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

被引:395
作者
Koedinger, Kenneth R. [1 ,2 ]
Corbett, Albert T. [1 ]
Perfetti, Charles [3 ,4 ]
机构
[1] Carnegie Mellon Univ, Human Comp Interact Inst, Pittsburgh, PA 15213 USA
[2] Carnegie Mellon Univ, Dept Psychol, Pittsburgh, PA 15213 USA
[3] Univ Pittsburgh, Learning Res & Dev Ctr, Pittsburgh, PA 15260 USA
[4] Univ Pittsburgh, Dept Psychol, Pittsburgh, PA 15260 USA
关键词
Instructional principles; Learning principles; Knowledge representation; Cognitive modeling; Education; Experimentation; Cognitive task analysis; WORKED-OUT EXAMPLES; DISTRIBUTED PRACTICE; SELF-EXPLANATIONS; COMPLEX SKILL; ACQUISITION; PRINCIPLES; EXPERTISE; TEXT; DISCRIMINATION; VARIABILITY;
D O I
10.1111/j.1551-6709.2012.01245.x
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
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.
引用
收藏
页码:757 / 798
页数:42
相关论文
共 126 条
[1]   The effects of self-explaining when learning with text or diagrams [J].
Ainsworth, S ;
Loizou, AT .
COGNITIVE SCIENCE, 2003, 27 (04) :669-681
[2]   An effective metacognitive strategy: learning by doing and explaining with a computer-based Cognitive Tutor [J].
Aleven, VAWMM ;
Koedinger, KR .
COGNITIVE SCIENCE, 2002, 26 (02) :147-179
[3]   Automated, Unobtrusive, Action-by-Action Assessment of Self-Regulation During Learning With an Intelligent Tutoring System [J].
Aleven, Vincent ;
Roll, Ido ;
McLaren, Bruce M. ;
Koedinger, Kenneth R. .
EDUCATIONAL PSYCHOLOGIST, 2010, 45 (04) :224-233
[4]   The developmental progression from implicit to explicit knowledge: A computational approach [J].
Alibali, MW ;
Koedinger, KR .
BEHAVIORAL AND BRAIN SCIENCES, 1999, 22 (05) :755-+
[5]  
Anderson J. R., 1993, Rules of the mind
[6]   The role of examples and rules in the acquisition of a cognitive skill [J].
Anderson, JR ;
Fincham, JM ;
Douglass, S .
JOURNAL OF EXPERIMENTAL PSYCHOLOGY-LEARNING MEMORY AND COGNITION, 1997, 23 (04) :932-945
[7]   An integrated theory of the mind [J].
Anderson, JR ;
Bothell, D ;
Byrne, MD ;
Douglass, S ;
Lebiere, C ;
Qin, YL .
PSYCHOLOGICAL REVIEW, 2004, 111 (04) :1036-1060
[8]  
Anderson JR, 2002, COGNITIVE SCI, V26, P85, DOI 10.1207/s15516709cog2601_3
[9]  
Anderson Jr, 2000, ADV INSTR P, V5, P1
[10]  
[Anonymous], 004769 NAT I CHILD H