I design adaptive online modules or MOOClets which improve and personalize people’s education in complex real-world environments, by aligning tests of scientific hypotheses with practical improvements.
My work bridges human-computer interaction design of practical online technology – to enable students to learn, instructors to teach, and scientists to do research – with cognitive science behavioral experiments and applications of machine learning/AI for learning and high-level cognition.
Examples include increasing motivation and reflective problem-solving for students solving mathematics exercises on Khan Academy, strategies for self-questioning that enhance learning from videos in MOOCs, and digital tools that provide in-the-moment guidance to students in applying management concepts from courses to everyday interactions with people. You can contact me at joseph_jay_williams AT harvard DOT edu.
In this blend of scientific research and applications I collaborate and consult with domain/topic experts, instructors, designers, and researchers from diverse disciplines like education, psychology, and computer science. I draw on theories and methodology from research I have done, as well as synthesizing findings from other scientists, work on behavior change, 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, experience as an ed-tech consultant and science & technology advisor, and my own active development of interactive learning and behavior change resources.
I am currently a Research Fellow at HarvardX, the online learning research and development component of Harvard University. I also work closely with Neil Heffernan at WPI using the ASSISTments authoring and online mathematics exercise platform, leading the advisory board for an NSF Software Infrastructure grant that crowdsources randomized controlled trials from the broader scientific community.
I was previously a postdoc at Stanford University in the Graduate School of Education and Lytics Lab, working with the Office of the Vice Provost for Online Learning and Candace Thille's Open Learning Initiative. I received my PhD in Experimental and Computational Cognitive Science from UC Berkeley's Psychology Department. I worked with Tania Lombrozo to investigate why prompting people to explain "why?" helps learning, and with Tom Griffiths on using Bayesian statistics and methods from machine learning to characterize learning, reasoning, and judgment.