Abstract
The trait complexes model suggests that interests, personality, and abilities converge into meaningful patterns. Understanding how these domains integrate is crucial for career guidance, as it may enhance the prediction of academic and professional trajectories. This study addressed three research questions: (RQ1) whether distinct trait complexes emerge from interests, personality traits, and perceived abilities in a sample of Portuguese higher education students; (RQ2) whether significant differences in these complexes exist between STEM (science, technology, engineering, and mathematics) and non-STEM students; and (RQ3) whether the identified complexes demonstrate significant predictive capacity in distinguishing between the two groups. The sample comprised 312 students (48.9% female; ages 18–30) from a Portuguese public university, enrolled in STEM and non-STEM fields. Participants completed the Personal Globe Inventory (PGI-PT), the Five-Factor Model Questionnaire – Brief Version (FFM-BV), and the Inventory of Work-Relevant Abilities (IWRA). Exploratory factor analysis revealed five trait complexes: People, Data, Things, Ideas, and Human Interaction. Discriminant analysis showed that these complexes significantly differentiated STEM from non-STEM students, with an overall correct classification rate of 89.1%. Things and Ideas positively predicted STEM enrolment, whereas Data and People were negative predictors. Findings support the relevance of trait complexes in understanding educational choices and highlight their utility as integrative tools in career assessment and guidance.