Neil Heffernan
Neil Heffernan
Professor of Computer Science, Director of the Learning Sciences and Technologies
Verified email at cs.wpi.edu - Homepage
Title
Cited by
Cited by
Year
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
3192014
Modeling individualization in a bayesian networks implementation of knowledge tracing
ZA Pardos, NT Heffernan
International conference on user modeling, adaptation, and personalization …, 2010
3082010
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
3002008
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
2922009
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
2312009
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
2202004
KT-IDEM: Introducing item difficulty to the knowledge tracing model
ZA Pardos, NT Heffernan
International conference on user modeling, adaptation, and personalization …, 2011
1892011
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
1772005
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
1592006
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
1462010
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
1362014
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
1342013
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
1312002
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
1282016
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
1272010
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
1112006
Using fine-grained skill models to fit student performance with Bayesian networks
ZA Pardos, NT Heffernan, B Anderson, CL Heffernan, WP Schools
Workshop in Educational Data Mining held at the 8th International Conference …, 2006
1072006
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
1042003
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
1012006
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
962010
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