Application of Bayesian Network–Use Two-Variable Linear Equation Unit in Junior High School Mathematics Course to Diagnostic Test Design and Adaptive Remedial Instruction

碩士 === 亞洲大學 === 資訊工程學系碩士班 === 95 === The study was to develop a system based on the probability reasoning of Bayesian Network and OT theory into Two-Variable Linear Equation Unit in seven year’s mathematics course of junior high school to induce the error types that students made and to validate the...

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Bibliographic Details
Main Authors: hung min jen, 洪敏甄
Other Authors: liou shiang chuan
Format: Others
Language:zh-TW
Published: 2007
Online Access:http://ndltd.ncl.edu.tw/handle/89771121022823325214
Description
Summary:碩士 === 亞洲大學 === 資訊工程學系碩士班 === 95 === The study was to develop a system based on the probability reasoning of Bayesian Network and OT theory into Two-Variable Linear Equation Unit in seven year’s mathematics course of junior high school to induce the error types that students made and to validate the effect of the system. The results were as follows. First, Bayesian Network was employed to diagnose the error concepts and the basic skills that students should have. The results had the ninety percent correspondence with the expert judgment. Therefore, Bayesian Network could diagnose the error types and sub-skills exactly and efficiently. In addition, the dynamics threshold of Bayesian Network had better effects than the motionless threshold in diagnosis and classification. Second, the significant differences were shown in grades among the high achievers, middle achievers and low achievers in the computerized adaptive diagnostic testing. With the design, the error types were decreased and the sub-skills were increased. The testees could receive the proper adaptive remedial instruction in time and enhance their learning. Third, the computerized adaptive diagnostic testing could save forty percent of test items. The reaction of the test answers, the error types and sub-skills could be predicted and the accuracy achieved ninety percent. It showed that in spite of a few test items, the results were similar with the complete test.