The learning loss caused by the COVID-19 pandemic on students’ outcomes is likely to have lasting effects on which evidence is lacking. Using a differencein- differences design through a triple difference estimator, we identify the evolution of the COVID-19 pandemic’s impact on Italian students’ test scores in the two years following the COVID-19 outbreak. Our findings indicate a persistently negative effect on mathematics and reading scores for grade 5 and grade 8 students in 2021–22, two years after the pandemic began, despite a statistically significant recovery compared to the previous school year. Our analysis highlights the pandemic’s disproportionate impact on girls, leading to a decrease in their academic performance and an intensification of gender-based inequalities (with the exception of grade 8 reading). Our results also show that the pandemic had a greater adverse impact on the academic achievement of students who experienced more prolonged classroom closures.

The gender gap in STEM disciplines in Italy is a persistent issue and, despite the growing interest in these subjects over the last decade, the underrepresentation of women continues to persist. The Global Gender Gap Report (2023) highlighted that Italy’s overall position has moved from 63rd place in 2022 to 79th place out of 146 countries in 2023. It seems this is mainly due to the participation of women in politics. However, a slight improvement was recorded regarding economic participation and opportunities.

According to ISTAT (2018), only 20% of graduates in STEM in Italy are women. This is significantly lower than the European average (around 40%, Eurostat, 2017). Several studies have sought to investigate the causes of this gap. Some have highlighted the importance of socio-cultural factors, such as gender stereotypes and social expectations (Nosek et al., 2009). Others have emphasised the importance of education and school orientation (OECD, 2015). However, most of these studies are based on aggregate data at the national or regional level, which can mask important differences at the local level (Blickenstaff, 2005). Moreover, few studies have examined the gender gap in STEM in Italy using advanced statistical methods (ISTAT, 2018).

In our study we refer to the data processed in accordance with the Research Protocol for the Study "From high school to the job placement: analysis of university careers and University mobility from Southern to Northern Italy" among the Ministry of University and Research, the Ministry of Education and Merit, the University of Palermo as the lead institution, and the INVALSI Institute. The reference researcher is Massimo Attanasio. Data concerns the whole individual information about any student enrolled at a public university in Italy, since 2008. In addition, just only for the students enrolled at the University of Palermo, data are linked to the results of the AlmaLaurea annual survey on graduates’ university experience and job placement.

Thanks to this huge database, we focused on the choices of bachelor's degree graduates regarding continuing their studies or going to work. Particular attention has been paid to STEM first and second-degree programs and gender differences. The use of multivariate techniques allowed us to discern the student characteristics most associated with the pathway choices made.

We acknowledge financial support under the National Recovery and Resilience Plan (NRRP), Mission 4, Component 2, Investment 1.1, Call for tender No. 104 published on 2.2.2022 by the Italian Ministry of University and Research (MUR), funded by the European Union – NextGenerationEU– Project Title Stem in Higher Education & Women INequalitieS [SHE WINS], CUP I53D23004810006, Grant Assignment Decree No. 1060 adopted on 07/17/2023 by the Italian Ministry of Ministry of University and Research (MUR).

This study was partially funded by the European Union - NextGenerationEU, in the framework of the GRINS -Growing Resilient, INclusive and Sustainable project (GRINS PE00000018 – CUP B73C22001260006). The views and opinions expressed are solely those of the authors and do not necessarily reflect those of the European Union, nor can the European Union be held responsible for them.

Predicting student performance is a key step in order to improve the efficiency of university systems. Students’ academic performance during their freshman year shapes their development throughout university career and their choice of future career (Bottia et al., 2016; Priulla et al. 2023a). In Italy, as well as in other context, the repercussions of delays or failures are undeniably significant, impacting not only students but also imposing costs on administrative functions. Furthermore, significant gendered performance differences are signals of systemic inequity in higher education (Matz et al., 2017; Priulla and Attanasio, 2023b). Although the link between gender and student performance is firmly established, there is a lack of comprehensive knowledge regarding its differential effects. Specifically, there is limited information on whether this relationship varies among students with differing levels of academic achievement (Priulla and Attanasio, 2021)

Using a unique dataset that includes the cohort of 2018/2019 high school graduates from Italy who enrolled in the Italian university system in the academic year 2019/2020, this study investigates the relationship between gender and university performance of students enrolled at a 3-year STEM (Science, Technology, Engineering and Mathematics) degree by studying how gender affects the performance of freshmen along the overall conditional distribution of credit earned in the first academic year. In addition, women and men are spread unevenly by STEM fields (e.g., horizontally). Certain STEM courses exhibit a notable male predominance, exemplified by fields such as Engineering and Informatics, while others lean towards a female majority, as seen in Natural Sciences. Additionally, some disciplines, display relatively balanced gender representation. Our study aims to illustrate the situated nature of gender disparities in credit earned along their overall conditional distribution and the importance of comparing men and women within single or at least similar scientific fields. Finally, the statistical modelling of earned credits encounters challenges posed by the discrete and often irregular nature of the observed distribution. Moreover, the hierarchical structure of our data demands an estimation strategy that extends beyond the simplicity of quantile regression (Schirripa Spagnolo et al., 2021; Carcaiso and Grilli, 2023; Grilli et al., 2016).

We acquire data from two administrative databases made available through an agreement with the Italian Ministry of University and Research (MIUR). Specifically, we integrate the ANS-U database, which contains micro-level longitudinal data sourced from the National Archive of University Students (Anagrafe Nazionale Studenti - ANS), and the INVALSI database, which includes micro-data obtained from the National Evaluation Institute for the School System (INVALSI).

The data used in this study have been processed in accordance with the RESEARCH PROTOCOL FOR THE STUDY "From high school to the jb placement: analysis of university careers and university mobility from Southern to Northern Italy" among the Ministry of University and Research, the Ministry of Education and Merit, the University of Palermo as the lead institution, and the INVALSI Institute. The reference researcher is Gianni Betti.

In this paper we ask whether the gender gap in skills - favouring boys in maths and girls in language - helps to explain the large gender gap in STEM choices in high school. The existing literature shows that skills influence educational choices, but do not help to explain the gender gap. This issue has so far been addressed in the context of the field of study at university or electives at the end of high school when students' educational choices are projected onto future employment careers and may include preferences for specific occupations and considerations of work-family balance. However, the transition between lower and upper secondary school may be driven by different motivations, and skills and performance at school may be more decisive.

This paper aims to fill this gap by focusing on the gendered choice of upper secondary school in Italy, where children are tracked into school types with very different learning goals at the age of 14. In such school systems, the choice of upper secondary school is crucial for children who end up not going on to university and can help to understand horizontal gender segregation in the labour market at lower levels of the social ladder. The Italian case is particularly suitable for study because it is a free choice system, with no binding teacher recommendations or ability restrictions: preferences are thus freely expressed without institutional constraints on the decision-making process.

We analyse the role of school performance in mathematics and Italian (teacher grades and standardised test scores), position in class ranking and comparative advantage in a subject. We find that ability matters for educational choices, but for children with low-educated parents it hardly explains the gender gap. Instead, ability mediates part of the gender gap for children from more advantaged backgrounds. Possible explanations for this difference relate to highly educated families holding more gender-egalitarian views, or to institutional features of the education system, due to the different content of STEM studies in academic and non-academic upper secondary school types.

This research project aims to provide a comprehensive understanding of the transition to employment for STEM graduates at University La Sapienza, with a particular focus on the gender differences in the labor market. Stemming from a decade-long research initiative, the project leverages an integrated approach that combines statistical analyses and bottom-up microdata analyses to gain insights into the complex dynamics characterizing the career transitions of STEM graduates(Alleva et al. 2015) . The research methodology involves the utilization of SPSS for constructing databases on graduates and employment contracts, as well as the development of derived variables from microdata to facilitate in-depth analyses.

Building on the existing model of investigation, the research extends its scope to examine the efficacy of post-graduate internships and to reconstruct individual narratives through administrative data. By delving into the mandatory communications, the incidence and role of post-graduate internships across different fields of study and their impact on the transition to employment will be explored(Lucisano et al, 2021, 2022). Furthermore, the project aims to shed light on the contradictions within the labor market that often fail to adequately value the experiences gained during university studies, particularly with respect to gender disparities.

The research also encompasses a sector-specific study on the employment transitions and the quality of the job market demand for STEM graduates. Given the central role of STEM disciplines in driving innovation and socioeconomic progress, the study seeks to provide insights that can inform educational policies and active labor market measures. It also aims to delineate strategies to enhance the employability of STEM graduates and facilitate a smooth transition into the workforce.

Moreover, the project will delve into the complex issue of the impact of employment during university studies, exploring how simultaneous work and study may influence academic experiences and subsequent career paths. Additionally, it will analyze the effectiveness of post-graduate internships and their influence on career trajectories. The research will also examine whether the STEM classification contains significant differences in outcomes within its various study paths and whether it represents a significant difference compared to other fields of study.

In conclusion, this research project seeks to provide a nuanced understanding of the career transitions of STEM graduates, with a specific emphasis on gender differences in the labor market. By integrating quantitative and qualitative methods and utilizing updated data, the study aims to outline a comprehensive picture of the challenges and opportunities that graduates encounter in their journey towards professional careers. The findings are intended to inform educational policies and support measures aimed at improving the employability of STEM graduates, particularly with regard to gender-specific considerations(Stanzione et al. 2020).

There is a burgeoning literature on women in STEM fields and their educational pathways (Cimpian, Kim & McDermott, 2020; Delaney & Devereux, 2019; Griffith, 2010: Koch et al., 2022). While a growing number of studies addresses the later labour market outcomes of women who completed STEM degrees (Sassler & Meyerhofer 2023; Sassler, Michelmore, Smith, 2017; Schwerter & Ilg 2023; White & Smith, 2022), we continue to know less about how these are shaped by family trajectories and how they relate to women’s earnings. In this study, we use rich Finnish register data to assess the labour market and family trajectories of women with STEM majors in tertiary education. We follow individuals born in 1974-1979 from age 30-40 and use multi-channel sequence analysis to identify the common labour market and family pathways of women and men. In a second step, we are interested in differences in the returns to these common pathways, in terms of earnings measured at age 40. In line with the prior literature we find that men are strongly overrepresented in engineering and computer science in Finland (Cimpian, Kim & McDermott, 2020; Sassler, Michelmore, Smith, 2017). In contrast, men and women are similarly distributed across natural science fields. We therefore run analyses separately for engineering and computer science and natural science. Multi-channel sequence analysis leads us to identify six clusters for women and men. The largest cluster for women indicates that one in three women who completed an engineering and computer science degree in tertiary education work in engineering and computer science occupations and have children (34%). The other clusters comprising a high share of women working in engineering and computer science occupations instead indicate distinct family trajectories, with women remaining single or in childless couples throughout their 30s. Among men, the largest cluster comprises individuals who work in engineering and computer science occupations and have children (42%). The other clusters comprising a high share of men working in engineering and computer science indicate a later transition into parenthood as well as remaining in childless couples and single. Late transitions into parenthood are considerably more common among men than women. Analyses on earnings at age 40 indicate that women earn less than men across clusters. Women who work in engineering and computer science tend to earn more than their counterparts in other occupations. In contrast, men who work in engineering and computer science and other occupations have similar earnings. Among both men and women, we observe considerable differences in earnings across family constellations as well as differences in the family trajectories followed by men and women. Single men and women earn less than their counterparts with children, while only childless men earn less.