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Koedinger, Kenneth R.; Corbett, Albert T.; Perfetti, Charles – Online Submission, 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…
Descriptors: Cognitive Science, Theory Practice Relationship, Interdisciplinary Approach, Praxis
Booth, Julie L.; Lange, Karin E.; Koedinger, Kenneth R.; Newton, Kristie J. – Online Submission, 2013
In a series of two in vivo experiments, we examine whether correct and incorrect examples with prompts for self-explanation can be effective for improving students' conceptual understanding and procedural skill in Algebra when combined with guided practice. In Experiment 1, students working with the Algebra I Cognitive Tutor were randomly assigned…
Descriptors: Concept Formation, Algebra, Mathematics Instruction, Prompting
Pavlik, Philip I., Jr.; Cen, Hao; Koedinger, Kenneth R. – Online Submission, 2009
Knowledge tracing (KT)[1] has been used in various forms for adaptive computerized instruction for more than 40 years. However, despite its long history of application, it is difficult to use in domain model search procedures, has not been used to capture learning where multiple skills are needed to perform a single action, and has not been used…
Descriptors: Performance Factors, Factor Analysis, Computer Software, Computer Assisted Instruction
Pavlik, Philip I. Jr.; Cen, Hao; Koedinger, Kenneth R. – Online Submission, 2009
This paper describes a novel method to create a quantitative model of an educational content domain of related practice item-types using learning curves. By using a pairwise test to search for the relationships between learning curves for these item-types, we show how the test results in a set of pairwise transfer relationships that can be…
Descriptors: Instructional Design, Test Results, Models, Pattern Recognition
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Pavlik, Philip I., Jr.; Cen, Hao; Wu, Lili; Koedinger, Kenneth R. – Online Submission, 2008
Using data from an existing pre-algebra computer-based tutor, we analyzed the covariance of item-types with the goal of describing a more effective way to assign skill labels to item-types. Analyzing covariance is important because it allows us to place the skills in a related network in which we can identify the role each skill plays in learning…
Descriptors: Algebra, Intelligent Tutoring Systems, Statistical Analysis, Coding