Human-Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Cogn Sci. 2012 Jul;36(5):757-98. doi: 10.1111/j.1551-6709.2012.01245.x. Epub 2012 Apr 9.
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.
尽管在教育相关的认知科学研究方面已经取得了大量的成果，但在将研究应用于教育实践时，仍然存在混淆和争议。为了支持更系统的方法，我们描述了知识-学习-教学（KLI）框架。KLI 促进了具有高度通用性的教学原则的出现，同时明确了学生在课程中可能获得的知识的详细分析的约束和机会。我们借鉴了科学、数学和语言学习等领域的研究，说明了 KLI 框架提供的知识、学习和教学事件的分析。我们提出了一套三个协调的知识、学习和教学分类法。例如，我们确定了三种广泛的学习事件（LE）类别：（a）记忆和流畅性过程，（b）归纳和精炼过程，以及（c）理解和意义生成过程，并展示了它们如何导致不同的知识变化以及对最佳教学选择的约束。
