Zachary A. Pardos
Zachary A. Pardos
Associate Professor at UC Berkeley
Verified email at - Homepage
Cited by
Cited by
Modeling individualization in a bayesian networks implementation of knowledge tracing
ZA Pardos, NT Heffernan
User Modeling, Adaptation, and Personalization: 18th International …, 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
KT-IDEM: Introducing item difficulty to the knowledge tracing model
ZA Pardos, NT Heffernan
User Modeling, Adaption and Personalization: 19th International Conference …, 2011
Affective States and State Tests: Investigating How Affect and Engagement during the School Year Predict End-of-Year Learning Outcomes.
ZA Pardos, RSJD Baker, MOCZ San Pedro, SM Gowda, SM Gowda
Journal of Learning Analytics 1 (1), 107-128, 2014
Affective states and state tests: Investigating how affect throughout the school year predicts end of year learning outcomes
ZA Pardos, RSJD Baker, MOCZ San Pedro, SM Gowda, SM Gowda
Proceedings of the third international conference on learning analytics and …, 2013
Data mining and education
KR Koedinger, S D'Mello, EA McLaughlin, ZA Pardos, CP Rosé
Wiley Interdisciplinary Reviews: Cognitive Science 6 (4), 333-353, 2015
Goal-based course recommendation
W Jiang, ZA Pardos, Q Wei
Proceedings of the 9th international conference on learning analytics …, 2019
Adapting bayesian knowledge tracing to a massive open online course in edx
Z Pardos, Y Bergner, D Seaton, D Pritchard
Educational Data Mining 2013, 2013
Using fine-grained skill models to fit student performance with Bayesian networks
ZA Pardos, NT Heffernan, B Anderson, CL Heffernan, WP Schools
Handbook of educational data mining 417, 2010
The sum is greater than the parts: Ensembling models of student knowledge in educational software
ZA Pardos, SM Gowda, RSJ Baker, NT Heffernan
ACM SIGKDD explorations newsletter 13 (2), 37-44, 2012
Does Time Matter? Modeling the Effect of Time with Bayesian Knowledge Tracing.
Y Qiu, Y Qi, H Lu, ZA Pardos, NT Heffernan
EDM, 139-148, 2011
Using HMMs and bagged decision trees to leverage rich features of user and skill from an intelligent tutoring system dataset
ZA Pardos, NT Heffernan
Journal of Machine Learning Research W & CP, 2001
Navigating the parameter space of Bayesian Knowledge Tracing models: Visualizations of the convergence of the Expectation Maximization algorithm
Z Pardos, N Heffernan
Educational Data Mining 2010, 2010
Enabling real-time adaptivity in MOOCs with a personalized next-step recommendation framework
ZA Pardos, S Tang, D Davis, CV Le
Proceedings of the fourth (2017) ACM conference on learning@ scale, 23-32, 2017
Designing for serendipity in a university course recommendation system
ZA Pardos, W Jiang
Proceedings of the tenth international conference on learning analytics …, 2020
Connectionist recommendation in the wild: on the utility and scrutability of neural networks for personalized course guidance
ZA Pardos, Z Fan, W Jiang
User modeling and user-adapted interaction 29, 487-525, 2019
Clustering students to generate an ensemble to improve standard test score predictions
S Trivedi, ZA Pardos, NT Heffernan
Artificial Intelligence in Education: 15th International Conference, AIED …, 2011
Learning gain differences between ChatGPT and human tutor generated algebra hints
ZA Pardos, S Bhandari
arXiv preprint arXiv:2302.06871, 2023
The effect of model granularity on student performance prediction using Bayesian networks
ZA Pardos, NT Heffernan, B Anderson, CL Heffernan
International Conference on User Modeling, 435-439, 2007
The utility of clustering in prediction tasks
S Trivedi, ZA Pardos, NT Heffernan
arXiv preprint arXiv:1509.06163, 2015
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