The overall aim of the project "Stem in Higher Education & Women INequalitieS" (SHE WINS) is to understand the intersections between: a) gender and STEM programs in higher education; b) gender and STEM labour market outcomes in Italy. Despite the increasing attention to the experiences, challenges, and barriers to women in STEM fields, the current research is still fragmented because it is usually based on single datasets referring to separate domains such as either secondary education or higher education or the labour market. Therefore, from a multidimensional and longitudinal perspective, a more comprehensive approach is lacking. Thanks to exclusive access to microdata of "Anagrafe Nazionale Studenti" (the Italian National Student Registry database) and their statistical linkage with both INVALSI and AlmaLaura microdata, the SHE WINS project aims at overcoming the abovementioned data fragmentation. It should offer new analysis to gain new knowledge on this critical issue.

In particular, it will be possible to answer, among others, the following crucial research questions.

• Do the features of the attended high school or the family background have an impact on women's university choices and careers?
• How well do the INVALSI test results in math explain the success/dropout in STEM careers in higher education?
• Are there regional "weaknesses" that increase the risk of not enrolling in STEM programs?
• Do the STEM gender gap change across different level of students' performances?
• Do university student careers explain the wage gender gap in the STEM labour market?
• Is there a skill-mismatch issue for women STEM graduates in the labour market?

The answer to such research questions will provide the information necessary to define a set of suitable indicators to measure, summarise and display the gender gap in STEM enrolment, dropout, student careers, and labour market outcomes. These indicators will then be used as a data repository for the prototype web-based interactive dashboard of measures and maps, constantly accessible and usable for the scientific community and policymakers in real-time.

Goals beyond the scientific purposes of the project
The goal of reducing gender inequality in STEM education is particularly challenging and relevant. Generally speaking, it is recognised that addressing the issue of any gender gap would lead to an improvement in the economic and social well-being of the whole population.

Specifically, the interest in the topic of the project is high both at the international level (SDG2030) and at the national level (PNRR). The SHE WINS project's main aims are strictly linked to their many themes and objectives.

For example, Sustainable Development Goal 4 (SDG 4, Quality Education) promotes inclusive and equitable quality education at all education levels to foster the competencies needed to face future challenges. A specific target (Target 4.5) addresses eliminating disparities, including gender inequalities, in education. It states that "all girls and boys, women and men, should have equal opportunity to enjoy education of high quality, achieve at equal levels and enjoy equal benefits from education.".

SDG 5 (Gender Equality) aims at closing the gender gap in all domains. Specifically, Target 5.8 intends to support female empowerment through technology, mainly ICT.

The Italian PNRR identifies gender equality as one of the overarching priorities. Achieving full equality for women in terms of economic and social access is an aim that every Plan's mission wants to pursue through an integrated program of resources and investments in a multidimensional perspective, funded by Next Generation EU. In the education field, promoting access by girls and women to the acquisition of STEM skills represents one of these measures. In particular, Mission 4 (Education and Research) includes lines of intervention to strengthen and improve the quality of teaching in STEM disciplines at all levels of education and encourage females to acquire STEM skills.

In addition, since 2004, the Italian Ministry for Education has been promoting the PLS, intending to foster the acquisition of scientific skills that better meet the challenges of contemporary society and the expectations of the world of work by students and strengthen the impact of education on society. Among its actions, it provides guidance activities and reduces dropout rates in STEM disciplines.

The integrated INVALSI+ANS dataset will provide crucial information for analysing domains SG1, SG2, and SG3. In detail, we will investigate the determinants of enrolment, dropout, university performances (to mention a few) using the second level school characteristics, the parents' background, and the level of competencies measured by the INVALSI test. The estimates should define specific female student profiles more at risk of gender inequality.

The analyses will allow getting information also at the sub-national level (i.e. NUTS2 or NUTS3 level of the Nomenclature of territorial units for statistics), given the level of details coming from the INVALSI+ANS dataset. Therefore, they could bring out regional disparities on which specific interventions can be envisaged, in line with the Italian PNRR about the reduction of regional unbalances. The integrated ANS+Almalaurea dataset will be helpful to investigate the link between the studies achieved and the labour market, with particular emphasis on STEM graduates and the gender gap (SG4). The results will emphasise crucial aspects that will require specific interventions to overcome the gender gap in the job market and encourage education in STEM fields.

This analysis will be developed first for graduates from the University of Palermo and then extended to other universities involved in the research agreement mentioned above. If INVALSI data before 2018 will be available, a hopeful outcome will be the integration of the three mentioned datasets into a unique database.

Work Packages

WP1 – Data Management

The aims of WP1 concern:

• managing the owned data and their continuous updates coming from the agreement with the MUR;
• finalising their integration to build databases that allow the longitudinal analysis of students' educational and professional experiences.

Moreover, since ANS-AlmaLaurea integration is of interest to many Italian universities, it is expected that they will share their AlmaLaurea data with the RUs of SHE WINS and thus contribute to enlarging the database.

In summary, there will be the following three milestones:

• MS1.1) Deterministic linkage of INVALSI and ANS microdata for longitudinal analyses
• MS1.2) Probabilistic linkage of ANS and AlmaLaurea microdata for longitudinal analyses
• MS1.3) Integration of INVALSI, ANS and Almalaurea microdata for achieving longitudinal student/graduate/worker biographies (only if INVALSI microdata will be available at least for the 2015 cohort)

WP2 - STEM Gender Gap in Education

One of the main goals of the SHE WINS Project regards the focus on the gender gap in STEM degree courses in Italy. The analysis will cover the different aspects outlined in SG1, SG2, and SG3, i.e. enrolment rates, drop-out rates, and performance in STEM degrees. In addition, a possible focus should be analysing the COVID period effect on students' choices at enrolment in HE. We will follow two interrelated approaches: that one based on indicators and the model-based one. Finding suitable measures for the investigated domains is very challenging and essential for the WP4. The overall analysis and the web-based platform require summary measures that can highlight different aspects of the gender gap in STEM. The analysis based on statistical models is helpful as it can highlight the possible determinants of the observed behaviours, especially regarding the gender gap topic. In fact, the available data allows monitoring and studying the aspects of the three SGs mentioned above and considering context information such as family social status, university experience, and high school educational background. They are all aspects that can determine choices and success at university. The Leading Unit will be the University of Siena due to the research experience of its members.

In summary, there will be the following three milestones:

• MS2.1) Descriptive analysis of the STEM-HE gender gap in a longitudinal perspective
• MS2.2) Estimation of statistical models for studying the determinants of the STEM-HE using a multidimensional and longitudinal perspective
• MS2.3) Definition of different types of indicators for measuring the intersectionality between gender and STEM in HE

WP3 – STEM Gender Gap in Employment

The second main goal is to investigate the gender gap for STEM graduates in the job market, with a particular focus on wages and job status. This aspect is really linked to the previous one because information about graduates' experience at university and their background can be helpful for such a goal. Therefore, WP2 and WP3, even though they are separate, have many contact points and opportunities for analysis and reflection. Also in this case, different statistical approaches will be followed to reach (summary) measures of the investigated domains and highlight possible factors linked to the gender gap. These results are also helpful for the WP4. The Leading Unit will be the University of Palermo, as it has already gained experience experimenting with the linkage of ANS+AlmaLaurea data on its graduates and has already started studying the topic.

In summary, there will be these three milestones:

• MS3.1) Descriptive analysis of STEM-labour market gender gap in a longitudinal perspective
• MS3.2) Estimation of statistical models for studying determinants of the gender gap in STEM labour market outcomes
• MS3.3) Definition of different types of indicators for measuring the intersectionality between gender and STEM in the labour market

WP4 - Web-based dashboard and research dissemination

Finally, WP4 is the natural expression and conclusion of the SHE WINS Project. Studies and analyses cannot have a tangible impact if they are not shared. Therefore, the creation of a web platform to consult measures and maps for monitoring aspects of the gender gap in STEM is, in our opinion, essential. This web platform will be developed in HTML JAVA script and PHB environment, with the contribution of an external consultant. We will ensure that it will be maintained, updated, and improved until the end of the Project. After its end, the prototype will still be accessible and useable.

One aspect to be stressed here concerns the work of the RUs for choosing the most relevant measures to be included in the platform, in which way to make them accessible, respecting privacy rules, and how to depict them graphically. Therefore, during this phase, the research units will discuss and reflect in-depth on identifying appropriate information and developing indicators to better communicate with the platform's users (as mentioned in WP3 and WP4).

In addition to the specific four WPs, the SHE WINS Project includes a dedicated public website to store the Project's information (e.g., objectives, Working Packages, members, and achieved goals).

Finally, the research results will be spread and also shared through scientific publications in international journals and conference communications.

In summary, there will be these four milestones:

• MS4.1) Creation of the website for SHE WINS Project
• MS4.2) Result dissemination
• MS4.3) Design of the Dashboard prototype on the STEM gender gap
• MS4.4) Implementation of the Dashboard prototype on the STEM gender gap