Zachary A. Pardos
Zachary A. Pardos
Assistant Professor at UC Berkeley
Verified email at berkeley.edu - Homepage
TitleCited byYear
Modeling individualization in a bayesian networks implementation of knowledge tracing
ZA Pardos, NT Heffernan
International Conference on User Modeling, Adaptation, and Personalization …, 2010
2092010
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
1222013
KT-IDEM: introducing item difficulty to the knowledge tracing model
ZA Pardos, NT Heffernan
International conference on user modeling, adaptation, and personalization …, 2011
1042011
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
802010
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
80*2001
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
692012
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
672010
Data mining and education
KR Koedinger, S D'Mello, EA McLaughlin, ZA Pardos, CP Rose
Wiley Interdisciplinary Reviews: Cognitive Science 6 (4), 333-353, 2015
562015
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
562014
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
492007
Adapting Bayesian Knowledge Tracing to a Massive Open Online Course in edX.
ZA Pardos, Y Bergner, DT Seaton, DE Pritchard
EDM 13, 137-144, 2013
462013
Ensembling predictions of student knowledge within intelligent tutoring systems
RSJ d Baker, ZA Pardos, SM Gowda, BB Nooraei, NT Heffernan
International Conference on User Modeling, Adaptation, and Personalization …, 2011
462011
Moocdb: Developing data standards for mooc data science
K Veeramachaneni, F Dernoncourt, C Taylor, Z Pardos, UM O’Reilly
AIED 2013 workshops proceedings volume 17, 2013
452013
Spectral clustering in educational data mining
S Trivedi, Z Pardos, G Sárközy, N Heffernan
Educational Data Mining 2011, 2010
382010
Clustering students to generate an ensemble to improve standard test score predictions
S Trivedi, ZA Pardos, NT Heffernan
International Conference on Artificial Intelligence in Education, 377-384, 2011
352011
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
342011
Determining the Significance of Item Order in Randomized Problem Sets.
ZA Pardos, NT Heffernan
International Working Group on Educational Data Mining, 2009
312009
The composition effect: Conjuntive or compensatory? an analysis of multi-skill math questions in ITS
Z Pardos, N Heffernan, C Ruiz, J Beck
Educational Data Mining 2008, 2008
272008
moocRP: An open-source analytics platform
ZA Pardos, K Kao
Proceedings of the Second (2015) ACM conference on learning@ scale, 103-110, 2015
252015
How should intelligent tutoring systems sequence multiple graphical representations of fractions? A multi-methods study
MA Rau, V Aleven, N Rummel, Z Pardos
International Journal of Artificial Intelligence in Education 24 (2), 125-161, 2014
252014
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