Neil Heffernan

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Medforfattere

Ken KoedingerHillman Professor of Computer Science, Depts of Human-Computer Interaction & Psychology, CarnegieVerifisert e-postadresse på cmu.edu
Zachary A. PardosAssociate Professor at UC BerkeleyVerifisert e-postadresse på berkeley.edu
Ryan BakerUniversity of PennsylvaniaVerifisert e-postadresse på upenn.edu
Mingyu FengSenior Research Associate, WestEdVerifisert e-postadresse på wested.org
Joseph BeckWorcester Polytechnic InstituteVerifisert e-postadresse på wpi.edu
Korinn OstrowWorcester Polytechnic InstituteVerifisert e-postadresse på wpi.edu
Anthony BotelhoWorcester Polytechnic InstituteVerifisert e-postadresse på wpi.edu
Jason WalonoskiThe MITRE CorporationVerifisert e-postadresse på mitre.org
Yutao WangVerifisert e-postadresse på wpi.edu
Vincent AlevenProfessor of Human-Computer Interaction, Carnegie Mellon UniversityVerifisert e-postadresse på andrew.cmu.edu
Joseph Jay WilliamsUniversity of Toronto (Computer Science)Verifisert e-postadresse på cs.toronto.edu
Seth Akonor AdjeiNorthern Kentucky UniversityVerifisert e-postadresse på nku.edu
Jaclyn OcumpaughAssociate Director, Penn Center for Learning Analytics, University of PennsylvaniaVerifisert e-postadresse på upenn.edu
Maria Ofelia "Sweet" Z. San PedroSenior Research Scientist at ACT, Inc.Verifisert e-postadresse på act.org
Sujith GowdaAlpha Data Labs, LLCVerifisert e-postadresse på alphadatalabs.com
Yue GongWorcester Polytechnic InstituteVerifisert e-postadresse på wpi.edu
Kim M. KellyWorcester Polytechnic InstituteVerifisert e-postadresse på wpi.edu
Shubhendu TrivediMassachusetts Institute of TechnologyVerifisert e-postadresse på csail.mit.edu
Xiaolu XiongWorcester Polytechnic InstituteVerifisert e-postadresse på wpi.edu
Juho KimAssociate Professor at KAISTVerifisert e-postadresse på kaist.ac.kr

Neil Heffernan

Professor of Computer Science, Director of the Learning Sciences and Technologies & Director of

Verifisert e-postadresse på cs.wpi.edu - Startside

AI Educational Data Mining User Modeling Intelligent Tutoring Systems the cognition of mathematics learning


Tittel Sortér etter sitater Sortér etter år Sortér etter tittel	Sitert av Sitert av	År
Why students engage in “gaming the system” behavior in interactive learning environments R Baker, J Walonoski, N Heffernan, I Roll, A Corbett, K Koedinger Journal of Interactive Learning Research 19 (2), 185-224, 2008	276	2008
Modeling individualization in a bayesian networks implementation of knowledge tracing ZA Pardos, NT Heffernan International Conference on User Modeling, Adaptation, and Personalization …, 2010	275	2010
Addressing the assessment challenge with an online system that tutors as it assesses M Feng, N Heffernan, K Koedinger User modeling and user-adapted interaction 19 (3), 243-266, 2009	256	2009
The ASSISTments ecosystem: Building a platform that brings scientists and teachers together for minimally invasive research on human learning and teaching NT Heffernan, CL Heffernan International Journal of Artificial Intelligence in Education 24 (4), 470-497, 2014	250	2014
A comparison of traditional homework to computer-supported homework M Mendicino, L Razzaq, NT Heffernan Journal of Research on Technology in Education 41 (3), 331-359, 2009	221	2009
Opening the door to non-programmers: Authoring intelligent tutor behavior by demonstration KR Koedinger, V Aleven, N Heffernan, B McLaren, M Hockenberry International conference on intelligent tutoring systems, 162-174, 2004	215	2004
The Assistment project: Blending assessment and assisting L Razzaq, M Feng, G Nuzzo-Jones, NT Heffernan, KR Koedinger, ... Proceedings of the 12th annual conference on artificial intelligence in …, 2005	174	2005
KT-IDEM: Introducing item difficulty to the knowledge tracing model ZA Pardos, NT Heffernan International conference on user modeling, adaptation, and personalization …, 2011	158	2011
Detection and analysis of off-task gaming behavior in intelligent tutoring systems JA Walonoski, NT Heffernan International Conference on Intelligent Tutoring Systems, 382-391, 2006	153	2006
Comparing knowledge tracing and performance factor analysis by using multiple model fitting procedures Y Gong, JE Beck, NT Heffernan International conference on intelligent tutoring systems, 35-44, 2010	137	2010
Population validity for Educational Data Mining models: A case study in affect detection J Ocumpaugh, R Baker, S Gowda, N Heffernan, C Heffernan British Journal of Educational Technology 45 (3), 487-501, 2014	124	2014
An intelligent tutoring system incorporating a model of an experienced human tutor NT Heffernan, KR Koedinger International Conference on Intelligent Tutoring Systems, 596-608, 2002	124	2002
Predicting college enrollment from student interaction with an intelligent tutoring system in middle school MO Pedro, R Baker, A Bowers, N Heffernan Educational Data Mining 2013, 2013	123	2013
A quasi-experimental evaluation of an on-line formative assessment and tutoring system KR Koedinger, EA McLaughlin, NT Heffernan Journal of Educational Computing Research 43 (4), 489-510, 2010	115	2010
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	109	2016
Informing teachers live about student learning: Reporting in the assistment system M Feng, NT Heffernan Technology Instruction Cognition and Learning 3 (1/2), 63, 2006	108	2006
Toward a rapid development environment for Cognitive Tutors KR Koedinger, V Aleven, N Heffernan Artificial Intelligence in Education: Shaping the Future of Learning through …, 2003	103	2003
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	100	2010
Predicting state test scores better with intelligent tutoring systems: developing metrics to measure assistance required M Feng, NT Heffernan, KR Koedinger International conference on intelligent tutoring systems, 31-40, 2006	97	2006
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 40, 2010	93	2010

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