Analysis of Students' Learning Behavior Based on Association Rule Mining Algorithm in Moodle Network Platform
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DOI: 10.25236/iceeecs.2018.100
Corresponding Author
Shaozhen Huang
Abstract
Based on the learning behaviors of learners in the curriculum management system, the assessment of learning performance is carried out to provide curriculum improvement and learning suggestions. The evaluation of learning materials and online courses provides feedback for teachers and students of E-learning courses. Quality is very important. However, because many curriculum management systems do not provide specific tools that allow teachers to track and evaluate all learners' behavioral activities throughout the entire process, it is very difficult to select valuable information when faced with large amounts of system data. Educational data mining is an effective way to solve this problem. Based on the introduction of E-learning data mining process, this paper focuses on the application of data mining technologies such as statistics, visualization, classification, clustering, and association rule mining in Moodle systems.
Keywords
Moodle Internet Platform, learning behavior, Association Rule.