Association Rules Mining for Educational Recommender Systems

10th International Scientific Conference Technics, Informatics and Education – TIE 2024, str. 104-107

АУТОР(И) / AUTHOR(S): Marko Bursać , Sanja Jevtić , Zoran Pavlović 

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DOI: 10.46793/TIE24.104B

САЖЕТАК /ABSTRACT:

Evaluation of e-learning systems has led to many systems based on recommending courses, teaching materials, etc. In addition to the traditional collaborative filtering, content-based filtering, and hybrid recommendation methods, this paper presents a methodology based on data mining technologies. The paper introduces a methodology for mining associative rules using the access logs of students in a Moodle course. After accessing student Moodle logs, it is necessary to clean and select the data relevant to the research, specifically the learning objects. Additionally, a query must be created to obtain transactions and discover the context of the events, which includes a list of learning objects. Based on the transaction table, we can then use an a priori algorithm to generate rules. The rules obtained using the presented methodology enable the simple creation of a system for recommending teaching materials aimed at improving the success of students.

КЉУЧНЕ РЕЧИ / KEYWORDS: 

recommendation system; apriori; learning materials; Moodle

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