This paper investigates gender differences in university performances in Science, Technology, Engineering and Mathematics (STEM) courses in Italy, proposing a novel application through the segmented regression models. The analysis concerns freshmen students enrolled at a 3-year STEM degree in Italian universities in the last decade, with a focus on the relationship between the number of university credits earned during the first year (a good predictor of the regularity of the career) and the probability of getting the bachelor degree within 4 years. Data is provided by the Italian Ministry of University and Research (MIUR). Our analysis confirms that first-year performance is strongly correlated to obtaining a degree within 4 years. Furthermore, our findings show that gender differences vary among STEM courses, in accordance with the care-oriented and technical-oriented dichotomy. Males outperform females in mathematics, physics, chemistry and computer science, while females are slightly better than males in biology. In engineering, female performance seems to follow the male stream. Finally, accounting for other important covariates regarding students, we point out the importance of high school background and students' demographic characteristics.

Andrea Priulla, Nicoletta D'Angelo, Massimo Attanasio (2021). An analysis of Italian university students' performance through segmented regression models: gender differences in STEM courses. GENUS, 77(11) [10.1186/s41118-021-00118-6].

An analysis of Italian university students' performance through segmented regression models: gender differences in STEM courses

Andrea Priulla;Nicoletta D'Angelo
;
Massimo Attanasio
2021

Abstract

This paper investigates gender differences in university performances in Science, Technology, Engineering and Mathematics (STEM) courses in Italy, proposing a novel application through the segmented regression models. The analysis concerns freshmen students enrolled at a 3-year STEM degree in Italian universities in the last decade, with a focus on the relationship between the number of university credits earned during the first year (a good predictor of the regularity of the career) and the probability of getting the bachelor degree within 4 years. Data is provided by the Italian Ministry of University and Research (MIUR). Our analysis confirms that first-year performance is strongly correlated to obtaining a degree within 4 years. Furthermore, our findings show that gender differences vary among STEM courses, in accordance with the care-oriented and technical-oriented dichotomy. Males outperform females in mathematics, physics, chemistry and computer science, while females are slightly better than males in biology. In engineering, female performance seems to follow the male stream. Finally, accounting for other important covariates regarding students, we point out the importance of high school background and students' demographic characteristics.
Settore SECS-S/01 - Statistica
Settore SECS-S/05 - Statistica Sociale
Andrea Priulla, Nicoletta D'Angelo, Massimo Attanasio (2021). An analysis of Italian university students' performance through segmented regression models: gender differences in STEM courses. GENUS, 77(11) [10.1186/s41118-021-00118-6].
File in questo prodotto:
File Dimensione Formato  
s41118-021-00118-6.pdf

accesso aperto

Descrizione: Articolo principale
Tipologia: Versione Editoriale
Dimensione 1.21 MB
Formato Adobe PDF
1.21 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10447/508860
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? 1
social impact