C Rosé, E McLaughlin, R Liu, K Koedinger. (2019). Explanatory Learner Models: Why Machine Learning (Alone) is not the Answer. British Journal of Educational Technology.

R Liu, J Stamper, J Davenport, S Crossley, D McNamara, K Nzinga, B Sherin. (2018). Learning linkages: Integrating data streams of multiple modalities and timescales. Journal of Computer-Assisted Learning.

R Liu, K Koedinger. (2017). Going beyond better data prediction to create explanatory models of educational data. Handbook of Learning Analytics, First Edition.

R Liu, K Koedinger. (2017). Closing the loop: Automated data-driven skill model discoveries lead to improved instruction and learning gains. Journal of Educational Data Mining.

R Liu, K Koedinger. (2017). Towards reliable and valid measurement of individualized student parameters. Proceedings of the 10th International Conference on Educational Data Mining.

S Crossley, R Liu, D McNamara. (2017). Predicting math performance using natural language processing tools. Proceedings of the 7th International Learning Analytics & Knowledge Conference.

R Liu, R Patel, K Koedinger. (2017). Modeling common misconceptions in learning process data. Proceedings of the 6th International Learning Analytics & Knowledge Conference. Best Paper Nominee.

R Liu, J Davenport, J Stamper. (2016). Beyond Log Files: Using multi-modal data streams towards data-driven KC model improvement. Proceedings of the 9th International Conference on Educational Data Mining.

R Patel, R Liu, K Koedinger. (2016). When to block versus interleave practice? Evidence against teaching fraction addition before fraction multiplication. Proceedings of the 38th Annual Meeting of the Cognitive Science Society.

C MacLellan, R Liu, K Koedinger. (2015). Accounting for slipping and other false negatives in logistic models of student learning. Proceedings of the 8th International Conference on Educational Data Mining.

R Liu, K Koedinger. (2015). Variations in learning rate: Student classifications based on systematic residual error patterns across practice opportunities. Proceedings of the 8th International Conference on Educational Data Mining.

R Liu, L Holt. (2015). Dimension-based statistical learning of vowels. Journal of Experimental Psychology: Human Perception & Performance.

R Liu, E McLaughlin, K Koedinger. (2014). Interpreting model discovery and testing generalization to a new dataset. Proceedings of the 7th International Conference on Educational Data Mining. Best Paper Nominee.

L Emberson, R Liu, J Zevin. (2013). Is statistical learning constrained by lower level perceptual organization? Cognition.

E Laing, R Liu, A Lotto, L Holt. (2012). Tuned with a tune: Talker normalization via general auditory processes. Frontiers in Psychology.

R Liu, L Holt. (2011). Neural changes associated with nonspeech auditory category learning parallel those of speech category acquisition. Journal of Cognitive Neuroscience.

L Emberson, R Liu, J Zevin. (2009). Statistics all the way down: How is statistical learning accomplished using varying productions of novel, complex sound categories? Proceedings of the 31st Annual Meeting of the Cognitive Science Society.