Philip Pavlik

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Ken KoedingerHCII, Carnegie Mellon UniversityAdresse e-mail validée de cmu.edu
GraesserProfessor of Psychology and Institute for Intelligent Systems, University of MemphisAdresse e-mail validée de memphis.edu
John R AndersonProfessor of Psychology, Carnegie Mellon UniversityAdresse e-mail validée de cmu.edu
Andrew OlneyInstitute for Intelligent Systems and Department of Psychology, University of MemphisAdresse e-mail validée de memphis.edu
Luke G. EglingtonStaff Learning Scientist @ Amplify EducationAdresse e-mail validée de amplify.com
Xiangen HuChair Professor of Learning Sciences and Technologies, Hong Kong Polytechnic UniversityAdresse e-mail validée de polyu.edu.hk
Zhiqiang CaiUW-MadisonAdresse e-mail validée de wisc.edu
Benjamin NyeUniversity of Southern California, Institute for Creative TechnologiesAdresse e-mail validée de ict.usc.edu
Michael (Mikhail) YudelsonStaff Data Scientist at Chegg, Inc.Adresse e-mail validée de chegg.com
Carol ForsythEducational Testing ServiceAdresse e-mail validée de ets.org
Sue-mei WuProfessor of Chinese Studies, Carnegie Mellon UniversityAdresse e-mail validée de andrew.cmu.edu
John StamperHuman-Computer Interaction Institute, Carnegie Mellon UniversityAdresse e-mail validée de stamper.org
Ying FangCentral China Normal UniversityAdresse e-mail validée de ccnu.edu.cn
Brian MacWhinneyProfessor of Psychology, CMUAdresse e-mail validée de cmu.edu
Andrew J. HamptonChristian Brothers UniversityAdresse e-mail validée de cbu.edu
Nora PressonUniversity of PittsburghAdresse e-mail validée de pitt.edu
Craig KellyFedExAdresse e-mail validée de fedex.com
Diane HalpernClaremont McKenna CollegeAdresse e-mail validée de cmc.edu
Lijia WangPh.D. candidate, the University of MemphisAdresse e-mail validée de memphis.edu
Vasile RusThe University of MemphisAdresse e-mail validée de memphis.edu

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Philip Pavlik

Carnegie Mellon University, University of Memphis

Adresse e-mail validée de memphis.edu - Page d'accueil

Cognitive Psychology Applied Learning Technology


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Performance factors analysis–a new alternative to knowledge tracing PI Pavlik, H Cen, KR Koedinger Artificial intelligence in education, 531-538, 2009	818	2009
Practice and Forgetting Effects on Vocabulary Memory: An Activation‐Based Model of the Spacing Effect PI Pavlik, JR Anderson Cognitive Science 29 (4), 559-586, 2005	474	2005
Using a model to compute the optimal schedule of practice. PI Pavlik, JR Anderson Journal of Experimental Psychology: Applied 14 (2), 101, 2008	311	2008
ElectronixTutor: an intelligent tutoring system with multiple learning resources for electronics AC Graesser, X Hu, BD Nye, K VanLehn, R Kumar, C Heffernan, ... International journal of STEM education 5, 1-21, 2018	111	2018
Learning Factors Transfer Analysis: Using Learning Curve Analysis to Automatically Generate Domain Models. PI Pavlik Jr, H Cen, KR Koedinger Online Submission, 2009	92	2009
SKOPE-IT (Shareable Knowledge Objects as Portable Intelligent Tutors): overlaying natural language tutoring on an adaptive learning system for mathematics BD Nye, PI Pavlik, A Windsor, AM Olney, M Hajeer, X Hu International journal of STEM education 5, 1-20, 2018	87	2018
iMinerva: A mathematical model of distributional statistical learning ED Thiessen, PI Pavlik Jr Cognitive Science 37 (2), 310-343, 2013	66	2013
A Review of Learner Models Used in Intelligent Tutoring Systems PI Pavlik Jr, K Brawner, A Olney, A Mitrovic Design Recommendations for Intelligent Tutoring Systems: Volume 1-Learner …, 2013	58*	2013
Avoiding problem selection thrashing with conjunctive knowledge tracing K Koedinger, PI Pavlik Jr, J Stamper, T Nixon, S Ritter Educational data mining 2011, 2010	55	2010
An ACT-R model of the spacing effect PI Pavlik, JR Anderson Proceedings of the Fifth International Conference on Cognitive Modeling, 177-182, 2003	53	2003
Logistic knowledge tracing: A constrained framework for learner modeling PI Pavlik, LG Eglington, LM Harrell-Williams IEEE Transactions on Learning Technologies 14 (5), 624-639, 2021	48*	2021
Using Item-Type Performance Covariance to Improve the Skill Model of an Existing Tutor. PI Pavlik Jr, H Cen, L Wu, KR Koedinger Online Submission, 2008	47	2008
Using optimally selected drill practice to train basic facts P Pavlik, T Bolster, SM Wu, K Koedinger, B Macwhinney Intelligent Tutoring Systems, 593-602, 2008	46	2008
Understanding and applying the dynamics of test practice and study practice PI Pavlik Instructional Science 35, 407-441, 2007	34	2007
Online Learning Persistence and Academic Achievement. Y Fang, B Nye, P Pavlik, YJ Xu, A Graesser, X Hu International Educational Data Mining Society, 2017	33	2017
Operation ARIES!: Methods, Mystery, and Mixed Models: Discourse Features Predict Affect in a Serious Game. CM Forsyth, AC Graesser, P Pavlik Jr, Z Cai, H Butler, D Halpern, K Millis Journal of Educational Data Mining 5 (1), 147-189, 2013	31	2013
The FaCT (Fact and Concept Training) System: A new tool linking cognitive science with educators PI Pavlik Jr, N Presson, G Dozzi, S Wu, B MacWhinney, KR Koedinger Proceedings of the Twenty-Ninth Annual Conference of the Cognitive Science …, 2007	30	2007
A new measure of text formality: An analysis of discourse of Mao Zedong H Li, AC Graesser, M Conley, Z Cai, PI Pavlik, JW Pennebaker Discourse Processes 53 (3), 205-232, 2016	29	2016
Learning Gains for Core Concepts in a Serious Game on Scientific Reasoning. C Forsyth, P Pavlik Jr, AC Graesser, Z Cai, M Germany, K Millis, RP Dolan, ... International Educational Data Mining Society, 2012	29	2012
Using contextual factors analysis to explain transfer of least common multiple skills PI Pavlik, M Yudelson, KR Koedinger Artificial Intelligence in Education: 15th International Conference, AIED …, 2011	27	2011

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