Elizabeth A McLaughlin
Elizabeth A McLaughlin
Verified email at cs.cmu.edu
TitleCited byYear
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
1602015
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
1192013
Automated Student Model Improvement.
KR Koedinger, EA McLaughlin, JC Stamper
International Educational Data Mining Society, 2012
932012
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
852010
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
792013
Data mining and education
KR Koedinger, S D'Mello, EA McLaughlin, ZA Pardos, CP Rose
Wiley Interdisciplinary Reviews: Cognitive Science 6 (4), 333-353, 2015
692015
Instruction based on adaptive learning technologies
V Aleven, EA McLaughlin, RA Glenn, KR Koedinger
Handbook of research on learning and instruction. Routledge, 2016
462016
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
422010
Interpreting model discovery and testing generalization to a new dataset
R Liu, EA McLaughlin, KR Koedinger
Educational Data Mining 2014, 2014
212014
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
142016
A comparison of model selection metrics in datashop
J Stamper, K Koedinger, E Mclaughlin
Educational Data Mining 2013, 2013
92013
Closing the Loop with Quantitative Cognitive Task Analysis.
KR Koedinger, EA McLaughlin
International Educational Data Mining Society, 2016
72016
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), 3, 2014
72014
Methods for Evaluating Simulated Learners: Examples from SimStudent.
KR Koedinger, N Matsuda, CJ MacLellan, EA McLaughlin
AIED Workshops, 2015
62015
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
62014
Is there an explicit learning bias? Students beliefs, behaviors and learning outcomes.
PF Carvalho, EA McLaughlin, K Koedinger
CogSci, 2017
32017
The knowledge-learning-instruction (KLI) dependency: how the domain-specific and domain-general interact in STEM learning
KR Koedinger, EA McLaughlin
Washington University Libraries, 2014
22014
Explanatory learner models: Why machine learning (alone) is not the answer
CP Rosť, EA McLaughlin, R Liu, KR Koedinger
British Journal of Educational Technology 50 (6), 2943-2958, 2019
12019
Using a Hierarchical Model to Get the Best of Both Worlds: Good Prediction and Good Explanation
KR Koedinger, L Sun, EA McLaughlin
When and how do worked examples work? Middle school students’ use of worked examples in textbook homework assignments
ES Wiese, EA McLaughlin, J Booth, KR Koedinger
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