The choice of field of study at the tertiary level: the analytic approach of mapping 2.0 and main results

This article presents the main results from a survey highlighting the students’ decision-making process at the end of upper secondary education, showing the propensities toward those continuing their studies at the tertiary level in the various subject fields and displaying the baskets of university choices. It's widely recognized in the social sciences that educational choices play a crucial role in explaining the (re)production of social and educational inequalities. The literature has shown the dual nature of choices (Bourdieu, 1970; Boudon, 1974; Mare, 1980; Breen & Goldhtorpe, 1997; Jackson, 2013), as both dependent variables with significant effects on individual pathways and future expectations, and as independent variables influenced by multiple dimensions (individual/ascriptive; aggregate/individual; institutional). The aim is to reconstruct the network of future propensities among the various university fields of studies using Social Network Analysis (Hanneman & Riddle, 2005; Knoke & Yang, 2019), from data collected by the Mapping technique (Hauser & Koppelman, 1979; Giancola et al., 2023). To achieve the goals, we developed a survey conducted between March and May 2023, in the city of Rome and the Lazio region. We collected 1953 cases of students who decide to pursue their studies at the tertiary level, from a total sample of 2860 respondents. The analysis started by identifying the level of certainty of respondents’ choice regarding the multiple proposed fields of university studies (Hoffmans et al., 2009). Next, we reconstructed the choices network, wherein the nodes represent the individual propensities and the links between them depict the mutual interchange among pairs of options. Using Social Network Analysis, we observed how perspectives overlap and combine or differ from each other. From this representation, we isolated the basket groups in which the membership was used as the dependent variable in a set of regression models. The results reveal the ability of this technique to assess the disparities in the effects on choices generated by the ascriptive factors (social origin, gender, migratory background), path variables (grade repletion, school track, school marks) and lastly attitudes towards school and university (measured using Likert and self-anchoring scales). The power of inertia of ascriptive variables seems to be reconfirmed in both the decision to pursue university studies and among the various fields of tertiary study.