Science & Engineering Research Support soCiety (SERSC)
For the personalized learning, a good testing method, which can effectively estimate a learner's proficiency, is required. In this paper, the authors propose a novel testing method, Bayesian network-based approach to Computerized Adaptive Testing (CAT). Their novel approach can estimate proficiency of the examinee effectively and efficiently because it reflects complicated relationships between all items and their categories, and can estimate detailed proficiency about each specific category. In experimental results, they show that their approach can improve accuracy and speed of estimating examinee's proficiency as compared with classical testing methods like paper-based test and conventional IRT (Item-Response Theory) -based CAT.