A Guide for Association Rule Mining in Moodle Course Management System


DOI: https://doi.org/10.15308/Sinteza-2016-56-61
Authors:
Goran Avlijaš
Milenko Heleta
Radoslav Avlijaš

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Keywords:
data mining, moodle, association rule mining


Abstract:
The main goal of educational data mining is development and evaluation of different methods of exploration of educational data. Different analytical tools offer opportunities to analyze data generated by different kinds of Learning Management Systems (LMS). The goal of this paper is to describe the process of association rule mining in Moodle LMS, in theory and praxis, step by step. For practical demonstration we have used data from one of the Singidunum University Moodle courses. Data was analyzed using the open source data mining software Weka. Selected variables included students’ login frequency, number of accessed resources and forum messages, as well as the average performance on quizzes. With minor adaption of the proposed method any educator can realize benefits of association rule mining, regardless of prior knowledge in data analysis, and without having to purchase expensive software tools.

CITATION:

IEEE format

G. Avlijaš, M. Heleta, R. Avlijaš, “A Guide for Association Rule Mining in Moodle Course Management System,” in Sinteza 2016 - International Scientific Conference on ICT and E-Business Related Research, Belgrade, Singidunum University, Serbia, 2016, pp. 56-61. doi:10.15308/Sinteza-2016-56-61

APA format

Avlijaš, G., Heleta, M., Avlijaš, R. (2016). A Guide for Association Rule Mining in Moodle Course Management System. Paper presented at Sinteza 2016 - International Scientific Conference on ICT and E-Business Related Research. doi:10.15308/Sinteza-2016-56-61

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