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Elizabeth A McLaughlin
Elizabeth A McLaughlin
Verified email at cs.cmu.edu
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Cited by
Cited by
Year
Learning is not a spectator sport: Doing is better than watching for learning from a MOOC
KR Koedinger, J Kim, JZ Jia, EA McLaughlin, NL Bier
Proceedings of the second (2015) ACM conference on learning@ scale, 111-120, 2015
2972015
New potentials for data-driven intelligent tutoring system development and optimization
KR Koedinger, E Brunskill, RSJ Baker, EA McLaughlin, J Stamper
AI Magazine 34 (3), 27-41, 2013
1922013
Instruction based on adaptive learning technologies
V Aleven, EA McLaughlin, RA Glenn, KR Koedinger
Handbook of research on learning and instruction, 522-560, 2016
1742016
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
1482010
Data mining and education
KR Koedinger, S D'Mello, EA McLaughlin, ZA Pardos, CP Rosé
Wiley Interdisciplinary Reviews: Cognitive Science 6 (4), 333-353, 2015
1342015
Automated Student Model Improvement.
KR Koedinger, EA McLaughlin, JC Stamper
International Educational Data Mining Society, 2012
1212012
Using data-driven discovery of better student models to improve student learning
KR Koedinger, JC Stamper, EA McLaughlin, T Nixon
International conference on artificial intelligence in education, 421-430, 2013
1132013
Explanatory learner models: Why machine learning (alone) is not the answer
CP Rosé, EA McLaughlin, R Liu, KR Koedinger
British Journal of Educational Technology 50 (6), 2943-2958, 2019
732019
Seeing language learning inside the math: Cognitive analysis yields transfer
K Koedinger, E McLaughlin
Proceedings of the annual meeting of the cognitive science society 32 (32), 2010
492010
Is the doer effect a causal relationship? How can we tell and why it's important
KR Koedinger, EA McLaughlin, JZ Jia, NL Bier
Proceedings of the sixth international conference on learning analytics …, 2016
412016
Interpreting model discovery and testing generalization to a new dataset
R Liu, EA McLaughlin, KR Koedinger
Educational Data Mining 2014, 2014
282014
A comparison of model selection metrics in datashop
J Stamper, K Koedinger, E Mclaughlin
Educational Data Mining 2013, 2013
152013
A general multi-method approach to design-loop adaptivity in intelligent tutoring systems
Y Huang, V Aleven, E McLaughlin, K Koedinger
International Conference on Artificial Intelligence in Education, 124-129, 2020
102020
Closing the Loop with Quantitative Cognitive Task Analysis.
KR Koedinger, EA McLaughlin
International Educational Data Mining Society, 2016
102016
Computer-Supported Human Mentoring for Personalized and Equitable Math Learning
P Schaldenbrand, NG Lobczowski, JE Richey, S Gupta, EA McLaughlin, ...
International Conference on Artificial Intelligence in Education, 308-313, 2021
82021
Methods for Evaluating Simulated Learners: Examples from SimStudent.
KR Koedinger, N Matsuda, CJ MacLellan, EA McLaughlin
AIED Workshops, 45-54, 2015
82015
A general multi-method approach to data-driven redesign of tutoring systems
Y Huang, NG Lobczowski, JE Richey, EA McLaughlin, MW Asher, ...
LAK21: 11th International Learning Analytics and Knowledge Conference, 161-172, 2021
72021
Is there an explicit learning bias? Students beliefs, behaviors and learning outcomes.
PF Carvalho, EA McLaughlin, K Koedinger
CogSci, 2017
72017
Data-driven Learner Modeling to Understand and Improve Online Learning: MOOCs and technology to advance learning and learning research (Ubiquity symposium)
KR Koedinger, EA McLaughlin, JC Stamper
Ubiquity 2014 (May), 1-13, 2014
72014
MOOCs and technology to advance learning and learning research: Data-driven learner modeling to understand and improve online learning
KR Koedinger, EA McLaughlin, JC Stamper
Ubiquity 3, 1-13, 2014
72014
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