Integrating Advantages of Diverse Expert Bayesian Networks in Developing an Adaptive Learning System for the Sixth-Year Elementary School Algebra Class

碩士 === 亞洲大學 === 資訊工程學系碩士班 === 95 === The study aimed at reducing the teachers’ burden when they diagnosed and remedied students’ misconceptions in math and at developing a fast, precise and effective computerized adaptive learning system by integrate Bayesian Network as an instrument of inference an...

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Bibliographic Details
Main Authors: Chang chien ming, 張見銘
Other Authors: Liu hsiang chuan
Format: Others
Language:zh-TW
Published: 2007
Online Access:http://ndltd.ncl.edu.tw/handle/87780679215285005924
Description
Summary:碩士 === 亞洲大學 === 資訊工程學系碩士班 === 95 === The study aimed at reducing the teachers’ burden when they diagnosed and remedied students’ misconceptions in math and at developing a fast, precise and effective computerized adaptive learning system by integrate Bayesian Network as an instrument of inference and knowledge structures as concepts to help the sixthyear elementary students in learning algebra. At first, after analyzing the contents of the competence indicators and finding out the sub-skills and bugs, the study set up a model of Bayesian Network and developed a standardized test accordingly. After implementing the pre-test, five different Expert Bayesian Network were thus established. All the data collected from the pre-test were used as training samples to elevate classification results by integrating diverse Expert Bayesian Networks. Next, the study used the same data from the pre-test to analyze the students’ structure concepts when receiving tests. Then, the study added the knowledge structures to the system to make the diagnosis test adaptive. Finally, the study linked the diagnosis reports of the adaptive test to the animated remedial instructions which would arouse students’ interests in learning and would match the nodes of sub-skills. Eventually, the whole system became a computerized adaptive learning system for the sixth-year elementary students in algebra classes. After the on-line pre-tests and post-tests, the results of the adaptive learning system were as below: 1. Integrating diverse Expert Bayesian Networks elevated the classification results. Among the six fusion methods, the classification results of the Structure Fusion Method were elevated most highly. 2. It could be successfully transferred from paper tests to computerized adaptive tests. Besides, computerized adaptive tests not only saved time but they also brought about good inference results as to the existence of nodes. 3. The system could effectively diagnose the concepts which needed remedying for each individual six-year student in their algebra learning. In addition, the animated remedial instructions could serve the purpose for remedying those misconceptions.