Vila Real (São Pedro), Portugal
Senhora da Saúde, Portugal
Este traballo aborda os determinantes da inserción laboral dos graduados en educación superior, utilizando un modelo de regresión loxística para identificar variables explicativas relacionadas con características socio-demográficas, de traxectoria académica e institucionais. A análise empírica baséase nun cuestionario anónimo en liña aplicado a un conxunto de graduados, de 2014 a 2019, en institucións portuguesas. Analizáronse arredor de cincocentas observacións. Aínda que os límites entre as universidades e as escolas politécnicas son menos obvios hoxe en día, aínda existen algunhas diferenzas entre os dous subsistemas de educación superior con respecto á adecuación do emprego á educación.
As principais diferenzas están relacionadas co campo de estudo, o xénero e a necesidade de desprazarse a un distrito diferente do domicilio familiar para estudar e traballar. Tamén se atopan factores que melloran a probabilidade de adecuación educación-emprego, comúns a ambos os subsistemas, como son i) ter estudado "ciencias sociais, comercio e dereito" e "enxeñería, fabricación e construción", ii) obtido boas notas finais, e iii) ter participado en actividades extracurriculares de formación complementaria.
This paper deals with the determinants of education-job match for higher-education graduates, using a logistic regression model to identify explanatory variables related to sociodemographic, academic trajectory and institutional characteristics. The empirical analysis is based on an anonymous online questionnaire administered to a sample of graduates, from 2014 to 2019, in Portuguese institutions, of which about five hundred observations were made. Although the boundaries between universities and polytechnics are less obvious today, there are still some differences between the two higher-education subsystems regarding education-job match. The main ones are related to the field of study, gender, and the need to move away from home to study and work. Factors that improve the probability of education-job matching, common to both subsystems, were also found, such as having i) studied ‘social sciences, commerce, and law’ and ‘engineering, manufacturing and construction’, ii) attained good final grades, and iii) participated in extracurricular activities involving complementary training