Unveiling College Student Preferences: Integrating Numerical and Factor Analysis in Understanding Choices for Mathematics Majors
Abstract
Purpose of the study: This study aims to understand the factors that influence students in choosing a mathematics major using the factor analysis method.
Methodology: Data were collected through structured interviews from 150 students at two different universities using stratified random sampling techniques. Analysis was performed using Principal Component Analysis (PCA) and Varimax rotation to identify the main dimensions that influence student preferences. Numerical analysis helped to group the variables into relevant factors based on the loading values
Main Findings: Factors that influence students in choosing Mathematics Major consist of 19 variables which are grouped into 5 factors, namely: the first factor is privileges and facilities with an eigenvalue of 4.088%, the second factor is the lecture building and social factors with an eigenvalue of 2.431%, the third factor is the promotion factor with an eigenvalue of 1.743%, the fourth factor is the job factor with an eigenvalue of 1.351%, the fifth factor is the comfort factor with an eigenvalue of 1.148%.
Novelty/Originality of this study: These findings provide new insights for educational institutions in designing effective promotional strategies and developing relevant curricula to increase the attractiveness of mathematics majors. The novelty of this study lies in the application of factor analysis to map students' specific reasons, which has rarely been done before in the context of higher education.
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