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

Abstract

The KLI framework proposes that optimal instructional choices change depending on content, and identifies three coordinated taxonomies across knowledge, learning, and instruction domains. It demonstrates how conflicting recommendations from learning science literature can be resolved through analysis of how instructional methods function to facilitate different learning mechanisms needed to achieve different knowledge acquisition goals.

Used in syntheses

• The Science of Durable Learning

Questions this source addresses

• How does the timing of practice change what we remember?
• When does mixing different kinds of practice help us learn?
• When should an intelligent tutor make learning harder?
• Why do some things we learn stay with us?
• How does the KLI framework resolve the apparent conflict between research favoring testing/practice versus research favoring worked examples?
• How does the KLI framework's three coordinated taxonomies (knowledge, learning, instruction) explain why the same instructional method can help learning in one context and fail in another?
• What are the three categories of learning processes KLI identifies, and how does each connect to a distinct type of knowledge component?
• What role did LearnLab's large-scale learning data play in grounding the KLI framework's claims about matching instruction to knowledge type?