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27Regular articles Perceiving temporal regularity in music* 1 Edward W. Large, Caroline Palmer Memory for goals: an activation-based model* 39 Erik M. Altmann, J. Gregory Trafton (review)Cognitive Science 26 (837): 839. 2002.
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10Integrating representation learning and skill learning in a human-like intelligent agentArtificial Intelligence 219 (C): 67-91. 2015.
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82LearnLab's DataShop: A Data Repository and Analytics Tool Set for Cognitive ScienceTopics in Cognitive Science 5 (3): 668-669. 2013.
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76The developmental progression from implicit to explicit knowledge: A computational approachBehavioral and Brain Sciences 22 (5): 755-756. 1999.Dienes & Perner (D&P) argue that nondeclarative knowledge can take multiple forms. We provide empirical support for this from two related lines of research about the development of mathematical reasoning. We then describe how different forms of procedural and declarative knowledge can be effectively modeled in Anderson's ACT-R theory, contrasting this computational approach with D&P's logical approach. The computational approach suggests that the commonly observed developmental progression from …Read more
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43Is self-explanation always better? the effects of adding self-explanation prompts to an english grammar tutorIn N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society, . pp. 1300--1305. 2009.
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35Solving Inductive Reasoning Problems in Mathematics: Not‐so‐Trivial PursuitCognitive Science 24 (2): 249-298. 2000.This study investigated the cognitive processes involved in inductive reasoning. Sixteen undergraduates solved quadratic function–finding problems and provided concurrent verbal protocols. Three fundamental areas of inductive activity were identified: Data Gathering, Pattern Finding, and Hypothesis Generation. These activities are evident in three different strategies that they used to successfully find functions. In all three strategies, Pattern Finding played a critical role not previously ide…Read more
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13Helping students know'further'-increasing the flexibility of students' knowledge using symbolic invention tasksIn N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society, . pp. 1169--74. 2009.
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17Seeing language learning inside the math: Cognitive analysis yields transferIn 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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15Key misconceptions in algebraic problem solvingIn B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society., Cognitive Science Society. pp. 571--576. 2008.
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40Testing Theories of Transfer Using Error Rate Learning CurvesTopics in Cognitive Science 8 (3): 589-609. 2016.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 model…Read more
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32Abstract Planning and Perceptual Chunks: Elements of Expertise in GeometryCognitive Science 14 (4): 511-550. 1990.
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16Complex student models often include key parameters critical to their behavior and effectiveness. For example, one meta-cognitive model of student help-seeking in intelligent tutors includes 15 rules and 10 parameters. We explore whether or not this model can be improved both in accuracy and generalization by using a variety of techniques to select and tune parameters.We show that such techniques are important by demonstrating that the normal method of fitting parameters on an initial data set g…Read more
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61Trade‐Offs Between Grounded and Abstract Representations: Evidence From Algebra Problem SolvingCognitive Science 32 (2): 366-397. 2008.This article explores the complementary strengths and weaknesses of grounded and abstract representations in the domain of early algebra. Abstract representations, such as algebraic symbols, are concise and easy to manipulate but are distanced from any physical referents. Grounded representations, such as verbal descriptions of situations, are more concrete and familiar, and they are more similar to physical objects and everyday experience. The complementary computational characteristics of grou…Read more
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23The effect of prior conceptual knowledge on procedural performance and learning in algebraIn McNamara D. S. & Trafton J. G. (eds.), Proceedings of the 29th Annual Cognitive Science Society, Cognitive Science Society. pp. 137--142. 2007.
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37When and how often should worked examples be given to students? New results and a summary of the current state of researchIn B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society., Cognitive Science Society. pp. 2176--2181. 2008.
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24Is it better to give than to receive? The assistance dilemma as a fundamental unsolved problem in the cognitive science of learning and instructionIn B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society., Cognitive Science Society. 2008.
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55An effective metacognitive strategy: learning by doing and explaining with a computer‐based Cognitive TutorCognitive Science 26 (2): 147-179. 2002.Recent studies have shown that self‐explanation is an effective metacognitive strategy, but how can it be leveraged to improve students' learning in actual classrooms? How do instructional treatments that emphasizes self‐explanation affect students' learning, as compared to other instructional treatments? We investigated whether self‐explanation can be scaffolded effectively in a classroom environment using a Cognitive Tutor, which is intelligent instructional software that supports guided learn…Read more
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546Much problem solving and learning research in math and science has focused on formal representations. Recently researchers have documented the use of unschooled strategies for solving daily problems -- informal strategies which can be as effective, and sometimes as sophisticated, as school-taught formalisms. Our research focuses on how formal and informal strategies interact in the process of doing and learning mathematics. We found that combining informal and formal strategies is more effective…Read more
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167The Knowledge-Learning-Instruction Framework: Bridging the Science-Practice Chasm to Enhance Robust Student LearningCognitive Science 36 (5): 757-798. 2012.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 acqui…Read more
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22Development of conceptual understanding and problem solving expertise in chemistryIn B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society., Cognitive Science Society. 2008.
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Carnegie Mellon UniversityRegular Faculty
Pittsburgh, Pennsylvania, United States of America