ACADEMIC PROFILE OF STUDENTS WHO DROP OUT A DEGREE. A CASE STUDY OF FACULTY OF ECONOMICS AND BUSINESS, UB
The analysis of the phenomenon of university drop out is a growing concern in higher education institutions, due to their high rates, but also to the socioeconomic impact that results from it.
There are multiple literatures on this phenomenon, from papers that focus on its definition as an academic phenomenon to studies that analyze the causes and reasons for its existence, through case studies that try to compare abandonment rates between the present university degrees and those existing before the European Higher Education Area.
Regarding the first analysis, a consensus has been reached both on the administrative and academic definition. It is considered that a student has abandoned his/ her studies if he/ she is not enrolled during two consecutive courses. This drop out may be mandatory –when the student has not met the requirements to continue- or it can also be the students voluntarily, ad for many reasons, has decided to abandon his/her studies.
On the other hand there are many studies that analyze and investigate the reasons of that abandonment. Although there is not a one and only reason accepted by everyone, there is a quite wide consensus about the fact that this phenomenon cannot be explained by a single cause but by many multiple type reasons. There are some subjective reasons related to the student (motivation, dedication ...), some economic factors, some performance factors related to the institution (level of difficulty, too theoretical requirement of career plan studies ...) and some other reasons not directly related to the education system (if the student works at the same time or is studying some other degree simultaneously).
This paper aims to make a snapshot of students who drop out any of the degrees of the Faculty of Economics and Business at the University of Barcelona, focusing on academic variables. To achieve this objective a multivariate methodology is proposed, conducting a factorial analysis and further on a cluster analysis in order to identify some possible student profiles. It aims to better understand this phenomenon and to establish or develop preventive strategies for the future.