Knowledge Component Analysis in Educational Data Mining

Abstract

Knowledge components (KCs) are defined as acquired units of cognitive function or structure that can be inferred from performance on a set of related tasks. Understanding students' learning of KCs is a fundamental educational data mining task enabling many educational applications.

Questions this source addresses

• How does educational data mining define a knowledge component, and why are KCs derived empirically from task data rather than fixed by instructional designers?
• How does knowledge component analysis translate into practical improvements in intelligent tutoring systems, such as personalized instruction and evidence-based selection of teaching strategies?
• What are the four dimensions LearnLab uses to categorize knowledge components, and how do they map to different learning processes and instructional approaches?
• What is the difference between the statistical model and the cognitive model in KC assessment, and how do they jointly explain student performance?