A Bayesian Networks Based Computerized Adaptive Testing Algorithm

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Title:	A Bayesian Networks Based Computerized Adaptive Testing Algorithm
Authors:	Jui-Hsing Chang
Contributors:	Department of Computer Science and Information Engineering
Keywords:	ＡＯ* Algorithms;Entropy;Euclidean distance
Date:	2006
Issue Date:	2009-11-18 13:13:34 (UTC+0)
Publisher:	Asia University
Abstract:	Non- concrete material object of characteristic of the psychology, but the change is abstract, can not be observed and measured directly in present technology, but these characteristics can show from the real behavior , then we, according to experimenter's response situation in a certain specific situation, in order to the method that is measured indirectly , to estimate or infer the difference degree of various kinds of potential psychological specialities, how experimenters' psychological speciality has appeared in accurate and fast inference, it is exactly what we need urgently. The present in implementing trends towards computerized adaptive testing, use shellfish's theory of the cause and effect of the network, direct different colonies , such as individual , class , group or the school of class ,etc. against students, one of construction can be analysed question of diagnosing, predict the system of student's learning ability , help students to find out those one's own basic conception without clear , help the teacher remedy the reference of teaching after class ing. In this section we present an example of an adaptive test that was used to diagnose person s skills The adaptive test uses Bayesian networks to model a tested student and the given questions。 Classical approach used in educational and psychological testing is item response theory IRT 。The presented application of Bayesian network can be regarded as a generalization of the multidimensional IRT It brings two basic advantages 。 1. It can better reflect the student reasoning process and provides better insight into the modelled problem 。 2. The student model encode dependence between skills 。Therefore adaptive tests can be substantially shortened while the test precision is kept This paper probes into the mathematic unit of square measure of grade 4， using the evidence of test questions to train Bayesian Networks ， and uses AO* Algorithms as strategy of selecting items to construct question structures， compare with Euclidean distance that provides to implement the real learning diagnose on-line system。 By using system to analyze the following questions；First , is the real learning diagnose on-line system feasible？Second，does adaptive selecting item on real learning diagnose on-line system have any efficiency？ So we collected the situation of students answered items，using Bayesian Networks and Euclidean distance as tools of analyzing，discussing its correct rate，and doing the entity whether real learning diagnose on-line system is a feasible reference or not。
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