Neil Heffernan
Neil Heffernan
Professor of Computer Science, Director of the Learning Sciences and Technologies & Director of
Verified email at cs.wpi.edu - Homepage
Title
Cited by
Cited by
Year
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
2762008
Modeling individualization in a bayesian networks implementation of knowledge tracing
ZA Pardos, NT Heffernan
International Conference on User Modeling, Adaptation, and Personalization …, 2010
2752010
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
2562009
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
2502014
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
2212009
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
2152004
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
1742005
KT-IDEM: Introducing item difficulty to the knowledge tracing model
ZA Pardos, NT Heffernan
International conference on user modeling, adaptation, and personalization …, 2011
1582011
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
1532006
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
1372010
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
1242014
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
1242002
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
1232013
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
1152010
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
1092016
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
1082006
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
1032003
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
1002010
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
972006
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
932010
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