Many different factors are taken into account by students when choosing a degree and university. Some of these are general considerations, such as the quality of the degree course (ratio of available places/places in first choice, cut-off mark, etc.), while others are subjective factors (e.g., friends doing the same course). This paper presents a partial multivariate model that considers the weight of the different variables linked to this decision, as identified in the bibliography. We analyzed four samples of first-year students (totaln=1790) from different engineering degree courses at the Universitat Politècnica de València (UPV) in the 2010-2011 and 2011-2012 academic years. All the students involved in the study had chosen this university and their courses as their first option. The overall effect shows that the structural model adjusts reasonably well to the different engineering courses analyzed. Similarly, the individual models for each engineering degree manage to identify the different effects involved. In the case of the engineering degree based on new technologies (ICT), the statistical effects are much greater and more statistically significant than in the other three branches of engineering considered. Social and individual factors were seen to have more impact on the choice of ICT degrees at the UPV.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.