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Seeing language learning inside the math: Cognitive analysis yields transfer

In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 471--476 (2010)

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  1. 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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  • The Knowledge-Learning-Instruction Framework: Bridging the Science-Practice Chasm to Enhance Robust Student Learning.Kenneth R. Koedinger, Albert T. Corbett & Charles Perfetti - 2012 - Cognitive Science 36 (5):757-798.
    Despite the accumulation of substantial cognitive science research relevant to education, there remains confusion and controversy in the application of research to educational practice. In support of a more systematic approach, we describe the Knowledge-Learning-Instruction (KLI) framework. KLI promotes the emergence of instructional principles of high potential for generality, while explicitly identifying constraints of and opportunities for detailed analysis of the knowledge students may acquire in courses. Drawing on research across domains of science, math, and language learning, we illustrate the (...)
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