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

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...

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Bibliographic Details
Published inInternational journal of distance education technologies Vol. 3; no. 4; pp. 35 - 50
Main Author Hwang, Gwo-Jen
Format Journal Article
LanguageEnglish
Published Hershey IGI Global 01.10.2005
Subjects
Algorithms
Answer Sheets
Basic Skills
Computer Assisted Instruction
Computers
Concept Mapping
Content Area Writing
Copyrights
Data mining
Diagnostic Teaching
Distance Education
Distance learning
Education
Educational Environment
Educational Technology
Electronic Equipment
Guidance
Influence of Technology
Learning Problems
Learning Processes
Numbers
Periodicals
Prerequisites
Researchers
Science Curriculum
Scientific Concepts
Student Participation
Students
Subtraction
System effectiveness
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ISSN1539-3100
1539-3119
DOI10.4018/jdet.2005100104

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Summary: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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ISSN:1539-3100
1539-3119
DOI:10.4018/jdet.2005100104