Using Bayesian Networks to Manage Uncertainty in Student Modeling
User Modeling and User-Adapted Interaction
Personalized e-learning system using Item Response Theory
Computers & Education
Adapting to intelligence profile in an adaptive educational system
Interacting with Computers
Research on Personalized E-Learning System Using Fuzzy Set Based Clustering Algorithm
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
| Hi-index | 0.00 |
The popularity of learning environments is increasing rapidly. In order to make learning environments more efficient, researchers have been matching the item difficulty to the learner's proficiency, as is done in computerized adaptive testing (CAT) by means of the item response theory (IRT). Even though some researchers have already implemented ideas of CAT and IRT for adaptive item selection in learning environments, some differences between testing and learning environments have been overlooked. In this study we focus on those differences that may require an adaptation of these existing CAT and IRT methods.