Multidimensional Analysis of University Students’ Subject Perceptions: Insights from Principal Components

In this study, principal component analysis (PCA) was applied to survey data to explore the conscious and unconscious attributes university students associate with different academic subjects and to identify the elements to which they attribute greater significance. The analysis yielded 20 principal components, of which five had eigenvalues exceeding 0.1, with cumulative explained variance reaching 80% by the tenth component. Interpretation of the components revealed that the first principal component reflected a dichotomy between subjects centered on rote memorization and those emphasizing rule-based learning, while the second component distinguished between the humanities and the sciences. Higher-order components were linked to evaluative dimensions of academic engagement, mid-level components reflected the broader epistemological positioning of disciplines, and lower-order components assessed the relational aspects of subjects in the context of interpersonal dynamics. These findings underscore the potential to provide more holistic and interdisciplinary perspectives in advising and enhancing educational practices across diverse academic disciplines.