Evolution of University Admission Preferences, A Data Mining Approach with CRISP-DM

Abstract

With the aim of identifying preferences and finding patterns related to them, this article serves as a guide on how to apply the CRISP-DM Methodology in data mining within higher education. This study intends to analyze cases of student preferences upon entering university, and how these analyses can be used to make relevant decisions regarding efforts to attract new prospective students by clearly defining each characteristic of interest to the university. It explores how data can be analyzed using the CRISP-DM methodology and how results can be effectively presented.