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Joseph Jay Williams
Joseph Jay Williams
University of Toronto (CS:HCI + applied AI/ML, Stats, Psych, Education, Econ)
Dirección de correo verificada de cs.toronto.edu - Página principal
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HarvardX and MITx: Two years of open online courses fall 2012-summer 2014
AD Ho, I Chuang, J Reich, CA Coleman, J Whitehill, CG Northcutt, ...
MIT Office of Digital Learning; HarvardX Research Committee, 2015
7332015
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
4262020
The role of explanation in discovery and generalization: Evidence from category learning
JJ Williams, T Lombrozo
Cognitive science 34 (5), 776-806, 2010
2802010
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
2212016
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
2002020
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
1972015
Explanation and prior knowledge interact to guide learning
JJ Williams, T Lombrozo
Cognitive psychology 66 (1), 55-84, 2013
1672013
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
1572014
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
1432015
A rational model of function learning
CG Lucas, TL Griffiths, JJ Williams, ML Kalish
Psychonomic bulletin & review 22 (5), 1193-1215, 2015
1382015
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
1292013
Ripple: A crowdsourced adaptive platform for recommendation of learning activities
H Khosravi, K Kitto, JJ Williams
arXiv preprint arXiv:1910.05522, 2019
932019
Explaining constrains causal learning in childhood
CM Walker, T Lombrozo, JJ Williams, AN Rafferty, A Gopnik
Child development 88 (1), 229-246, 2017
932017
Modeling human function learning with Gaussian processes
T Griffiths, C Lucas, J Williams, M Kalish
Advances in neural information processing systems 21, 2008
882008
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
832020
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
802016
Bandit algorithms to personalize educational chatbots
W Cai, J Grossman, ZJ Lin, H Sheng, JTZ Wei, JJ Williams, S Goel
Machine Learning 110 (9), 2389-2418, 2021
69*2021
The impact of adding textual explanations to next-step hints in a novice programming environment
S Marwan, N Lytle, JJ Williams, T Price
Proceedings of the 2019 ACM conference on innovation and technology in …, 2019
552019
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
512018
Evaluating computational models of explanation using human judgments
M Pacer, J Williams, X Chen, T Lombrozo, T Griffiths
arXiv preprint arXiv:1309.6855, 2013
502013
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Artículos 1–20