods from machine learning to develop probabilistic models of how people make judgments about randomness and explanation, and learn about causes, categories, and functions.