Joseph Jay Williams
Joseph Jay Williams
University of Toronto (CS:HCI + applied AI/ML, Stats, Psych, Education, Econ)
Verified email at - Homepage
Cited by
Cited by
HarvardX and MITx: Two years of open online courses fall 2012-summer 2014
A Ho, I Chuang, J Reich, C Coleman, J Whitehill, C Northcutt, J Williams, ...
Available at SSRN 2586847, 2015
The role of explanation in discovery and generalization: Evidence from category learning
JJ Williams, T Lombrozo
Cognitive science 34 (5), 776-806, 2010
Mining big data in education: Affordances and challenges
C Fischer, ZA Pardos, RS Baker, JJ Williams, P Smyth, R Yu, S Slater, ...
Review of Research in Education 44 (1), 130-160, 2020
Axis: Generating explanations at scale with learnersourcing and machine learning
JJ Williams, J Kim, A Rafferty, S Maldonado, KZ Gajos, WS Lasecki, ...
Proceedings of the Third (2016) ACM Conference on Learning@ Scale, 379-388, 2016
A playful game changer: Fostering student retention in online education with social gamification
M Krause, M Mogalle, H Pohl, JJ Williams
Proceedings of the Second (2015) ACM conference on Learning@ Scale, 95-102, 2015
Explanation and prior knowledge interact to guide learning
JJ Williams, T Lombrozo
Cognitive psychology 66 (1), 55-84, 2013
Improving outcome of psychosocial treatments by enhancing memory and learning
AG Harvey, J Lee, J Williams, SD Hollon, MP Walker, MA Thompson, ...
Perspectives on Psychological Science 9 (2), 161-179, 2014
Beyond prediction: First steps toward automatic intervention in MOOC student stopout
J Whitehill, J Williams, G Lopez, C Coleman, J Reich
Available at SSRN 2611750, 2015
Scaling up behavioral science interventions in online education
RF Kizilcec, J Reich, M Yeomans, C Dann, E Brunskill, G Lopez, S Turkay, ...
Proceedings of the National Academy of Sciences 117 (26), 14900-14905, 2020
A rational model of function learning
CG Lucas, TL Griffiths, JJ Williams, ML Kalish
Psychonomic bulletin & review 22 (5), 1193-1215, 2015
The hazards of explanation: Overgeneralization in the face of exceptions.
JJ Williams, T Lombrozo, B Rehder
Journal of Experimental Psychology: General 142 (4), 1006, 2013
Modeling human function learning with Gaussian processes
T Griffiths, C Lucas, J Williams, M Kalish
Advances in neural information processing systems 21, 2008
Explaining constrains causal learning in childhood
CM Walker, T Lombrozo, JJ Williams, AN Rafferty, A Gopnik
Child development 88 (1), 229-246, 2017
The future of adaptive learning: does the crowd hold the key?
NT Heffernan, KS Ostrow, K Kelly, D Selent, EG Van Inwegen, X Xiong, ...
International Journal of Artificial Intelligence in Education 26, 615-644, 2016
RiPPLE: A crowdsourced adaptive platform for recommendation of learning activities
H Khosravi, K Kitto, JJ Williams
arXiv preprint arXiv:1910.05522, 2019
Understanding the effect of in-video prompting on learners and instructors
H Shin, EY Ko, JJ Williams, J Kim
Proceedings of the 2018 CHI conference on human factors in computing systems …, 2018
mHealth app using machine learning to increase physical activity in diabetes and depression: clinical trial protocol for the DIAMANTE Study
A Aguilera, CA Figueroa, R Hernandez-Ramos, U Sarkar, A Cemballi, ...
BMJ open 10 (8), e034723, 2020
Why are people bad at detecting randomness? A statistical argument.
JJ Williams, TL Griffiths
Journal of experimental psychology: learning, memory, and cognition 39 (5), 1473, 2013
Evaluating computational models of explanation using human judgments
M Pacer, J Williams, X Chen, T Lombrozo, T Griffiths
arXiv preprint arXiv:1309.6855, 2013
Beyond time-on-task: The relationship between spaced study and certification in MOOCs
Y Miyamoto, C Coleman, J Williams, J Whitehill, S Nesterko, J Reich
Available at SSRN 2547799, 2015
The system can't perform the operation now. Try again later.
Articles 1–20