Riassunto analitico
The aim of this master's thesis is to analyse in which degree courses students from the University of Modena and Reggio Emilia (UNIMORE) graduated. This work is aimed at studying which could be the determinants that influence a student's choice to graduate in a certain field rather than another, considering also the presence and the behaviour of the gender gap in each of the field between males and females. The analysis performed has being based on a survey developed in 2018 by AlmaLaurea, where students were asked to give an overall evaluation of the study-experience at UNIMORE and their future perspectives. The database contains information from 4640 students, and focuses on the main variables related to the course evaluation (e.g. field, duration, grades, relationships, services...) and on variables related to the "background" of the students (e.g. where they come from, their social status, information about parents' title, why they graduated in a particular degree course...) I proceeded to compute the various regressions, by means of OLS, by computing four different models with the probability of graduating in one of the four different macro-areas, i.e. Physical Sciences, Social Sciences, Life Sciences and Humanities, as the dependent variable. Thus, by keeping the part of the model concerning the independent variables the same for all four models, it was possible to calculate what is how it affects the probability of graduating in one of these four areas. It resulted that the likelihood of graduating in a degree in Physical Sciences shows a negative association with being a female student, and the distance with respect to residence of the students. while a positive association is shown for being driven by purely professional motivations, having no work experience, having a good knowledge of computer tools, and having had a positive experience during the degree course. As far as Life Sciences are concerned, the likelihood of graduating in this field decreases if the likelihood of having graduated from a technical institute increases, and if competence in IT tools increases. On the other hand, there is a positive association when considering the probability of being female, when considering the quality of relationships, when considering not having work experience and when considering a purely cultural motivational component. The likelihood of graduating in a degree in the area of Social Sciences, I found it to be negatively associated with the quality of relationships of the students, with not having work experience, and with mastering IT tools, while I found it to be positively associated with coming from a technical institute and with being a female student. Lastly, I found that the likelihood of graduating in a Humanities field is positively dependent on being female, and the distance from the student’s place of residence. Whereas on the other hand, I found a negative relationship with purely professional motivational factors, no work experience status. In addition, the higher the rating a student gave to the degree course as a whole, the lower the probability of graduating in a humanities field. For each model, I calculated the relative gender gap. By means of predictive margins, in the same incremental system used for the computation of the models themselves, and I have verified that the gender gap, while being unfavourable to girls only when the physical sciences are considered, it tends to narrow as the models evolve. this evolution is not found, however, when the probability of graduating in the social sciences is considered, where a final predictive margin is greater, almost double that of the starting one.
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