Using data mining to obtain seemingly hidden information about students

Rafael Vieira de Paula and Kelly Pazolini

Revista IPecege, 2018, vol. 4, issue 3

Abstract: The process of obtaining information from large databases, known as "Knowledge Discovery in Databases" (KDD), has been used by large companies to suggest books, films, or music, respectively, according to user preferences. This was achieved through techniques that analyze patterns to facilitate decision-making. This group of techniques is called data mining. The objective of this study was to use data mining techniques to discover seemingly hidden patterns in a questionnaire regarding student satisfaction in twelve areas of life. The dataset used for this study was collected through a questionnaire answered by a group of students from Master in Business Administration (MBA) courses at an educational institution located in the city of Piracicaba, in the state of São Paulo. This dataset was compiled and analyzed using the "Waikato Environment for Knowledge Analysis" (WEKA) software, which, through data mining techniques, was able to establish trends in student satisfaction in twelve pre-established areas of life. The tool demonstrated the efficiency of data mining techniques in discovering patterns for the proposed scenario.

Keywords: Teaching/Communication/Extension/Profession (search for similar items in EconPapers)
Date: 2018
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