Learning Factors Transfer Analysis: Using Learning Curve Analysis to Automatically Generate Domain Models

This paper describes a novel method to create a quantitative model of an educational content domain of related practice item-types using learning curves. By using a pairwise test to search for the relationships between learning curves for these item-types, we show how the test results in a set of pairwise transfer relationships that can be expressed in a Q-matrix domain model. Creating these Q-matrices for various test criteria we show that the new domain model results in consistently better learning curve fits as shown by crossvalidation. Further, the Q-matrices produced can be used by educators or curriculum designers to gain a richer, more integrated perspective on concepts in the domain. The model may also have implications for tracing student knowledge more effectively to sequence practice in tutoring/training software.

• Type: Journal
• Year: 2009
• Where: EDM
• Authors: Philip I. Pavlik Jr., Hao Cen, Kenneth R. Koedinger
• Keywords: Data Mining, Domain Model, EDM 2009, Model, Q-matrix Domain Model