The analysis of the relationship between library use and course achievement through data mining

Extraordinary developments in information technologies increase the rate of data production, collection and storage in many sectors. That high volume of data, which can be stored instantaneously, does not make sense unless it is analyzed and transformed into a pile of data. On the other hand, by analyzing the data with the right methods, useful information can be obtained for decision makers. However, analyzing data manually in classical ways is insufficient to achieve detailed and useful results. In this sense, data mining is one of the most widely used method for making available data sources usable, understandable, transforming them into useful information and finally, obtaining potential information from raw data. In this study, the relationship between (Uşak University Faculty of Economics and Administrative Sciences) students' borrowed books about their must courses from Central Library of Uşak Univeristy and their success in the must courses were investigated through association analysis, which is one of descriptive data mining techniques. The association analysis was performed via open source WEKA data mining software. The analysis was carried out with the Apriori algorithm, which is widely used technique as found in WEKA. In this analysis it was focused on 17 must courses. As a result of the analysis, various association rules for course letter note, course achievement status and book use were obtained. In this way, the relationship between the students' borrowed books about must courses and the status of passing or failing the course along with the course grade are presented as percentage values. In addition, as a result of the association rules, a relation was found between the borrowing book and the status of passing the course in all 17 courses.