Optimal Learning Lab

Applying cognitive theory to optimize learning.
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Publications

Featured publications from the lab.

A short list of recent and representative papers connected to the lab's work on adaptive practice, student modeling, knowledge tracing, and transfer.

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Recent

Recent featured work

2026 | Published April 15

How meaningfulness and initial learning degree influence associative storage and retrieval processes: A multinomial processing tree and power function analysis

Chu, W., Pavlik, P. I., Jr., & Hu, X. (2026). Psychonomic Bulletin & Review, 33, article 141.

Published article and DOI
2026

Comparing Zero-Shot Large Language Model Prompting with Human Coding of Theory Concepts in Student Essays

Keith, S., Pavlik, P. I., Jr., Stives, K. L., & Kerr, L. J. (2026). Journal of Educational Data Mining, 18(1), 286–317.

Published article and DOI
2025

Evolutionary Features for Mitigating Cold Starts in Logistic Knowledge Tracing

Pavlik, P. I., Jr., & Eglington, L. G. (2025). Proceedings of the 18th International Conference on Educational Data Mining, 403-409.

Published article and DOI
Modeling

Knowledge tracing and student modeling

First page thumbnail for How to optimize student learning using student models that adapt rapidly to individual differences

How to optimize student learning using student models that adapt rapidly to individual differences

Eglington, L. G., & Pavlik, P. I., Jr. (2023). International Journal of Artificial Intelligence in Education, 33(3), 497-518.

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First page thumbnail for How well do contemporary knowledge tracing algorithms predict the knowledge carried out of a digital learning game?

How well do contemporary knowledge tracing algorithms predict the knowledge carried out of a digital learning game?

Scruggs, R., Baker, R. S., Pavlik, P. I., Jr., McLaren, B. M., & Liu, Z. (2023). Educational Technology Research and Development, 71(3), 901-918.

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First page thumbnail for Logistic knowledge tracing: A constrained framework for learner modeling

Logistic knowledge tracing: A constrained framework for learner modeling

Pavlik, P. I., Eglington, L. G., & Harrell-Williams, L. M. (2021). IEEE Transactions on Learning Technologies, 14(5), 624-639.

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First page thumbnail for User modeling: a notoriously black art

User modeling: a notoriously black art

Yudelson, M., Pavlik, P., & Koedinger, K. (2011). Lecture Notes in Computer Science, 6787, 317-328.

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First page thumbnail for Performance factors analysis: A new alternative to knowledge tracing

Performance factors analysis: A new alternative to knowledge tracing

Pavlik, P. I., Jr., Cen, H., & Koedinger, K. R. (2009). In V. Dimitrova & R. Mizoguchi (Eds.), Proceedings of the 14th International Conference on Artificial Intelligence in Education (pp. 531-538).

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First page thumbnail for Using item-type performance covariance to improve the skill model of an existing tutor

Using item-type performance covariance to improve the skill model of an existing tutor

Pavlik, P., Cen, H., Wu, L., & Koedinger, K. (2008). Educational Data Mining 2008 - 1st International Conference on Educational Data Mining, Proceedings, 77-86.

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Spacing

Spacing and practice scheduling

First page thumbnail for Optimizing practice scheduling requires quantitative tracking of individual item performance

Optimizing practice scheduling requires quantitative tracking of individual item performance

Eglington, L. G., & Pavlik, P. I., Jr. (2020). npj Science of Learning, 5, Article 15.

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First page thumbnail for Using a model to compute the optimal schedule of practice

Using a model to compute the optimal schedule of practice

Pavlik, P. I., Jr., & Anderson, J. R. (2008). Journal of Experimental Psychology: Applied, 14(2), 101-117.

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First page thumbnail for Practice and Forgetting Effects on Vocabulary Memory: An Activation-Based Model of the Spacing Effect

Practice and Forgetting Effects on Vocabulary Memory: An Activation-Based Model of the Spacing Effect

Pavlik, P. I., Jr., & Anderson, J. R. (2005). Cognitive Science, 29(4), 559-586.

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Transfer

Transfer, prerequisite structure, and instructional design

First page thumbnail for A measurement model of microgenetic transfer for improving instructional outcomes

A measurement model of microgenetic transfer for improving instructional outcomes

Pavlik, P. I., Yudelson, M., & Koedinger, K. R. (2015). International Journal of Artificial Intelligence in Education, 25(3), 346-379.

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First page thumbnail for Towards better understanding of transfer in cognitive models of practice

Towards better understanding of transfer in cognitive models of practice

Yudelson, M., Pavlik, P., & Koedinger, K. (2011). Proceedings of the 4th International Conference on Educational Data Mining, 373-374.

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First page thumbnail for Using contextual factors analysis to explain transfer of least common multiple skills

Using contextual factors analysis to explain transfer of least common multiple skills

Pavlik, P. I., Yudelson, M., & Koedinger, K. R. (2011). In G. Biswas, S. Bull, J. Kay, & A. Mitrovic (Eds.), Artificial Intelligence in Education (Lecture Notes in Computer Science, Vol. 6738, pp. 256-263).

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First page thumbnail for Learning factors transfer analysis: Using learning curve analysis to automatically generate domain models

Learning factors transfer analysis: Using learning curve analysis to automatically generate domain models

Pavlik, P., Cen, H., & Koedinger, K. (2009). EDM'09 - Educational Data Mining 2009: 2nd International Conference on Educational Data Mining, 121-130.

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