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A Data Mining Approach to Diagnosing Student Learning Problems in Sciences Courses

A Data Mining Approach to Diagnosing Student Learning Problems in Sciences Courses

Gwo-Jen Hwang
Copyright: © 2005 |Volume: 3 |Issue: 4 |Pages: 16
ISSN: 1539-3100|EISSN: 1539-3119|ISSN: 1539-3100|EISBN13: 9781615202362|EISSN: 1539-3119|DOI: 10.4018/jdet.2005100104
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MLA

Hwang, Gwo-Jen. "A Data Mining Approach to Diagnosing Student Learning Problems in Sciences Courses." IJDET vol.3, no.4 2005: pp.35-50. http://doi.org/10.4018/jdet.2005100104

APA

Hwang, G. (2005). A Data Mining Approach to Diagnosing Student Learning Problems in Sciences Courses. International Journal of Distance Education Technologies (IJDET), 3(4), 35-50. http://doi.org/10.4018/jdet.2005100104

Chicago

Hwang, Gwo-Jen. "A Data Mining Approach to Diagnosing Student Learning Problems in Sciences Courses," International Journal of Distance Education Technologies (IJDET) 3, no.4: 35-50. http://doi.org/10.4018/jdet.2005100104

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Abstract

In recent years, researchers have attempted to develop more effective distance education systems. Nevertheless, students in network-based learning environments may need additional guidance and assistance when they encounter problems in learning certain concepts. Therefore, it is important to provide learning guidance in a distance learning environment. In this paper, we propose a data mining approach that is capable of assisting teachers to provide information needed for guiding students during the learning process. Several experiments on science courses have shown the effectiveness of applying the novel approach.

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