Discussion and Conclusion
Previous studies have convincingly shown the explanatory value of either autonomous motivation or academic self-concept regarding academic achievement. In this study, a person-oriented research perspective was used taking into account both autonomous motivation and academic self-concept, to provide first evidence of the presence of various motivational profiles among STEM students, their distribution across gender and specific student groups and to explore associations with early academic achievement.
In contrast with former research, explorative correlation analysis showed no significant association between academic self-concept and academic motivation for female students in our sample. Both motivational variables were measured during the first week of the academic year, in full transition from secondary school to the new environment of university. Since in secondary schools female students express a lower interest in STEM compared to male students [47], we can expect that the minority of females that eventually choose to study STEM in university are highly motivated. But in contrast to secondary school, where the gender composition of most classes is more or less balanced, it is possible that during the first weeks of the academic year and the first confrontations with large and predominantly male classes, their minority status becomes really apparent and affects their academic self-concept. Jackson et al. [34] reported that during transition from secondary school to university, self-concept of female students declines more than self-concept of male students and that female students are more susceptible to the Big-Fish-Little-Pond effect (BFLPE) [48]. This transition effect might become aggravated by the minority status of female students in STEM programs, and as a result, it might influence the association between motivation and self-concept.
In order to gain a more comprehensive picture of the possible synergy of both motivational variables in university STEM programs, we used a person-centered analysis approach.