The Knowledge‐Learning‐Instruction Framework: Bridging the Science‐Practice Chasm to Enhance Robust Student Learning

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 prom...

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Bibliographic Details
Published in:Cognitive science 2012-07, Vol.36 (5), p.757-798
Main Authors: Koedinger, Kenneth R., Corbett, Albert T., Perfetti, Charles
Format: Article
Language:English
Subjects:
Biological and medical sciences
Cognition & reasoning
Cognitive modeling
Cognitive Psychology
Cognitive Science
Cognitive task analysis
Education
Education - methods
Educational Practices
Educational Principles
Educational psychology
Experimentation
Fundamental and applied biological sciences. Psychology
Humans
Instructional principles
Interdisciplinary Approach
Knowledge
Knowledge representation
Language
Learning
Learning principles
Logical Thinking
Mathematics
Mathematics - education
Memory
Praxis
Principles
Psychology. Psychoanalysis. Psychiatry
Psychology. Psychophysiology
Psychopedagogics. Didactics
Pupil and student. Academic achievement and failure
Science - education
Taxonomy
Teaching - methods
Theory Practice Relationship
Transfer (Psychology)
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Summary: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 analyses of knowledge, learning, and instructional events that the KLI framework affords. We present a set of three coordinated taxonomies of knowledge, learning, and instruction. For example, we identify three broad classes of learning events (LEs): (a) memory and fluency processes, (b) induction and refinement processes, and (c) understanding and sense‐making processes, and we show how these can lead to different knowledge changes and constraints on optimal instructional choices.
ISSN:0364-0213
1551-6709
DOI:10.1111/j.1551-6709.2012.01245.x