Computerized adaptive testing and learning using Bayesian network

Abstract

In this paper, we propose a novel CAT (Computerized Adaptive Testing) system based on Bayesian network. Our novel system makes good use of topology and probabilistic inference algorithm of Bayesian network to efficiently estimate proficiency of learner and also give an adaptive learning guide when needed. From several experiments, we identified that our system could considerably improve proficiency-estimation performance when compared with conventional CAT methods.