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  1.  16
    iMinerva: A Mathematical Model of Distributional Statistical Learning.Erik D. Thiessen & Philip I. Pavlik - 2013 - Cognitive Science 37 (2):310-343.
    Statistical learning refers to the ability to identify structure in the input based on its statistical properties. For many linguistic structures, the relevant statistical features are distributional: They are related to the frequency and variability of exemplars in the input. These distributional regularities have been suggested to play a role in many different aspects of language learning, including phonetic categories, using phonemic distinctions in word learning, and discovering non-adjacent relations. On the surface, these different aspects share few commonalities. Despite this, (...)
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  2.  10
    Using a Model to Compute the Optimal Schedule of Practice.Philip I. Pavlik & John R. Anderson - 2008 - Journal of Experimental Psychology: Applied 14 (2):101-117.
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  3.  26
    Practice and Forgetting Effects on Vocabulary Memory: An Activation‐Based Model of the Spacing Effect.Philip I. Pavlik & John R. Anderson - 2005 - Cognitive Science 29 (4):559-586.
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  4.  18
    Testing Theories of Transfer Using Error Rate Learning Curves.Kenneth R. Koedinger, Michael V. Yudelson & Philip I. Pavlik - 2016 - Topics in Cognitive Science 8 (3):589-609.
    We analyze naturally occurring datasets from student use of educational technologies to explore a long-standing question of the scope of transfer of learning. We contrast a faculty theory of broad transfer with a component theory of more constrained transfer. To test these theories, we develop statistical models of them. These models use latent variables to represent mental functions that are changed while learning to cause a reduction in error rates for new tasks. Strong versions of these models provide a common (...)
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  5.  13
    The Language of Instruction: Compensating for Challenge in Lectures.Srdan Medimorec, Philip I. Pavlik, Andrew Olney, Arthur C. Graesser & Evan F. Risko - 2015 - Journal of Educational Psychology 107 (4):971-990.