International Journal of Modern Education and Computer Science (IJMECS)
IJMECS Vol. 3, No. 4, 8 Aug. 2011
Cover page and Table of Contents: PDF (size: 160KB)
The Application of Bayesian Classification Theories in Distance Education System
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Author(s)
Ma Da
1,*
Wei Wei
1
Hu Hai-guang
1
Guan Jian-he
1
Index Terms
Bayesian networks, naïve Bayesian, classification, distance education, RFM model
Abstract
With the vigorous application of distance education in recent years, the biggest challenge that the learners and managers are facing today is how to institute the training courses and choose the learning resources according to the personal characteristics of learners. It is subjective to arbitrarily decide the learning resources. This study presents a new constructional method, based on the Bayesian networks of courses relationship. This method uses the feedback of learning resources from the learners and examination results of training courses as data samples. And a new procedure is presented, joining quantitative value of RFM model and naïve Bayesian algorithm, to classify the learners and offer more support to make decision. Moreover, the experimental results demonstrate that the algorithm is efficient and accurate, and the Bayesian network method can be used in other Electronic Commerce System
Cite This Paper
Ma Da, Wei Wei, Hu Hai-guang, Guan Jian-he,"The Application of Bayesian Classification Theories in Distance Education System", International Journal of Modern Education and Computer Science(IJMECS), vol.3, no.4, pp.9-16, 2011. DOI:10.5815/ijmecs.2011.04.02
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