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.
EDM'09 - Educational Data Mining 2009: 2nd International Conference on Educational Data Mining
Pavlik, P., Cen, H., & Koedinger, K. (2009). Learning factors transfer analysis: Using learning curve analysis to automatically generate domain models. EDM'09 - Educational Data Mining 2009: 2nd International Conference on Educational Data Mining, 121-130. Retrieved from https://digitalcommons.memphis.edu/facpubs/8138