The Development of Online Adaptive Learning Model in The“ Unit of Four Fundamental Arithmetic Operations of Polynomial”in The Mathematics Field of The Junior High School.

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Title:	The Development of Online Adaptive Learning Model in The“ Unit of Four Fundamental Arithmetic Operations of Polynomial”in The Mathematics Field of The Junior High School.
Authors:	CHANG, HSIN-CHUNG
Contributors:	Department of Computer Science and Information Engineering
Keywords:	Bayesian Network;computerized adaptive diagnostic testing;computerized adaptive remedial instruction
Date:	2008
Issue Date:	2009-11-18 13:14:25 (UTC+0)
Publisher:	Asia University
Abstract:	This study aims to explore the capability evaluations, sub-skills and error types in the unit of Four Fundamental Arithmetic Operations of Polynomial in the mathematics field of eighth-graders in the junior high school. There are 3 capability evaluations, 23 sub-skills and 37 error types included. By means of the probability reasoning of Bayesian Network, the research aims to construct a computerized adaptive learning mode system of this unit, which includes computerized adaptive diagnostic testing and computerized adaptive remedial instruction, so that students could be assessed, diagnosed and receive remedial instruction. The results are as follows: 　　First, by means of the dynamics threshold of Bayesian Network, the distinguishing rate of error types on average is 94%; the distinguishing rate of sub-skills on average is 91.8%; the distinguishing rate of capability evaluation is 92.1% and the diagnosis rate of the whole Bayesian Network on average is 93.3%, which show the diagnosis accuracy of Bayesian Network in this unit. 　　Second, in the aspects of computerized adaptive diagnostic testing, the rate of reducing test items is 15.8%; the prediction accuracy of the whole Bayesian Network on average is 96.5%; the prediction accuracy of the response of testing items is 97.7%. 　　Last, in the aspects of computerized adaptive remedial instruction, the progress rate of post-test is 87.5%, and the effect of students on different levels is obvious. The progress rate of error types is 37.4%; the progress rate of sub-skills is 33%. Adaptive remedial instruction upgraded students’ achievement and reduced the error types they made and enhanced their sub-skills, so the achievement is significant.
Appears in Collections:	[Department of Computer Science and Information Engineering] Theses & dissertations

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