Research and design of applying association rule in Course Management System

Ningjiu Tang, Zhi Chen, Tao Lin, Jie Cui · 2012

Course Management System (CMS) is web-based system which is designed to simplify, streamline, and automate many aspects of the course's management. But, traditional CMS has some problems in helping teachers gathering students' information. In this paper, we have designed a framework of association rules application called ARMOCMS, and implemented the prototype on Moodle platform, which is a popular open-source CMS. We adopted an improved version of PredictiveApriori algorithm to mine data. Specifically, we integrate the experience evaluation of experts and subjective evaluation of teachers into the system's knowledge base. And then, the system will form weighted precision with rules being mined to strengthen the subjective interestingness evaluation. Besides, the system can provide some suggestions to enhance the intelligibility of rules. The rules which are not matched will be classified according to their novelty in rank. The experiment result shows that our work can help teachers make better decisions.

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