Using a life course approach, this chapter reviews key gender gaps in measured skills (e.g. reading, mathematics), career expectations, educational attainment, field of study and barriers to lifelong learning. Several key factors influencing these gender differences are presented. The chapter closes with policy options to reduce gender segregation in fields of study and ensure gender equality in lifelong learning and adult skills.
Gender Equality in a Changing World
Taking Stock and Moving Forward
Abstract
Gender gaps in educational attainment and skills arise in youth, reflecting gendered socialisation processes. Girls and boys, for instance, expect to pursue different careers, and their expectations largely reflect existing occupational segregation. Gender gaps in basic skills – including reading, mathematics and science – also appear relatively early.
In nearly all EU and OECD countries, women have surpassed men in terms of educational attainment, reflecting several interrelated factors, such as perceived differences in labour market opportunities for women and men without tertiary education; changes in social norms and economic opportunities; and educational systems and occupational degree requirements; among others.
Although women may be more likely to pursue tertiary education, notable segregation by field of study persists, with women far less likely to pursue studies in engineering, mathematics, information and technology.
Gender gaps in literacy and numeracy evolve over the life course, reflecting that women and men use different skills at home, at school, and at work as a result of segregation by occupation and education and gender norms and stereotypes around paid and unpaid work.
Women and men report similar levels of participation in adult education and training, but barriers to access differ by gender, with women much more likely than men to report that family responsibilities are preventing them from engaging in learning opportunities.
Incorporating a gender angle into education policies is essential to ensure equitable access and opportunities for all. By considering gender, policies can promote inclusivity, challenge stereotypes, and create a learning environment where every student can thrive, regardless of their gender.
To overcome gender segregation by field of study, governments have implemented a range of interventions, including gender sensitive learning materials, teacher training and career counselling, alongside dedicated career pathways, industry partnerships and targeted financial incentives. To close gender gaps in lifelong learning and adult skills, governments are turning toward flexible learning options and short-cycle programming at learning institutions, as well as policies and programmes that support a better balance between work, family and education.
Educational attainment and skills are strongly linked to labour market success, and women and men should be able to choose their educational paths without being constrained by gender norms or stereotypes. Yet, gender norms and stereotypes and attitudes toward gender roles have long influenced choices, and in some cases, policy environments have deliberately limited opportunities (e.g. some professions were historically not open to women).
This chapter proceeds as follows. Section 4.1 reviews key gender gaps in educational attainment and skills for girls and boys and women and men over the life course, as well as some of the key factors behind gender differences in interests, career expectations and educational outcomes. Section 4.2 explores policy options to reduce gender segregation in fields of study and ensure gender equality in lifelong learning and adult skills.
Starting in childhood and youth, this section looks at gender gaps in performance in reading, science and mathematics and in career expectations. This section then turns to young adulthood, highlighting gender differences in educational attainment and field of study. In the final part, this section investigates the evolution of measured skills and access to lifelong learning in middle and later adulthood. Key explanations for gender differences are put forth.
4.1.1. Childhood and youth: Gender stereotypes and norms start exerting an influence early
From the earliest ages, gender norms and stereotypes influence the expectations of girls and boys concerning their skills and career expectations.
Gender gaps in perceived and measured skills and abilities emerge in childhood and youth
Skills developed in childhood are the foundation for skills in later life. Once gaps emerge – whether the result of nature, nurture, socialisation, some combination of the above, or something else entirely – they can be difficult to close (OECD, 2020[1]), signalling the importance of early intervention.
From a gender perspective, differences in perceived and measured skills and abilities develop early (OECD, 2020[2]). International testing data, for example, show that at around age 10 years, gender gaps in reading favour girls, while gender gaps in mathematics and science favour boys (see Online Annex Figure 4‑A1) (OECD, 2022[3]). And at age 15, boys continue to post higher scores than girls in mathematics in most EU and OECD countries and girls continue to outperform boys in reading in all EU and OECD countries (Figure 4.1). Although tackling gender gaps in measured skills in adolescence is important for ensuring improved gender equality in later life, it should be noted that gender gaps in reading, mathematics and science tend to be smaller than those found for other personal characteristics, such as socio‑economic background (OECD, 2024[4]).
Gender gap (boys less girls) in average scores (points), 15‑year‑old students, 2022
Note: EU‑26 and OECD‑37 averages reflect unweighted averages. ↗ indicates that the data is sorted according to this series in ascending order. Data for this figure can be downloaded via Annex 4.A.
Source: OECD Secretariat calculations using publicly available microdata from the 2022 OECD Programme for International Student Assessment (PISA) (www.oecd.org/en/data/datasets/pisa-2022-database.html#data).
These patterns and trends in gender gaps at the average do, however, mask important narratives across the score distribution (Figure 4.2). In mathematics and science, for example, gender gaps favour girls at the bottom of the distribution, but flip to favour boys at the top of the distribution. This change occurs at around the 50th percentile and gender gaps in favour of boys grow larger for higher percentiles in the distribution. This likely reflects deeply engrained associations – learned at a young age – between high-level intellectual abilities and men. By age six years, for instance, evidence finds that “girls are less likely than boys to believe that members of their gender are “really, really smart” and begin to avoid activities said to be for children who are “really, really smart” (Bian, Leslie and Cimpian, 2017[5]).
By contrast, for reading, gender gaps in performance favour girls across the distribution, although they are smaller at the top. Since reading is a foundational skill that underpins learning and competence in all areas, boys’ underperformance in this area may be contributing to early school leaving and lower tertiary enrolment (see Section 4.1.2).
Gender gap (boys less girls) in average scores (points) for selected percentiles of the score distribution, 15‑year‑old students, 2022
Note: EU‑26 and OECD‑37 averages reflect unweighted averages. Data for Luxembourg are missing. The 95th percentile refers to the highest scorers and the 5th percentile to the lowest scorers. Data for this figure can be downloaded via Annex 4.A.
Source: OECD Secretariat calculations using publicly available microdata from the 2022 OECD Programme for International Student Assessment (PISA) (www.oecd.org/en/data/datasets/pisa-2022-database.html#data).
Gender and migrant status may interact in important and unique ways across countries (see Online Annex Figure 4‑A2) (OECD, 2024[6]). In Austria, first-generation girls score 28 points lower in mathematics than first-generation boys and second-generation girls score 26 points lower than second-generation boys. This compares to a gender gap of only 15 points for native‑born students. By comparison, in Switzerland, gender gaps in mathematics favouring boys are smaller for first-generation students (4 points) than for second-generation (13 points) and native‑born (12 points) students. Differences across countries in gender gaps in skills by migrant status highlight how social, cultural, economic, political and institutional factors can interact with gender to influence the outcomes of girls and boys, regardless of place of birth. It is for this reason that policies and programmes to close gender gaps and support children’s skills development cannot always be generalised across countries and must, instead, reflect country-level circumstances.
Source: OECD calculations using 2022 OECD PISA.
Explaining gender gaps in mathematics and reading
No single explanation can capture the many nuances relating gender and academic achievement across all subjects, topics, ability levels or population groups (Cobb-Clark and Moschion, 2017[7]), but the gendered socialisation process is likely to play a key role.
Parents, teachers and peers may, for example, have biases – whether known or unknown, conscious or unconscious – that affect interactions (e.g. time spent assisting with homework), investments (e.g. extracurricular activities, personalised tutoring) and expectations (e.g. math ability, tertiary attainment). These differences in interactions, investments and expectations may themselves lead to disparities in interests, learning motivation and educational outcomes, contributing to later life differences in field of study and occupation (OECD, 2019[8]; Carrell, Page and West, 2010[9]; Dee, 2007[10]; Gevrek, Gevrek and Neumeier, 2020[11]; Bian, Leslie and Cimpian, 2017[5]; Carlana, 2019[12]; Baker and Milligan, 2016[13]; Lavy and Sand, 2018[14]). Indeed, evidence suggests that gender-based stereotypes about interest in technical fields emerge in children as early as six years of age (Master, Meltzoff and Cheryan, 2021[15]).
Gender biases (held by parents, teachers and peers) regarding interest in and aptitude for certain areas of work or fields of study reflect not only gender norms and stereotypes around skills and abilities, but also gendered expectations of educational and economic opportunities (Nollenberger, Rodríguez-Planas and Sevilla, 2016[16]; van Hek, Kraaykamp and Wolbers, 2016[17]; Rodríguez-Planas and Nollenberger, 2018[18]; Encinas-Martín and Cherian, 2023[19]). For example, girls may put less personal effort into the study of mathematics, as current patterns of occupational segregation may lead them to aspire to and expect to work in careers that do not require high levels of mathematics. Parents and teachers, observing the same patterns, may expect less of girls than of boys and encourage them less in the study of mathematics (Gevrek, Gevrek and Neumeier, 2020[11]). Indeed, research finds that parents are less likely to expect their daughters to work in a STEM field (OECD, 2015[20]). Girls have also been found to have higher levels of math anxiety (Foley et al., 2017[21]), less confidence in their math abilities (OECD, 2015[20]), and a greater distaste for mathematics (Bharadwaj et al., 2016[22]). In fact, even when controlling for test scores, high school boys evaluate their math abilities as higher than girls, and boys’ self-assessment is less likely to be impacted by receiving lower grades (Zander et al., 2020[23]). This is consistent with research that finds that men generally engage in more self-promotion than women (Exley and Kessler, 2022[24]).
Boys, on the other hand, have been found to be less interested in or motivated by reading (Marinak and Gambrell, 2010[25]). Boys may also eschew reading to build their “masculine” social identity and status among peers, since reading is viewed as more “feminine” (Espinoza and Strasser, 2020[26]), and stereotypically feminine (or less masculine) behaviour is often associated with lower status and/or the domestic sphere (Berdahl et al., 2018[27]; EIGE, 2020[28]). The belief that reading is not masculine may derive, in part, from the fact that boys are not exposed to reading early in their lives in the same way as girls. Fathers are, for example, less likely to read than mothers and fathers are less likely to read to sons than to daughters (Auxier et al., 2021[29]; Leavell et al., 2011[30]). Recognising that not enough fathers were reading to their children, in 1999, Sweden’s national unions launched a project called Las For Mej, Pappa (“Read to Me, Dad”). Through this project, local union branches disseminate information about the programme and stock books of interest to both union members and their children. Each local union also organises “dad days,” where a working-class author presents his book and a child-development expert discusses the importance of writing and reading, explaining to fathers how they can help to improve their child’s reading habits (OECD, 2012[31]). Participants apply for leave under the Study Leave Act and tax-free stipends are offered (Landsorganisationen i Sverige, 2025[32]). Still ongoing in 2025, thousands of fathers have participated in the programme (IF Metall, n.d.[33]; Landsorganisationen i Sverige, 2025[32]).
Poorer performance among boys than among girls across all three subjects at the bottom of the distribution may also be related to boys’ greater likelihood of behaving in ways that are associated with poorer academic performance (e.g. arriving late at school, engaging in non-conformist and anti-social behaviour in the classroom, spending less time on homework) (Encinas-Martín and Cherian, 2023[19]; OECD, 2015[20]; Hadjar et al., 2014[34]). Gender gaps in these behaviours may stem from several factors, including gender differences in personal preferences, gender differences in the prevalence of neurological disorders, structural factors and gendered socialisation processes (OECD, 2015[20]; Hadjar et al., 2014[34]) (see Section 4.1.2).
Girls and boys often aspire and expect to work in different careers
There are clear and important differences in occupational expectations and aspirations that emerge at an early age, and these expectations largely reflect existing occupational segregation by gender. Recent work by the OECD, for example, finds that one in four of the top 30 most popular roles selected by 5‑year‑old girls are in traditionally women‑dominated occupations, while more than 1 in 2 of the top 30 most popular roles selected by 5‑year‑old boys are in traditionally men‑dominated occupations (OECD, 2021[35]). This is corroborated by Drawing the Future, a survey of over 20 000 children aged 7 to 11 years old, which finds that girls’ and boys’ career choices were clearly shaped by gender-specific ideas about jobs, with boys choosing jobs in traditionally men-dominated spaces and girls choosing jobs in traditionally women-dominated spaces (Chambers et al., 2018[36]). Similar findings emerge in more specific draw-a-scientist studies, where girls are shown to increasingly draw scientists as men as they age from childhood into adolescence (Miller et al., 2018[37]).
These gendered career aspirations and expectations persist through to adolescence. According to the 2022 OECD PISA, girls are overrepresented among those expecting to work in currently women-dominated occupations, including in personal care, health and teaching, while girls are underrepresented among those expecting to work in currently men-dominated occupations, including in information and communication technologies and the trades (Figure 4.3). Indeed, there is a striking overlap between current levels of occupational segregation and occupational segregation as measured by adolescent career expectations. Although these may only be career expectations among students at age 15 years, evidence from longitudinal studies suggests that adolescents’ expectations are a good predictor of future jobs (Mann et al., 2020[38]).
It is worth noting, however, that despite the clear persistence of occupational segregation in many areas, there are several potentially promising developments for science and engineering professionals and protective service workers (e.g. firefighters, police officers) (see Online Annex Figure 4‑A3). For example, according to the 2022 PISA, 44% of 15‑year‑old students who expect to work in careers as science and engineering professionals are girls. This is higher than in 2015, when girls accounted for only 35% of students who expected to work in such careers. It is also higher than the current share of science and engineering professionals who are women, which sits at 32% (Figure 4.3). There are similar improvements among protective service workers.
These improvements may reflect recent governmental efforts to introduce policies and programmes aimed at increasing girls’ and young women’s interest and enrolment in science, technology, engineering and math (STEM) and the introduction of recruitment campaigns and programmes in police services specifically targeting women. For example, in the 2024 OECD Questionnaire on Policy Combinations for Gender Equality, 17 out of 35 EU and OECD countries mentioned that they have included STEM-related goals in their gender equality strategies, have embedded gender equality considerations into their national strategies on STEM and/or have introduced specific policies and programmes aimed at encouraging girls and women to study STEM fields and enter STEM careers.
Share (%) of 15‑year‑old students reporting career expectations for selected occupations who are girls compared to share (%) of employed persons (15‑64) in selected occupations who are women, EU‑25 countries, 2022
Note: Data refer to unweighted averages across EU countries. Occupations refer to ISCO‑08 classifications. For data on employment and adolescent career expectations, estimates represent unweighted averages for EU‑25 countries, excluding Luxembourg and Cyprus. Some countries are missing data on employment by sex for certain occupations. To ensure data reliability, country-occupation-gender cells for adolescent career expectations are only included when cell size is larger than five observations. As a result, some countries are missing data on adolescent career expectations. Data for this figure can be downloaded via Annex 4.A.
Source: Eurostat “Employed persons by detailed occupation (ISCO‑08 two‑digit level)” (https://doi.org/0.2908/LFSA_EGAI2D) combined with OECD Secretariat calculations using publicly available microdata from the 2022 OECD Programme for International Student Assessment (PISA) (www.oecd.org/en/data/datasets/pisa-2022-database.html#data).
Explaining gender differences in career expectations
As with gender gaps in skills, gender differences in career expectations are largely driven by gender stereotypes and norms which are learned through a gendered socialisation process that starts at birth. Indeed, no matter how old, children are exposed to the gendered environment around them, including at home (e.g. gendered toys), in public spaces (e.g. more women supervising children in parks), in semi-public spaces (e.g. predominantly women working in childcare centres), in the media (e.g. gendered characters in TV and film) and in educational resources (e.g. books conveying gender stereotypes and norms). And through observation of their environment, children are absorbing gender norms and stereotypes regarding behaviour, occupations, attitudes and activities.
These observations are then reinforced through learning and socialisation. Parents and teachers may relate to and interact with girls and boys in different ways and may believe – consciously or unconsciously – that girls and boys have different interests, skills and abilities, contributing to or creating gender differences in assessments, outcomes, and expectations (Nollenberger, Rodríguez-Planas and Sevilla, 2016[16]; Rodríguez-Planas and Nollenberger, 2018[18]; Hadjar et al., 2014[34]; OECD, 2019[8]). Classmates and communities may knowingly or unknowingly police gender norms and stereotypes, with children experiencing “disapproval and social penalties” in the event of deviations from expected behaviours and interests (Fraile and Sánchez‐Vítores, 2019[39]).
Books, TV and films – important elements of culture – also present children and adolescents with a gendered view of the future. In 2024, for example, of over 2 000 characters appearing in films, only 38% of women characters had an identifiable job or occupation, compared to 62% of men characters (Lauzen, 2025[40]). In this same study, only 37% of characters that were portrayed as leaders were women. This is problematic since children can absorb many gender norms and stereotypes, including those around different career paths, through media. Indeed, in a survey of over 13 000 children aged 7 to 11 years old in the United Kingdom, 39% of children drew a “dream” job performed by someone they knew, who was typically their parent, guardian or an extended family member. Of the 61% who did not know someone who did their dream job, almost half reported that they had heard about the job through TV, film or radio (Chambers et al., 2018[36]). This suggests two things. First, it suggests that role models may be important for girls and boys. Short-term exposure to role models may only temporarily change stereotypical beliefs, but longer- or long-term. Second, it also suggests that policies must work toward ensuring that all media types are regularly challenging and dismantling stereotypical representations of girls and boys and women and men.
Tackling gender norms and stereotypes that uphold gender differences in career expectations can be a challenge since such beliefs can often be self-reinforcing (Makarova, Aeschlimann and Herzog, 2019[41]). If women and girls, for example, choose not to enter STEM fields because they are “for men and boys,” there will be fewer women and girls in these fields, which ultimately bolsters the viewpoint that these fields are “for men and boys.” At the same time, however, gender norms and stereotypes may not be the sole culprit for gender differences in career aspirations and eventual field of study. Recent evidence suggests that (top performing) girls may choose not to study fields related to science and mathematics because they (feel they) are even better at reading. Indeed, even when girls are top performances in mathematics, they are more likely to hold an “intra‑individual strength” in reading. This comparative advantage for girls in reading may be contributing to gendered self-selection across fields of study (Breda and Napp, 2019[42]; Stoet and Geary, 2018[43]).
4.1.2. Young adulthood: Gender norms and stereotypes translate into gendered career paths and life choices
Gender norms and stereotypes learned through socialisation processes at a young age combine with economic, structural and behavioural factors to translate into gendered choices regarding field of study and level of education. This ultimately affects career paths.
Women are more likely to obtain a tertiary education, while men are more likely to leave school early
Across the 15 OECD countries with available data, only 15% of women aged 25‑64 years had a tertiary education in the 1981‑89 period, compared to 19% of men. Over time, these shares have continuously increased for both women and men, although the increase has been larger for women. By the 2020‑23 period for this same set of 15 countries, 46% of women had a tertiary education, compared to 39% of men (see Online Annex Figure 4‑A4).
Higher levels of educational attainment for women relative to men is now essentially the norm across all OECD countries, with only 5 countries showing the opposite pattern, namely Mexico, Türkiye, Germany, Switzerland and Korea. (Figure 4.4). Even in these cases, however, gender gaps remain quite small, sitting at 3 percentage points, on average. By comparison, in those EU and OECD countries where gender gaps favour women, gaps are, on average, three times larger (9 percentage points).
Share (%) of women and men (25‑64) whose highest level of educational attainment is tertiary, 2023 or latest
Note: EU‑25 and OECD‑38 averages are unweighted. Data for Chile are from 2022. Tertiary education refers to ISCED 2011 Levels 5‑8, and includes short-cycle tertiary, Bachelor’s or equivalent, Master’s or equivalent, and Doctorate or equivalent. Data for this figure can be downloaded via Annex 4.A.
Source: OECD Data Explorer “Adults’ educational attainment distribution, by age group and gender” (https://data-explorer.oecd.org/s/16o).
Higher levels of tertiary educational attainment among women are partly driven by higher rates of early school leaving among men. In 2023, among OECD countries, 20% of men aged 25‑64 had left formal education without having completed an upper secondary degree (OECD Data Explorer, 2024[44]).1 By comparison, 18% of women report having less than an upper secondary education. Gender gaps are of a similar size among those aged 25‑34 years, but drop-out rates are lower for both women (12%) and men (15%), reflecting increasing educational attainment among EU and OECD populations.
Gender gaps in educational attainment often vary across racial and ethnic groups (see Online Annex Figure 4‑A5). In Canada, for instance, women who identify as Inuk, First Nations, Métis, Southeast Asian, Filipino, and Latin American are more likely to have a Bachelor’s degree than similar men. By contrast, women who identify as Black, Arab, South Asian, Chinese, West Asian and Korean are less likely than similar men to have a Bachelor’s degree. Gender gaps range from 1 to 5 percentage points when favouring men and 1 to 10 percentage points when favouring women. In New Zealand, gender gaps favour women for all racial and ethnic groups, ranging from a gap of 2 percentage points to 8 percentage points. In most EU and OECD countries, such analyses are not possible as data on ethnicity and race are lacking, and in some EU and OECD countries, collecting data on ethnicity and race is not legal. This makes it impossible to assess differences in outcomes and limits the capacity for governments to implement (targeted) interventions.
Source: Statistics Canada Table 98‑10‑0330‑01 “Visible minority by occupation, highest level of education and generation status: Canada, provinces and territories” and Table 98‑10‑0413‑01 “Highest level of education by census year, Indigenous identity and Registered Indian status: Canada, provinces and territories” and Statistics New Zealand Aotearoa Data Explorer “Highest qualification and ethnic group (grouped total responses) by age group and sex, for the census usually resident population count aged 15 years and over, 2006, 2013, and 2018 Censuses (RC, TA, SA2, DHB).”
Explaining gender differences in educational attainment
Gender gaps in tertiary educational attainment can be linked to several key factors that are economic, social, structural and behavioural in nature.
Labour market opportunities and occupational segregation: Due to occupational segregation, men have had (and still have) different career goals and more, better and/or different employment opportunities without formal upper secondary or tertiary educational credentials than women (Welmond and Gregory, 2021[45]; OECD, 2023[46]; Bonnet and Murtin, 2023[47]; Borgna and Struffolino, 2017[48]; OECD, 2022[49]). These findings are corroborated by a Pew Research Center survey in which 26% of men without a tertiary education reported that the reason they did not pursue further education was because they did not need higher education for the job or career they desired. This compares to only 20% of women (Parker, 2021[50]).
Social norms and economic opportunities: In the last century, beliefs about the roles of women and men in society and in the household have undergone a rapid shift, with younger generations of women less likely than older generations of women to believe that the most important role for a woman is to take care of her home and family (see Online Annex Figure 4‑A6) (Eurobarometer, 2024[51]). This has allowed women to enter the labour market in ever greater numbers. At the same time that norms around gender roles have been changing, the economic benefits that accrue to people with higher levels of education have increased and there has been strong “demand for labour in service professions” (Hadjar et al., 2014[34]). Combined together, the increasing acceptance of women in the labour market, greater opportunities for women in the labour market, and rising returns to education explain much of the increasing educational attainment of women (Encinas-Martín and Cherian, 2023[19]; Hadjar et al., 2014[34]). Indeed, as proposed by Becker (1964[52]), for women, investing in education only made sense when women could use that education to earn an income or gain status in the labour market.
Parental expectations: Parental expectations can exert an important influence on educational outcomes, and parents of girls are slightly more likely to report that they expect their child to complete tertiary education than parents of boys. Indeed, in the 22 OECD countries with available data, 76% of parents expect their sons to complete tertiary education, compared to 80% for daughters (see Online Annex Figure 4‑A7) (OECD, 2022[3]). Although such gaps are small, a simple correlation exercise between gender gaps in parental expectations and gender gaps in tertiary educational attainment for the population aged 25‑64 years across the 24 EU and OECD countries with available data reveals a positive correlation coefficient above 0.60. This means that countries with larger gender gaps in tertiary educational attainment (measured as the share of women aged 25‑64 years with tertiary less the share of men aged 25‑64 years with tertiary) also have larger gender gaps in parental expectations (measured as the share of girls with parents who expect them to go to university minus the share of boys with parents who expect them to go to university). Different expectations for sons and daughters may reflect that “parents still harbour stereotypical notions of what women and men excel at and the career they can pursue when they enter the labour market,” which is itself related to existing occupational segregation (OECD, 2015[20]).
Educational systems: The characteristics of educational systems can play an important role in shaping the size and direction of gender gaps in outcomes. Consider first highly stratified education systems (also known as early tracking systems). These systems place students in different types of programmes (e.g. academic, vocational) to provide them with different skills (and sometimes with different credentials) (Hadjar et al., 2014[34]). In some cases, stratification is so extreme that placement in certain programmes does not provide direct access to tertiary education, limiting a student’s options after completion of compulsory school (OECD, 2021[53]). But even when pathways are open in theory, there may be significant barriers to access to these pathways in practice and graduates from vocational education and training (VET) programmes are not always set up for success in post-secondary education. While tertiary attainment should not be the goal for everyone and many technical and vocational education programmes have very strong outcomes, limiting access to tertiary education hinders the opportunities for graduates from these programmes to engage in further learning. In many highly stratified systems, boys are more likely than girls to be placed into or oriented towards VET programmes (OECD, 2015[20]). This early gendered sorting by programme not only reinforces gender inequality in future career options and educational attainment, but it has also been shown to lead to gender gaps in measured skills (van Hek, Buchmann and Kraaykamp, 2019[54]; Lorenz and Schneebaum, 2023[55]). Alongside gender norms and stereotypes, some of the reasons for gendered differences in enrolment by programme type (including into VET programmes) include overall lower achievement among boys (with low achievers overrepresented in VET programmes); greater awareness of the need to prepare for labour market entry among boys (given that men are more likely to be in occupations requiring technical or vocational skills); and a greater enjoyment and interest in the content of VET programmes among boys. Consider also the level of standardisation in curricula, i.e. the extent to which teachers and schools have the ability to adjust course offerings, course content, and learning materials, such as textbooks. In a recent study, higher levels of standardisation were found to lead to lower overall reading performance for both girls and boys, but with a stronger negative association for boys than for girls, contributing to increased gender gaps in performance (van Hek, Buchmann and Kraaykamp, 2019[54]). Consider, too, testing conditions. Although more research is needed, evidence suggests that gender differences in achievement on school-based tests and assignments may reflect not only “differences in cognitive skills but also (and crucially) differences in engagement with and motivation for school-based tests” (Borgonovi, Ferrara and Maghnouj, 2018[56]; Borgonovi, 2022[57]). This suggests that changes in the tools and methods used to assess skills and competences could help narrow gender gaps. Other educational system characteristics may also matter for gender gaps in outcomes, but more research is needed, including on the underlying mechanisms and channels driving these relationships.
Degree requirements: Specific occupations have changed degree requirements in recent years, which has served to reinforce higher rates of tertiary education among women. For example, in nursing in many OECD countries, there has been a shift from a requirement for a vocational credential to a requirement for a tertiary qualification. Alongside other factors mentioned here, given the predominance of women in nursing, this change in degree requirements may have contributed to the relatively larger increase in the share of women with tertiary degrees compared to men (OECD, 2021[53]).
Impact of low socio‑economic status on academic achievement: Compared to girls, research suggests that boys’ academic performance is particularly affected by low socio‑economic status (DiPrete and Buchmann, 2013[58]; Autor and Wasserman, 2013[59]; Welmond and Gregory, 2021[45]; Autor et al., 2023[60]), potentially contributing to their overrepresentation among low achievers. Evidence suggests that this gender difference is not the result of family environment (as measured by initial allocation to family types and health at birth), and that only a small portion is accounted for by environmental factors (e.g. schools and neighbourhoods) (Autor et al., 2023[60]). Instead, gender differences seem to be mostly driven by a differential sensitivity to household inputs. For example, compared to girls, “having a mother who is married at birth – a proxy for men role models in the home – confers additional benefits to boys relative to girls, particularly at the lower tails of the outcome distribution” (Autor et al., 2023[60]). Boys may also be “differentially vulnerable to a scarcity of parental time, emotional and financial resources due to gender differences in non-cognitive skills, including boys’ lower rates of socio‑emotional skills and lesser ability to delay gratification” (Autor et al., 2023[60]).
Over-representation of women in education professions: In the OECD, women represented 96% of teachers in early childhood education and 83% of teachers at the primary level (see Online Annex Figure 4‑A8). It has been suggested that the over-representation of women in education has contributed to boys’ poor academic performance (Hadjar et al., 2014[34]), but there is no consensus in the literature on the impact of teacher-student gender matches on either boys or girls (Viarengo, 2021[61]). Whether teacher-student gender matches have an impact or not, a better balance between women and men teachers in education and across subject matters could benefit all students by challenging gender norms and stereotypes and biased views of teachers and specific fields of study (OECD, 2023[46]). The over-representation of women in teaching is likely driven by many factors, including gender stereotypes that mean teaching is perceived as a woman’s profession; greater use and availability of flexible working arrangements, which make teaching attractive for working mothers; and differences in relative wages between women and men, which make teaching financially less appealing to men than to women (OECD, 2022[62]). Recent research from an audit study also suggests that men applicants may face gender bias in hiring, particularly for entry-level positions (Fullard, 2025[63]).
Sense of belonging and achievement in academic environments: Students who perform poorly at school are difficult to motivate and are at greater risk of early school leaving (Encinas-Martín and Cherian, 2023[19]). They may also feel disconnected or alienated from school, leading them to “build an identity based on rebellion against school and formal education,” increasing their risk of early leaving (Encinas-Martín and Cherian, 2023[19]). Compared to girls, boys are more likely to report that they feel alienated at school and more likely to perform poorly (Hadjar et al., 2014[34]; OECD, 2023[46]).
Behaviours associated with educational success: Across a range of indicators related to educational success – e.g. on-time arrival at school, engagement in non-conformist and anti-social behaviour in the classroom, time spent on homework, regular attendance at school, enjoyment of reading, etc. – boys do worse than girls (Encinas-Martín and Cherian, 2023[19]; OECD, 2015[20]; Hadjar et al., 2014[34]). These gender gaps may stem from several factors. Boys are, for example, less likely than girls to have an interest in and be motivated by school (Hadjar et al., 2014[34]; Parker, 2021[50]). Structural factors within education systems may also be contributing to boys’ lack of engagement as “learning environments, pedagogical practices and curricula” are less likely to “relate to and engage the interest and dispositions of many teenage boys” (OECD, 2015[20]). Neurological disorders – which are more prevalent among boys (see Chapter 7) – could equally be playing a role in gender gaps in behaviours associated with educational success, particularly in engagement in non-conformist and anti-social behaviour in the classroom. Layered on top of these factors is a gendered socialisation process that teaches boys that being interested in schoolwork and displaying characteristics important for educational success – e.g. conformity, co‑operation, submission – is not aligned with “masculine” ideals – e.g. indifference toward formal achievement and disregard of authority (OECD, 2015[20]; Hadjar et al., 2014[34]).
On average, women account for 57% of those aged 25‑34 years with a Bachelor’s degree, compared to 49% of those with a Doctorate in OECD countries (see Online Annex Figure 4‑A9). The decline in the share of women among credential holders at higher levels of educational attainment suggests that women are not continuing on the academic track at the same rate as men.
One important factor that may be preventing women from continuing on to further levels of education is the lack of supportive family policy. In some OECD countries, for example, higher education students may not have (e.g. Australia) or only recently gained access to (paid) family leave (e.g. Poland) (OECD STIP, 2023[64]; Universities Australia, 2024[65]). Higher education students may also not be able to access affordable high-quality – and crucially – flexible childcare on campus, without which it may be difficult to continue on or complete their studies (Reichlin Cruse et al., 2021[66]). Suitable and affordable (family) housing may also be more difficult to find (Manze, Watnick and Freudenberg, 2021[67]).
Another important factor that may limit women’s pursuit of higher levels of education may be discrimination and harassment, especially in men-dominated fields such as science, technology, engineering and math (STEM) (OECD, 2022[68]).
Gender-based violence is pervasive (see Chapter 8) and women victims/survivors may face barriers to education or challenges within academic settings. Perpetrators may, for example, prevent their partners from studying (e.g. physical violence or stalking at university, disruption of academic efforts, destroying homework or school supplies). These obstacles may lead to lower academic success and, if women victims/survivors are forced to abandon or delay their studies, lower levels of educational attainment. Indeed, in a recent study in Australia, women victims/survivors of domestic violence were less likely to attain a university degree compared to women who had not experienced domestic violence, with the gap in attainment reaching 15% by age 25 years.
Source: Summers, Shortridge and Sobeck (2025[69]), The Cost of Domestic Violence to Women's Employment and Education.
Gender differences in fields of study stem from gender norms and stereotypes
Gender segregation by field of study exists within VET programmes and within tertiary. In the context of VET programmes, girls are more likely to be enrolled in health and social care, while boys are more likely to be enrolled in energy-, industry- and building- and construction-related programmes (e.g. Nordic Council of Ministers (2022[70])). In the context of tertiary education, a similar picture emerges, with women more likely to enrol in education, health and welfare and men more likely to enrol in information and communication technologies (ICTs) and engineering, manufacturing and construction (Figure 4.5). These gaps are partly the consequence of gendered career expectations and gendered performance across subject matters (see Section 4.1.1), which are both a product of gender stereotypes and norms (Encinas-Martín and Cherian, 2023[19]).
Share (%) of graduates for selected fields of education at the tertiary level who are women, 2022
Note: EU‑25 and OECD‑36 averages are unweighted. Data for Japan for information and communication technologies (ICTs) is not available. All levels of tertiary are included. In Türkiye, shares hover around 50% for all five subjects presented. Data for this figure can be downloaded via Annex 4.A.
Source: OECD Data Explorer “Number of enrolled students, graduates and new entrants by field of education” (https://data-explorer.oecd.org/s/p1).
4.1.3. Middle and older adulthood: Gender gaps in adult skills and lifelong learning
Skill acquisition does not cease upon completing secondary or tertiary education. Instead, skill acquisition continues through various channels, such as on-the‑job training and short course programming. This section explores gender differences in skills in adulthood, as well as use of and barriers to adult learning and training.
Gender gaps in measured skills evolve over the life course
Literacy and numeracy skills evolve over the life course, reflecting differences in individual use of such skills at work and at home and later life investment in training and continuing education. Gender gaps in numeracy, for example, grow larger and increasingly favour boys and men as individuals age. By contrast, gender gaps in literacy – which favour girls and women – peak during adolescence and are smaller for young adults, creating an inverted-U shape (OECD, 2020[2]; Borgonovi, Choi and Paccagnella, 2018[71]). Recent results combining the 2022 PISA and the 2023 Survey of Adult Skills uphold these findings, with smaller gender gaps in literacy and larger gender gaps in numeracy among older age groups (OECD, 2024[72]).
This evolution of skills over the life course is related to segregation by education, field of study and occupation and to gender norms and stereotypes around paid and unpaid work. Indeed, segregation by field of study, industry and occupation means that women and men do not have the same opportunities to learn, practice and maintain their level of proficiency in different types of skills and abilities (Encinas-Martín and Cherian, 2023[19]). Men, for instance, are more likely to specialise in fields of study and occupations that use math and numeracy more intensively, which may contribute to growing gaps as people age. By contrast, literacy is a skill used across all fields of study and occupations and is key to success in education and in the labour market (OECD, 2020[2]; Borgonovi, Choi and Paccagnella, 2018[71]), which may contribute to shrinking gaps across the life course. To top it all off, women are more likely to step out of the labour market for caregiving reasons, which may further cause skills, such as literacy, numeracy and problem solving, to atrophy.
While it is difficult to separate cohort effects (i.e. different age groups are exposed to different social, economic and cultural institutions and norms, which may affect measured skills), cross-sectional results show that gender gaps in numeracy favour men across all ages, with gaps growing larger for older age groups. By contrast, gender gaps in literacy favour women, but the size of the gap is smallest for older women and men (Figure 4.6).
Gender gap (men minus women) in mean literacy and numeracy scores by age group, 2023
Note: OECD average is unweighted and includes 27 OECD countries plus England (United Kingdom) and the Flemish-speaking regions of Belgium. Results are based on the Survey of Adult Skills (PIAAC) run in 2023. Gender gaps in mean scores in literacy and numeracy in the PIAAC cannot be directly compared to the gender gaps in mean scores in math, science and reading in the PISA (see Figure 4.1) because of differences in standard deviations. OECD (2024[72]) notes that when expressing gender gaps in the two surveys relative to their standard deviations, the gender gap in literacy among adults is smaller than the gender gap in reading for 15‑year‑old students, while the gender gap in numeracy is larger, suggesting a widening of the gap among adults. These findings are in line with previous studies that compared the proficiency of 15‑year‑olds in PISA with that of 27‑year‑olds in the first cycle of the Survey of Adult Skills (Borgonovi, Choi and Paccagnella, 2021[73]). Data for this figure can be downloaded via Annex 4.A.
Source: OECD (2024[72]), Do Adults Have the Skills They Need to Thrive in a Changing World?: Survey of Adult Skills 2023, Table A.2.8 (L) and Table A.2.8 (N), https://stat.link/eb8dxq.
Family responsibilities are a major barrier to women’s continued education and training
On average, across the OECD, there is little difference in the extent to which women and men are engaging in adult education and training (see Online Annex Figure 4‑A10) (Eurostat, 2024[74]) and similar shares of women and men report barriers to access to education and training (18% of men versus 21% of women) (Eurostat, 2024[75]). Yet, gender differences emerge in the specific barriers cited. Compared to men, for instance, women are notably more likely to cite family obligations and responsibilities as a barrier to education and training (Figure 4.7). This finding is corroborated by the OECD Survey of Adults Skills, which finds that family obligations are a reason for non-participation for 27% of women with children compared to 4% of men with children (OECD, 2021[76]). As a barrier, family responsibilities are unique in their nature since they prevent parents from developing adequate learning habits, cause parents to divert their attention from studying and decrease the overall productivity of learning and study processes (OECD, 2021[76]).
Share (%) of women and men (25‑64) not participating in education or training by reason for not participating, 2022
Note: EU‑27 average is weighted. Reasons for not participating do not add to 100. “No response” is dropped from figure. Data for this figure can be downloaded via Annex 4.A.
Source: Eurostat “Population wanting to participate in education and training, by reason for not participating and sex”, https://doi.org/10.2908/TRNG_AES_176.
Beyond the indicators presented in this chapter and in the Online Annex, relevant data sources include:
OECD Dashboard on Gender Gaps: Presents key indicators on gender inequalities in education, employment, governance and private and public leadership.
OECD Programme for International Student Assessment (PISA): Features data on students’ behaviours, experiences, expectations, and skills both at home and at school. Important social and demographic factors relating to the family and school are also included.
European Institute for Gender Equality (EIGE)’s Gender Statistics Database: Contains information on gender equality in education, including participation in education and training, educational attainment, early school leaving, skills, and work experiences during school.
OECD Education at a Glance: Provides authoritative information on the state of education around the world, including developments in gender gaps.
OECD Skills Outlook: Offers insights into ongoing and forthcoming issues related to changes in skills demands, skills supply and the implications of skills policies for economic and social well-being.
Using Table 4.1, this section applies the priority considerations of the conceptual framework included in Chapter 3 to advance gender equality in educational attainment and skills by exploring two examples of policy goals (priority consideration 1): tackling gender segregation in fields of study (Outcome A) and ensuring gender equality in lifelong learning and adult skills (Outcome B). These goals need to be accompanied by a results framework (priority considerations 1 and 4), whose indicators can be drawn from those presented in Section 4.1 and additional sources.
Table 4.1 is designed to assist policy makers in identifying cross-portfolio policy and programme combinations (priority consideration 3) and planning for their evaluation (priority consideration 2). While the list of policy options is extensive, it does not pretend to be exhaustive. At the same time, not all policy options apply in all settings or contexts. Overall, Table 4.1 aims to encourage the consideration of different policy options as part of a cross-sectoral and multi-stakeholder approach that works towards the achievement of gender equality outcomes.
Tackling gender segregation in fields of study, for example, requires a comprehensive life course approach, starting from combatting gender norms and stereotypes among youth around career aspirations and expectations. Policy interventions additionally need to ensure that women and men can choose any occupation or industry of interest to them – for instance, by encouraging workplaces to combat toxic masculinity in men-dominated occupations (e.g. STEM, trades) and by ensuring both women and men have access to fitted equipment that can keep them safe (e.g. steel-toed boots) (OECD, 2021[77]). In recent decades, policy has strongly focused on increasing the presence of women in men-dominated industries and occupations (see Section 4.2.2 for examples from Germany). Yet, to fully tackle gender segregation, investments must equally support and encourage men entering non-traditional fields, such as care and education (see Section 4.2.2 for examples from Norway).
In a similar way, ensuring gender equality in lifelong learning and adult skills demands for a comprehensive approach across domains – including education, unpaid work, earnings and income, and health. For instance, supporting the diverse needs of working-age women and men – e.g. balancing work, family, care and education – may require adapting learning provision (Stein, 2023[78]; OECD, 2023[46]), offering financial assistance for adults returning to education (OECD, 2017[79]), as well as complementary interventions such as childcare and long-term care to rebalance unpaid care responsibilities within households (OECD, 2021[80]).
Table 4.1 also highlights the important feedback loops between policy goals. Gender segregation in fields of study, for example, contributes to occupational and industrial segregation, which translates into gender differences in skill use and acquisition in the workplace, contributing to gender gaps in adult skills and learning opportunities. Occupational and industrial segregation and gender differences in skills can further contribute to gender differences in pay and pensions (see Chapter 5), in leadership and representation (see Chapter 6), and in the impacts of the green and digital transition (see Chapter 9).
The effectiveness of the policies and programmes outlined in Table 4.1 varies across countries and across time. Continuous monitoring and evaluation that incorporates a gender perspective (priority consideration 5) is essential for governments to understand the gendered effects of policies and programmes (see Chapters 2 and 3); ensure that policies and programmes are achieving their intended outcomes; identify strengths and areas for improvement; improve decision-making, resource allocation and accountability; and inform future strategies (priority consideration 6). While international evidence offers valuable insights on similar interventions, the effectiveness of each policy and programme will depend on their specific design and context – including interactions with other interventions, socio‑economic and cultural factors, available resources, and institutional settings.
For example, time‑limited single‑use interventions, such as brief exposure to role models, have been found to only temporarily changes the stereotypical beliefs of women and girls (Olsson and Martiny, 2018[81]). By contrast, long-term exposure – such as having a mother in a non-stereotypical occupation – is more likely to change gendered aspirations and expectations. This highlights the importance of role models for children, and the need for sustained efforts to challenge gender stereotypes across media, educational materials, and other interventions. Evidence also shows the potential of gender-neutral language, diverse role models, and teacher training to address gender bias and positively influence classroom dynamics and student outcomes (Brussino and McBrien, 2022[82]), and later-stage evidence confirms that teacher attitudes and role models significantly influence students’ self-perceptions and educational choices, particularly in STEM (Carlana, 2019[12]; Breda et al., 2020[83]). Embedding gender equality in early childhood education through inclusive curricula and teacher training can additionally reshape expectations and reduce gender segregation in later study and career choices (UNICEF, 2022[84]). Recognising this, governments are increasingly adjusting curricula, revising textbooks and teaching materials and offering teacher training on gender sensitivity. Many governments are further introducing gender sensitive career counselling, industry partnerships, and targeted financial incentives.
4.2.1. Key policy actions across EU and OECD countries
Note: “Env.” stands for Environment and “Agri.” stands for Agriculture.
Source: OECD Secretariat based on desk research and the 2024 OECD Questionnaire on Policy Combinations for Gender Equality and OECD (2022[49]; 2021[85]), Government of Ireland (2022[86]), European Union ( (European Union, 2015[87]; European Union, 2016[88]; European Union, 2017[89]; European Union, 2019[90]; OECD, 2021[76]) and European Union (2023[92]).
4.2.2. Country case studies of key policy combinations in EU and OECD countries
According to the OECD Secretariat’s 2024 Questionnaire on Policy Combinations for Gender Equality, many EU and OECD countries have implemented policy combinations to advance gender equality in educational attainment and skills. Case studies are provided below, alongside an example of building intersectionality considerations into policy combinations.
Reducing gender segregation in fields of study
Germany addresses stereotypes in early childhood education through teacher training and grants to men entering the field, as well as through STEM-based extracurricular activities and campaigns to raise awareness around girls in STEM. For example, Girls’ Day – Girls’ Future Day takes place once a year and is sponsored by the Federal Ministry for Family Affairs, Senior Citizens, Women and Youth and the Federal Ministry of Education and Research. On this nationwide day of action, schoolgirls from fifth grade onwards are given an insight into professions and courses of study in which women have thus far been underrepresented. Several ministries also support “Klischeefrei”, a coalition of over 600 members from various sectors advocating for gender-neutral career and study choices, providing resources, networking and support through a service centre and a portal. Other ministries contribute through a range of additional policies, such as grants to encourage women to enter the trades (Labour); investments in childcare in universities (Education and Research); grants to support later life transitions to in-demand occupations (Labour); investments in campus safety (Justice); grants to increase innovation in gender-specific safety equipment and standards (Labour); measures to increase women’s representation in academic leadership positions in STEM (Education and Research), interventions with employers to ensure women have better access to STEM and innovation careers (Education and Research); and programmes to support women’s networks in men-dominated fields (Culture).
Ensuring gender equality in lifelong learning and adult skills
Norway’s Ministry of Education and Research has developed a teacher recruitment programme that targets students from upper secondary schools and “folk colleges” to promote teacher education and diversity in the teaching profession and encourage entry into teaching by underrepresented groups. In another initiative, “Men in health,” the Ministry of Health and Care Service supports later life learning in non-traditional occupations through the targeted recruitment of men in the healthcare sector. It facilitates an accelerated education course to certify as a healthcare worker for job-seeking men. Successful candidates are provided a “health recruit” title after completion of the course. The health recruits alternate between receiving social benefits and a salary. Since 2010, more than 800 men aged 25‑55 years have obtained certificates as health professionals through this initiative. An evaluation of the project, ran in 2018, shows that approximately 9 out of 10 got a relevant job in the healthcare sector.
In the 2023 National Action Plan of Greece’s Ministry of Education, Religious Affairs and Sports, there are five objectives relating to primary and secondary education, higher education, vocational education and training, religious freedom and lifelong learning. Within the objective on lifelong learning, “Preparation of a national strategy to strengthen lifelong learning,” one of the specific actions is to design and implement targeted lifelong learning programmes for people with disability and especially for those who experience multiple discriminations, including young women and men, migrants and refugees with disabilities.
Source: OECD Secretariat using the 2024 OECD Questionnaire on Policy Combinations for Gender Equality and Government of Greece (2022[93]).
Note: Supporting data for all Chapter 4 figures in the main text and the Online Annex are available in the StatLink below.
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← 1. The European Commission measures the rate of early school leaving as the share of the population aged 18‑24 years old who had completed, at most, a lower secondary education and were not in further education or training (in the 4 weeks before the survey) (European Commission, 2020[94]).