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1、2024GLOBAL EDUCATION MONITORING REPORTTechnology on her termsGENDER REPORTiiiThis publication is available in Open Access under the Attribution-ShareAlike 3.0 IGO(CC-BY-SA 3.0 IGO)licence (http:/creativecommons.org/licenses/by-sa/3.0/igo/).By using the content of this publication,the users accept to

2、 be bound by the terms of use of the UNESCO Open Access Repository(https:/www.unesco.org/en/open-access/cc-sa).The present licence applies exclusively to the texts.For the use of images,prior permission shall be requested from:publication.copyrightunesco.org or UNESCO Publishing,7,place de Fontenoy,

3、75352 Paris 07 SP France.UNESCO is an Open Access publisher and all publications are made available online,free of charge through UNESCOs documentary repository.Any commercialization of its publications by UNESCO is for cost recovery of nominal actual costs for printing or copying content on paper o

4、r CDs,and distribution.There is no profit motive.This publication can be referenced as:UNESCO.2024.Global Education Monitoring Report:Gender report Technology on her terms.Published in 2024 by the United Nations Educational,Scientific and Cultural Organization 7,Place de Fontenoy,75352 Paris 07 SP,F

5、rance UNESCO,2024 First editionISBN:978-92-3-100672-2https:/doi.org/10.54676/WVCF2762For more information,please contact:Global Education Monitoring Report team UNESCO,7,place de Fontenoy 75352 Paris 07 SP,France Email:gemreportunesco.org Tel.:+33 1 45 68 07 41 www.unesco.org/gemreport https:/ Any e

6、rrors or omissions found subsequent to printing will be corrected in the online version at www.unesco.org/gemreport Typeset by UNESCOPrinted on recycled,PEFC certified paper,with vegetable inks.Graphic design by Optima DesignLayout by Optima DesignCover photo:UNICEF/UNI526471/Tapes Caption:13-year-o

7、ld Victoria from Herson Ukraine,poses for a photo during a robotics activity organized at a Community Refugee Centre in Cahul,Moldova.Gender Reports of the Global Education Monitoring Report series2022 Deepening the debate on those still left behind2020 A new generation:25 years of efforts for gende

8、r equality in education2019 Building bridges for gender equality2018 Meeting our commitments to gender equality in education2016 Education for people and planet:Creating sustainable futures for allPrevious Gender Reviews of the EFA Global Monitoring Report series2015 Gender and the EFA 20002015:Achi

9、evements and challenges2013/4 Teaching and learning:Achieving quality for all2012 Youth and skills:Putting education to work2011 The hidden crisis:Armed conflict and educationThis report and all related materials are available for download here:Bit.ly/2024genderreport.ivThe Global Education Monitori

10、ng Report is an independent annual publication.The GEM Report is funded by a group of governments,multilateral agencies and private foundations and facilitated and supported by UNESCO.The Education 2030 Incheon Declaration and Framework for Action specifies that the mandate of the Global Education M

11、onitoring Report is to be the mechanism for monitoring and reporting on SDG 4 and on education in the other SDGs with the responsibility to report on the implementation of national and international strategies to help hold all relevant partners to account for their commitments as part of the overall

12、 SDG follow-up and review.It is prepared by an independent team hosted by UNESCO.The designations employed and the presentation of the material in this publication do not imply the expression of any opinion whatsoever on the part of UNESCO concerning the legal status of any country,territory,city or

13、 area,or of its authorities,or concerning the delimitation of its frontiers or boundaries.The Global Education Monitoring Report team is responsible for the choice and the presentation of the facts contained in this book and for the opinions expressed therein,which are not necessarily those of UNESC

14、O and do not commit the Organization.Overall responsibility for the views and opinions expressed in the Report is taken by its Director.The Global Education Monitoring Report teamDirector:Manos AntoninisBenjamin Alcott,Samaher Al Hadheri,Daniel April,Bilal Fouad Barakat,Marcela Barrios Rivera,Yekate

15、rina Baskakova,Madeleine Barry,Yasmine Bekkouche,Daniel Caro Vasquez,Anna Cristina DAddio,Dmitri Davydov,Francesca Endrizzi,Stephen Flynn,Lara Gil,Chandni Jain,Priyadarshani Joshi,Maria-Rafaela Kaldi,Josephine Kiyenje,Kate Linkins,Camila Lima De Moraes,Alice Lucatello,Kassiani Lythrangomitis,Anissa

16、Mechtar,Patrick Montjourids,Claudine Mukizwa,Yuki Murakami,Manuela Pombo Polanco,Judith Randrianatoavina,Kate Redman,Maria Rojnov,Divya Sharma,Laura Stipanovic,Dorothy Wang and Elsa Weill.The 2024 Gender Report tells the increasingly positive story of girls education access,attainment and achievemen

17、t,which is helping reverse decades of discrimination.But there is much more to say on gender equality in and through education.A companion to the 2023 GEM Report,this report looks at the interaction between education and technology with a gender lens.First,it looks at the impact of technology on gir

18、ls education opportunities and outcomes.Although many instances are seen of radio,television and mobile phones providing a learning lifeline for girls,particularly in crisis contexts,gender divides exist globally in both access to technology and in digital skills,although the latter are smaller amon

19、g youth compared to among adults.Biased social and cultural norms inhibit equitable access to and engagement with technology in and outside of school,with girls always left on the wrong side of the divide.While technology offers many girls opportunities to access important education content in safe

20、environments,for instance on comprehensive sexuality education,technology in practice often exacerbates negative gender norms or stereotypes.Social media usage impacts learners and particularly girls well-being and self-esteem.The ease with which cyberbullying can be magnified through the use of onl

21、ine devices in the school environment is a cause of concern,as is the biased design of artificial intelligence algorithms.Second,the report looks into the role of education on the shape of future technological development.It shows that women struggle to pursue STEM careers,which manifests from an ea

22、rly age in the form of anxiety in mathematics and develops into a reluctance to study STEM subjects,ultimately resulting in a lack of women in the technology workforce.Women make up only 35%STEM graduates,and hold only a quarter of science,engineering and ICT jobs.Ensuring women participate on equal

23、 terms in shaping the worlds ongoing digital transformation will ensure that technology works for everyone and takes into consideration the needs of all humanity.Since wars begin in the minds of men and women,it is in the minds of men and women that the defenses of peace must be constructedWhat role

24、 can education play in determining whether technological development is gender equal?SHORT SUMMARYThe share of women among STEM graduates is 35%and has not changed in the past 10 years.v2024GLOBAL EDUCATION MONITORING REPORTGENDER REPORTTechnology on her termsForewordTechnology is a tool.It promises

25、 easier access to education;personalized and enriched learning experiences.Yet,technology is not yet gender neutral.This Global Education Monitoring report,Technology on Her Terms,tells us a lot about technology in education,especially its role in replicating and amplifying gender biases.First,our r

26、eport underlines that men and women have unequal access to information and communication technologies:130 million fewer women than men own a mobile phone,for instance,and 244 million fewer women have Internet access worldwide even though digital tools can be a lifeline for girls and women in rural z

27、ones,poorer areas,and crisis situations.Moreover,according to this report,not only are some women and girls unable to access the learning opportunities that the digital transformation may offer,but they are also unable to help shape it on an equal footing.Indeed,women are currently underrepresented

28、in the technological design and deployment process:in 2022,women held less than 25 per cent of science,engineering and information and communication technology jobs.Today,they represent only 26 per cent of employees in data and artificial intelligence.This lack of representativity has real consequen

29、ces on algorithms and data sources,which perpetuate and amplify gender biases.With all too predictable results:according to a recent UNESCO study of generative AI models,a woman is described as a“model”or a“waitress”in 30 per cent of automatically generated texts,while male names are associated with

30、 terms such as“business”and“career”.This situation is also due to pernicious and powerful prejudices among content generators:negative stereotypes paint science,technology,engineering and mathematic as male-oriented fields,causing girls and young women to veer away from STEM career tracks despite th

31、eir very real capabilities in these domains.These stereotypes are also widespread on social media,which girls spend more time on.Girls are therefore more at risk of being exposed to content promoting gendered professions,unrealistic body standards,the sharing of sexually explicit images,cyberbullyin

32、g all of which place added strain on their mental health and well-being,and in turn affect academic performance.All these factors create a feedback loop:where girls are exposed to negative gender norms,steered away from studying STEM subjects,and deprived of the opportunity to shape the very tools t

33、hat expose them to these stereotypes.The solution,as underlined in our report,starts with education,which plays a major role in re-balancing the gender dimension of technology.Reducing exposure to social media and negative gender stereotypes.Encouraging more girls to study towards scientific careers

34、 through women role models in STEM fields.Ensuring that technological applications are no longer predominantly designed by men.These are some of the recommendations set out in the following pages,which UNESCO is already urging policymakers to implement.For example,our Recommendation on the Ethics of

35、 Artificial Intelligence,adopted unanimously by our Member States in November 2021,establishes a clear ethical framework that incorporates the continuous monitoring and evaluation of systemic biases in AI.Our Recommendation also underlines the importance of media and information literacy,to enable u

36、sers of AI tools to think critically and deconstruct stereotypes.viiiG LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTIn addition,UNESCO recently launched Women4Ethical AI,a collaborative platform to ensure that women are represented equally in the design and deplo

37、yment process.And,every day,we train teachers to transmit their passion for science to girls and women so they can become future actors in these fields.Ultimately,the main lesson of our report is this:technological progress may support educational and social progress but only if we are the masters o

38、f technological tools,rather than their servants.Only if we leverage technology in education,on our terms.Audrey Azoulay Director-General of UNESCOixG LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTShort summary.v Foreword.viiiContents.xiContentsTechnology on her t

39、erms CHAPTER 1.What progress was achieved by the SDG midpoint?.5Globally,there is gender parity in participation and completion.6African girls who start school late or repeat grades are more likely to leave school early.8Countries follow various trajectories towards or away from parity.11Parity for

40、some does not mean parity for all.13Gender disparity in learning varies among average and top students.13The tertiary education participation gender gap is growing.17There is a gender gap in TVET but not in adult education and training.18Gender gaps in adult literacy are also disappearing.20Girls ne

41、ed separate sanitation facilities in schools.22Women dominate the teaching profession but there is large variation.23CHAPTER 2.Technology affects girls education opportunities and outcomes .25Girls are often on the wrong side of the digital divide.28Gender gaps in digital skills are rapidly changing

42、.30Technology can affect gender norms positively and negatively.33Technology facilitates access to comprehensive sexuality education.33Social media negatively affects well-being and reinforces gender norms.35Technology can promote school-related gender-based violence.37Countries are beginning to tak

43、e actions to tackle digital risks.38CHAPTER 3.Education can determine whether technological development is gender equal.40Girls confidence in STEM subjects is harmed early.41Gender and social identities and stereotypes shape STEM aspirations.45Teacher and textbook biases can negatively affect girls

44、aspirations.46Countries are trying to reduce gender disparity in STEM.47CHAPTER 4.Conclusion.49xiG LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTKEY MESSAGESWhat progress was achieved by the SDG midpoint?Although pockets of extreme exclusion persist,on average gir

45、ls tend to do as well in school,if not better than boys.Gender parity in enrolment was achieved in primary and lower secondary education in 2009 and in upper secondary education in 2013,which has been maintained ever since.But in sub-Saharan Africa,gender parity has not been achieved at any level of

46、 education.More girls are out of school than boys.Girls who start school late or repeat grades in the region are also far more likely than boys to leave school early.Pockets of extreme exclusion for girls and young women persist in poor countries,including the Democratic Republic of the Congo,Nigeri

47、a and Pakistan,where there is gender parity in school attendance among the richest but substantial disparity among the poorest.In technical and vocational education and training,of the 146 countries with data,40 have a sizeable gap in favour of males in contrast to just 3 in favour of females.In ter

48、tiary education,parity was achieved in 1998,but by 2004,disparity started at the expense of men:by 2020,there were 114 women enrolled for every 100 men.Yet male students are still more likely to study abroad.Countries are moving further away from their national SDG 4 benchmarks on gender parity in s

49、econdary education completion.In total,36%of countries have set a national target on this gender gap,the lowest rate of all benchmark indicators.For countries where fewer young women than men were completing upper secondary school in 2015,the gender gap in completion rates fell from 6.9 to 4.2 perce

50、ntage points in 2022 but should have fallen to just 1 point if countries had been on track.For countries where fewer young men than women were completing upper secondary school in 2015,the gender gap in completion rates increased from 6.8 to 9.5 percentage points in 2022,when it should have fallen t

51、o 5.5 points if countries had been on track.Examining the gender gap in learning achievement not only at average but also at high levels of performance provides important insights.In reading,globally,for every 100 boys,there are 115 girls proficient at the end of lower secondary education.In science

52、 and mathematics,there is near parity at average levels of learning achievement,but boys have an advantage over girls at the higher levels of achievement.Technology affects girls education opportunities and outcomesICT can overcome barriers to education access for girls in crisis contexts.Radio and

53、mobile phones have provided an education lifeline for girls banned from going to school in Afghanistan or affected by the Boko Haram crisis in Nigeria.Some features in technology design can help overcome barriers to education faced by girls.In Kenya,the M-shule platform delivers education through te

54、xt messages on low-tech mobile phones with no need for an Internet connection.1G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTGirls and women are on the wrong side of the digital divide.Girls and women are less able to access technology.For instance,81%of men and

55、 75%of women owned a mobile phone in 2023.In Pakistan,22%of women without a phone cited lack of family approval as the primary obstacle,compared to 4%of men.There are 244 million fewer women than men using the Internet worldwide.A survey of girls and their parents in Ethiopia,India,Jordan,Kenya,Nige

56、ria,Rwanda and the United Republic of Tanzania showed that parents tended to believe that girls require more protection than boys from potential online distractions and temptations.There are large gender gaps in digital skills,but they are changing rapidly.The prevalence in the youth population of s

57、preadsheet skills is about 1%in low-,14%in lower-middle-,33%in upper-middle-and 57%in high-income countries.The average gender parity index is slightly less unfavourable for young women(0.91)than for adult women(0.82).But countries vary:for every 100 young men with spreadsheet skills,there are only

58、40 young women in Chad but 117 young women in Egypt with such skills.The prevalence in the youth population of programming skills is about 0.5%in low-,2%in lower-middle-,6%in upper-middle-and 14%in high-income countries.While the average gender parity index is less unfavourable for young women(0.75)

59、than for adult women(0.50),the disparity remains very large.For every 100 young men with programming skills,there are only 21 young women in Ireland,24 in Hungary and 28 in Austria but 110 young women in Saudi Arabia,118 in Albania and 130 in the State of Palestine with such skills.Technology can he

60、lp youth access sexuality education that might not be available elsewhere.Technology provides a safe and confidential environment for learning about sexuality.The Girl Talk app increased the sexual health knowledge of girls aged 12 to 18.Thailand has e-learning courses for teachers to learn about se

61、xuality education.Radio and television have been proven to enhance knowledge on sexual and reproductive health rights.A radio drama in Nepal motivated 11%of those who listened to seek family planning services.Regular listeners of a BBC radio programme in Sierra Leone had a better understanding of th

62、e risks of child marriage.Social media negatively affects well-being and reinforces gender norms.Girls are twice as likely as boys to suffer an eating disorder,which is exacerbated by the use of social media.Facebooks own research found that 32%of teenage girls said that when they felt bad about the

63、ir bodies,Instagram made them feel worse.TikToks algorithm targets teenagers with body image and mental health content every 39 seconds,and with content related to eating disorders every 8 minutes.In the United States,many universities have explicitly banned TikTok from campus.Greater interaction on

64、 social media at age 10 is associated with worsening socioemotional difficulties with age among girls,while no cross-associations were found among boys.Emotional well-being is linked to better academic outcomes.One longitudinal study of families in England found that children with better emotional w

65、ell-being made more progress in primary school and were more engaged in secondary school.2G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTTechnology allows for cyberbullying,including through image abuse.Cyberbullying is common,and more so for girls and non-binary

66、 students.A global poll of children aged 7 to 18 showed that a higher share of those of unspecified gender(50%)than girls(37%)and boys(29%)consider it very likely they will encounter online harm.Image abuse is common.A third of undergraduate female students in Canada and 88%of girls surveyed in Unit

67、ed Kingdom schools and colleges said that they had been sent pictures or videos they did not want to see.The danger of deepfakes made by artificial intelligence is spilling over into school environments.In Brazil and Spain,for instance,schoolgirls have been victims of deepfake pornographic images ci

68、rculating in schools,while female teachers have been recorded as victims of the abuse in the United States.Education can determine whether technological development is gender equalGirls confidence in STEM subjects is harmed early.Girls were found to be significantly less confident in mathematics tha

69、n boys in all but two education systems that participated in the 2019 TIMSS survey.Girls who are more anxious in mathematics are less likely to perform well.At least a quarter of the variation in mathematics performance across countries could be explained by the differences in overall mathematics an

70、xiety in each country.Boys and girls educational trajectories diverge at around the age when they start deciding about their careers.In Canada and Ireland,for example,different subject choices among boys and girls in secondary school explain most of the subsequent gender gap.Girls are far less likel

71、y to study STEM subjects despite concerted efforts.In 201823,the share of STEM graduates who were female was 35%.Only in 9 out of 122 countries were the majority of STEM graduates female,notably Arab States,such as the Syrian Arab Republic and Tunisia.High shares of female STEM graduates in Arab cou

72、ntries coincide with lower mathematics anxiety.For a subset of 50 countries with data for 201011 and 202021,there has been no change in the share of STEM graduates who are female.There are notable examples of decline:Hungary(by 5 percentage points to 29%),stagnation(e.g.Chile where the share has rem

73、ained at 20%)and improvements,such as North Macedonia(from 40%to 50%),the Netherlands(from 21%to 31%)and Morocco(from 39%to 49%).There is a large gender gap in tertiary field choices.The average share of STEM is 15%among young female graduates and 35%among young male graduates.Countries with the lar

74、gest absolute gaps include Finland,Germany and Sweden,while Mauritania,Samoa and the United Republic of Tanzania are among the few countries with no gap.Countries are adopting various approaches to address gender divides.However,while 68%of countries globally have policies to support STEM education,

75、only half of these policies specifically support girls and women.Gender gaps in STEM crystallize in gender imbalances in the technology workforce.Women are far less likely to pursue STEM careers.Women held less than 25%of science,engineering and ICT jobs in 2022 and occupy just over one in five tech

76、nology positions in companies.In 2022,only 17%of patent applications were filed by women globally.The digital transformation is led by men.Women constitute only 26%of employees in data and artificial intelligence,15%in engineering,and 12%in cloud computing across the worlds leading economies.A lack

77、of women in the technology workforce is an economic loss to society.Doubling the share of women in the tech workforce by 2027 could boost GDP by EUR 600 billion.3G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTNegative gender stereotypes impact on girls STEM aspir

78、ations.Study choice can,but not always determines,career choice.Taking a computer science course in secondary school can increase the chances of majoring in computer science by 10 percentage points.Still,only one in four women with an IT degree technology took up digital occupations in the European

79、Union,compared with over one in two men.Low expectations from parents and teachers can reinforce gender segregation.In Denmark,having a mother who is STEM-educated helps mitigate potential negative peer effects.Teachers may not always have a positive influence.In Latin America,up to 20%of mathematic

80、s teachers reported believing that their subject is easier for boys.4G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTWhat progress was achieved by the SDG midpoint?The midpoint in the implementation of the 2030 Agenda for Sustainable Development was marked in Sept

81、ember 2023 at the SDG Summit.There is a lag in education data production,but up-to-date reporting was further hampered by the fact that education data collection processes had been tested by the COVID-19 pandemic disruptions.The ultimate effects of school closures on education systems will remain ha

82、rd to determine for a few more years.In the case of learning achievement,the first evidence from the worlds richer countries documents a negative medium-term effect but it was less dramatic than feared.The long-term impact on learning will remain difficult to assess,as no shock of that magnitude had

83、 ever been experienced before.In the case of education participation and attainment,the data that emerge do not suggest a visible impact.A bigger issue may be,rather,that progress in access to education has almost ground to a halt over the past 10 years.This first part of the 2024 Gender Report revi

84、ews progress on gender parity in education for most SDG 4 targets.Despite the kaleidoscopic range of possibilities to look at gender disparity(Box 1),the report documents the continuing growth in girls and young womens participation in education at different levels,which has helped reverse decades o

85、f discrimination.It also suggests that this long-term trend is going to continue,increasingly putting disadvantaged boys and young men at a worse relative position.But this is not a reason to lose focus on those countries where girls continue to lose out on education opportunities,a predicament that

86、 is not limited to Afghanistan.Last but not least,as this series of reports has Aichata Togo,a 15-year-old 9th grader,takes her lessons on the radio.To enable pupils to follow the school curriculum,lessons are given on the national radio so that children can attend school from home.Thanks to COVID-1

87、9 broadcasts,Aichata and many other children have been able to follow their school curriculum and save their school year.Mopti region,central Mali.Credit:UNICEF/UN0431560/Keta5continued to stress,parity is but one part of the effort for gender equality in and through education.With gender gaps in a

88、wide range of social and economic outcomes,the role that education can play in that respect needs to be constantly reassessed and reconsidered.GLOBALLY,THERE IS GENDER PARITY IN PARTICIPATION AND COMPLETION One of the most notable successes in the implementation of the international education agenda

89、 over the past 30 years has been the move towards gender parity in education.The world achieved gender parity in primary and lower secondary education enrolment in 2009 and in upper secondary education in 2013.Tertiary education progress has been different.Parity was achieved a decade earlier,in 199

90、8,but by 2004,there was already disparity at the expense of men,which has continued to increase:by 2020,there were 114 women enrolled for every 100 men.The one exception to this success has been sub-Saharan Africa where parity has not been achieved at any level of education.As of 2020,for every 100

91、males,there were 96 females enrolled in primary,91 in lower secondary,87 in upper secondary and 80 in tertiary education.Conditions for girls and young women worsened during the period of structural adjustment in the 1990s and disparity increased in secondary education.The 1997 level of the gender p

92、arity index in lower secondary enrolment did not recover until 2010.The 1999 level of the gender parity index in upper secondary enrolment did not recover until 2013.But between 2015 and 2020,the gender parity index in upper secondary enrolment improved at the fastest rate ever observed,by 0.012 poi

93、nts per year.Similar levels of progress have been achieved in tertiary education(Figure 1).In absolute numbers,sub-Saharan Africa is the main world region where there are more girls of primary and secondary school age who are out of school than boys and the out-of-school population is growing.Global

94、ly,9 out of the 10 countries with the highest out-of-school rates are in the region(Box 2).In Northern Africa and Western Asia,it is estimated that the number of out-of-school boys may have just exceeded the number of out-of-school girls in 2022.In Central and Southern Asia,a long trend of a rapidly

95、 declining out-of-school population came to an end in 2022 as a result of the crisis in Afghanistan.In sub-Saharan Africa,slow declines in out-of-school rates mean that the out-of-school population has been rising.Since 2008,it is estimated that the number of out-of-school boys increased by 12 milli

96、on to 48 million and the number of out-of-school girls increased by 9 million to 51 million.Globally,between 2000 and 2022,the number of out-of-school boys has fallen by 35%to 128 million,while the number of out-of-school girls has fallen by 41%to 122 million(Figure 2).BOX 1:The global SDG 4 indicat

97、or on disparity is insightful but may not give the full pictureGlobal indicator 4.5.1,the parity index that compares the education status of two groups,one disadvantaged and one privileged,is defined in terms of other global education indicators(pletion or learning),at various education levels(e.g.p

98、rimary or secondary),and for various individual characteristics(e.g.sex or wealth).The potential combinations are so numerous that it is very difficult to talk of one trend.It is particularly challenging to make global comparisons in terms of characteristics whose definitions vary between countries.

99、For example,definitions of urban and rural are not the same between countries,and neither are definitions of poor and rich.The latter definition may be based on income,consumption or wealth,with each concept having different meanings and leading to different conclusions.In the case of gender dispari

100、ty,global indicator 4.5.1 is more straightforward to interpret.Yet it only provides the relative disadvantage between males and females,while masking the absolute disadvantage.For instance,the gender parity index for the gross graduation rate from tertiary education was 0.56 in Burkina Faso,which me

101、ant that males were graduating at almost twice the rate as females,the lowest in the world.But at gross graduation rates of 3.7%for males and 2.1%for females,it is clear that the main issue is not disparity but low overall levels of tertiary enrolment and graduation.The parity index is important but

102、 needs to be reviewed jointly along with the actual levels of the indicator.It is more insightful to compare the parity index among countries which are at similar levels of the analysed education indicator,a logic used in relation to the national SDG 4 benchmarks(Box 3).6G LO BA L E D U C AT I O N M

103、 O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTFIGURE 1:Sub-Saharan Africa has not achieved gender parity in enrolment at any education levelAdjusted gender parity index of the gross enrolment ratio by education level,world and sub-Saharan Africa,19902020 1990 1995 2000 2005 2010 2015 20201

104、990 1995 2000 2005 2010 2015 20201990 1995 2000 2005 2010 2015 2020ParityWorldSub-Saharan Africa0.50.60.70.80.91.01.11.21990 1995 2000 2005 2010 2015 2020Adjusted gender parity indexSource:UIS database.FIGURE 2:Sub-Saharan Africa is the only world region where there are more girls are out of school

105、and the out-of-school population is growingOut-of-school population of primary and secondary school age,world and selected regions,200022 100 120 140 160 180 200 22020002005201020152020 30 35 40 45 50 55 6020002005201020152020 5 7 9 11 13 15 1720002005201020152020 40 50 60 70 80 90 10020002005201020

106、152020MaleFemaleSource:VIEW database.a.PrimaryCentral and Southern AsiaNorthern Africa and Western AsiaSub-Saharan AfricaWorldb.Lower secondaryc.Upper secondaryd.Tertiary7G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTThree aspects of these average trends of disp

107、arity need further examination:disparity in completion(rather than in enrolment);differences in countries historic trajectories;and differences between the average population and selected groups where sex intersects with other factors of disadvantage.AFRICAN GIRLS WHO START SCHOOL LATE OR REPEAT GRA

108、DES ARE MORE LIKELY TO LEAVE SCHOOL EARLY First,enrolment is only a stepping stone towards completion.Gender disparity in completion rates tends to be larger than in enrolment rates for disadvantaged groups.But there is also a big difference in gender disparity between completing an education cycle

109、on time or not,especially in sub-Saharan Africa.Global SDG indicator 4.1.2 is the completion rate for those 3 to 5 years above graduation age(timely completion)but in sub-Saharan Africa,more than in any other world region,many children and young people complete each cycle even later than that(ultima

110、te completion).In primary education,there is gender parity in both the timely and ultimate completion rates,globally,while the same is true in Central and Southern Asia,which is used here as a reference region.But in sub-Saharan Africa since 2013,girls have been far more likely than boys to complete

111、 primary school on time.In contrast,girls are still less likely to ultimately complete primary school than boys:96 girls complete for every 100 boys who do so(Figure 4a).In lower secondary education,there is gender parity in both timely and ultimate completion rates,globally,and also in Central and

112、Southern Asia since 2020.In sub-Saharan Africa,gender parity in timely completion has almost been achieved,but girls are at a much bigger disadvantage in ultimate completion:85 girls complete for every 100 boys who do so.This means that if girls start school on time and do not repeat grades,so that

113、they are not too old for their grade,they are currently almost as likely as boys to complete lower secondary school as boys.But because of the problems of late entry and repetition,if they reach the age of 15 and have still not reached the end of lower secondary school,they are more likely to drop o

114、ut(Figure 4b).BOX 2:These are the 10 countries with the highest rates of education exclusion for girlsData gaps in some of the countries with the lowest levels of education development mean it can be difficult to list the countries with the lowest education access rates for girls.A recent estimation

115、 model that makes efficient use of available information for all countries shows that 9 of the 10 countries with the highest out-of-school rates for girls are in sub-Saharan Africa,the 10th country being Afghanistan.In the median country,49%of primary school age,59%of lower secondary school age and

116、74%of upper secondary school age girls are out of school(Figure 3).Somalia would almost certainly have replaced Djibouti in this list if data were available.FIGURE 3:Apart from Afghanistan,9 of the 10 countries with the highest education exclusion rates for girls are in sub-Saharan AfricaTen countri

117、es with the highest out-of-school rates for girls,by age group,2022PrimaryLower secondaryUpper secondaryTotal0102030405060708090100DjiboutiGuineaMaliC.A.R.ChadEquat.GuineaNigerEritreaSouth SudanAfghanistanOut-of-school rate(%)Source:VIEW database.Among countries with disaggregated data from househol

118、d surveys in the past five years,it is also possible to show the situation of the poorest girls facing the most extreme disadvantages.In Guinea and Mali,practically no poor young women are in school,putting them in the same situation as their Afghan sisters,who are officially banned from attending s

119、chool.8G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTIn upper secondary education,gender parity was achieved globally in timely completion in 2010 but by 2018 there was reverse disparity and as of 2020 there were 96 young men completing upper secondary school fo

120、r every 100 young women.Parity was achieved in ultimate completion in 2013 and has been maintained.But it must be noted that that this is an average of different tendencies.Of 163 countries with data,only 24%achieved parity in 2020,while 27%had a disparity at the expense of young women and 49%a(smal

121、ler)disparity at the expense of young men.In Central and Southern Asia,for every 100 young men who completed upper secondary school on time there were 68 young women in 2000 increasing to 93 in 2020.There is no difference in disparity between timely and ultimate completion.Sub-Saharan Africa started

122、 from a more equal position(75 young women completed for every 100 young men in 2000)but progressed at half the rate(87 young women for every 100 young men in 2020)and has fallen behind Central and Southern Asia.On the positive side,the rate of progress was twice as fast in 200820 than in 200008.But

123、 gender disparity is much higher in the ultimate completion rate:78 young women complete for every 100 young men who do so(Figure 4c).Young women who do not finish upper secondary school on time are more likely to leave school early,under pressure to marry and have children,while young men can affor

124、d to persevere with their education for a little longer to obtain the upper secondary education certificate.There has been no progress at all in closing this gap in the past 20 years.By contrast,this problem is not present at all in Central and Southern Asia,which is one of the reasons that helps ex

125、plain the faster progress of the region in closing the gender gap.FIGURE 4:In sub-Saharan Africa,girls are relatively more likely than boys to complete each school cycle on time Adjusted gender parity index of the timely and ultimate completion rate,200020 TimelyUltimate0.60.70.80.91.01.11.220002005

126、201020152020Gender parity index0.60.70.80.91.01.11.220002005201020152020Gender parity index0.60.70.80.91.01.11.220002005201020152020Adjusted gender parity indexParitya.PrimaryCentral and Southern AsiaWorldSub-Saharan Africa9G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R

127、E P O RTFIGURE 4 CONTINUED:0.60.70.80.91.01.11.220002005201020152020Gender parity index0.60.70.80.91.01.11.220002005201020152020Gender parity index0.60.70.80.91.01.11.220002005201020152020Adjusted gender parity indexParityTimelyUltimateTimelyUltimate0.60.70.80.91.01.11.220002005201020152020Gender pa

128、rity index0.60.70.80.91.01.11.220002005201020152020Gender parity index0.60.70.80.91.01.11.220002005201020152020Adjusted gender parity indexParitySource:VIEW database.b.Lower secondaryc.Upper secondaryCentral and Southern AsiaCentral and Southern AsiaWorldWorldSub-Saharan AfricaSub-Saharan Africa10G

129、LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTCOUNTRIES FOLLOW VARIOUS TRAJECTORIES TOWARDS OR AWAY FROM PARITY The second point to note is that countries trajectories depart from the global trend.Globally,the gender gap in the out-of-school rate among youth of up

130、per secondary school age fell from four percentage points in 2000 to zero in 2020.But it is possible to observe six patterns.Three have a starting point of an initial gap in favour of men,which remained constant(e.g.Guinea),declined(e.g.Sierra Leone)or reversed(e.g.Cambodia).One shows the maintenanc

131、e of parity throughout(e.g.Ecuador).The other two start with an initial gap in favour of women,which declined(e.g.Mongolia)or remained constant(e.g.the Philippines)(Figure 6).BOX 3:The gender gap in secondary completion is the only equity-oriented SDG 4 benchmark indicatorIn 2015,countries agreed in

132、 the Education 2030 Framework for Action,which is the roadmap for achieving SDG 4,to establish“appropriate intermediate benchmarks(e.g.for 2020 and 2025)”considering them as“indispensable for addressing the accountability deficit associated with longer-term targets”(UNESCO,2015).The UNESCO Institute

133、 for Statistics(UIS)and the Global Education Monitoring Report,which are jointly mandated by the Education 2030 Framework for Action to monitor progress towards SDG 4,have been helping countries to fulfil the commitment to set national SDG 4 benchmarks,defined as national targets for selected indica

134、tors to be achieved by 2025 and 2030.In 2019,the Technical Cooperation Group(TCG)on SDG 4 Indicators endorsed six SDG 4 benchmark indicators and decided that a seventh indicator should focus on equity.Following further deliberations in 202021,the TCG decided on the gender gap in upper secondary comp

135、letion rates as the seventh benchmark indicator.Note that the indicator is not the(relative)gender parity index(completion rate female/completion rate male)but the(absolute)gender gap(completion rate female completion rate male)because TCG members felt that the gap would be more transparent.While 70

136、%of countries have submitted a national target for the upper secondary completion rate,only 36%of countries have submitted a national target for the gender gap in upper secondary completion,the lowest submission rate of all benchmark indicators.There is no difference between the initial conditions o

137、f countries that did and did not submit national targets.The only plausible assumption is that countries are not used to the idea of setting an equity target and,faced for the first time with the task,they found it difficult to set a target,knowing they are unlikely to achieve parity.This is reflect

138、ed in the results of the second SDG 4 Scorecard,the annual monitoring report on progress towards the national SDG 4 benchmarks(UNESCO,2024).Reflecting the long-term trend towards more young women completing secondary school,countries in which fewer young women than men completed upper secondary scho

139、ol in 2015(on average a 6.9 percentage point gap)had reduced the gap to 4.2 percentage points by 2022,although the gap should have been just 1.0 percentage point if they had been on track to achieve their target.In contrast,countries in which fewer young men than women completed upper secondary scho

140、ol in 2015(on average a 6.8 percentage point gap)saw their gap increase to 9.5 percentage points,although the gap should have been 5.5 percentage points if they had been on track(Figure 5).In fact,the gender gap is the benchmark indicator with the largest percentage of countries moving away from the

141、ir target.FIGURE 5:Countries progress in closing the gender gap in secondary completion depends on their starting pointsCountries actual and needed progress to achieve their national benchmarks in the gender gap in upper secondary completion,by starting point 201522 -6.9-4.21.51.8-1.06.89.54.95.53.6

142、-10-5051020152020202220252030Female minus male completion rate(percentage points)ActualNeededCountries with disadvantage for boys in 2015National benchmarksCountries with disadvantage for girls in 2015Source:UNESCO(2024).11G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E

143、 P O RTFIGURE 6:Six country patterns can be observed in the evolution of the gender gap in upper secondary out-of-school ratesUpper secondary out-of-school rate,by sex,200020200020102020200020102020020406080100200020102020%FemaleMale200020102020200020102020020406080100200020102020%b.Sierra Leonee.Mo

144、ngoliaa.Guinead.Ecuadorc.Cambodiaf.Philippines12G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTFIGURE 6 CONTINUED:Initial gap in favour of menInitial parityInitial gap in favour of womenConstant DecreasingReversingConstant DecreasingReversingBenin,Cameroon,C.A.R,

145、Chad,Cte dIvoire,Eritrea,Ethiopia,Guinea-Bissau,Iraq,Mali,Mozambique,South Sudan,Togo,Yemen,Zambia Angola,D.R.Congo,TrkiyeBhutan,Comoros,Gambia,India,Nepal,Viet NamAlgeria,Armenia,Bolivia,Haiti,Kenya,Mexico,Rwanda,Saudi Arabia,South AfricaCosta Rica,Lao PDR,Saint Lucia,St Vincent/Grenad.,Suriname,Tr

146、inidad/Tobago,UruguayCabo Verde,Honduras,Jamaica,Malaysia,Mauritius,Philippines,Thailand,Venezuela,B.R.Source:VIEW database.PARITY FOR SOME DOES NOT MEAN PARITY FOR ALLThe third point about interpreting parity index values is that they only measure average disparity.While the situation of girls and

147、young women has improved rapidly in many countries,some are trapped in pockets of disadvantage due to location and poverty but also due to other social and cultural characteristics.For instance,in Mozambique,there are 73 young women in school for every 100 young men.But,while there is gender parity

148、in urban areas,in rural areas there are 53 young women in school for every 100 young men.In contrast,in the relatively few countries where young men are on average at a disadvantage,their disadvantage tends to be higher in rural areas,such as in Mongolia and Palestine(Figure 7a).The disparity is eve

149、n more exacerbated in terms of wealth.In a large number of low-and lower-middle-income countries,including the Democratic Republic of the Congo,Nigeria and Pakistan,there is gender parity in school attendance among the richest youth but substantial disparity among the poorest youth.In Cte dIvoire,th

150、ere are 72 young women in school for every 100 young men but only 22 poor young women in school for every 100 poor young men.Again,in the few countries where young men are at a disadvantage,their disadvantage tends to be higher among the poorest,such as in Bangladesh and Lesotho(Figure 7b).GENDER DI

151、SPARITY IN LEARNING VARIES AMONG AVERAGE AND TOP STUDENTSWhile girls and young women still face hurdles in education access and completion in many poor countries,gender gaps in learning outcomes are of a different kind.In reading,among 97 countries with data on the end of primary and of lower second

152、ary education in 201619,only two low-income countries had a tiny gap favouring boys:Chad and the Democratic Republic of the Congo.In the other 95 countries,the share of girls with minimum proficiency was an average of 10 percentage points higher than the share of boys.Globally,for every 100 proficie

153、nt boys,there are 115 proficient girls in reading at the end of lower secondary education.Boys have a small advantage over girls in mathematics in primary education,but this is reversed in lower secondary education.In the 2019 Trends in Mathematics and Science Study,the share of grade 4 boys with mi

154、nimum proficiency exceeded that of girls by 1.4 percentage points in 30 upper-middle and high-income countries.But by grade 8,it was girls that had a 1.4 percentage point advantage over boys(Figure 8a).In science,girls already have an advantage in grade 4(by 1.9 percentage points)which more than dou

155、bles by grade 8(4.3 percentage points)(Figure 8b).13G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTFIGURE 7:Young women in poor and rural households tend to be educationally more disadvantaged than the average learnerGender parity index of the attendance rate amo

156、ng youth of upper secondary school age,low-and lower-middle-income countries,201419 0.200.400.600.801.001.201.401.60AfghanistanGuineaChadCte dIvoireUgandaBeninZambiaMozambiquePakistanTajikistanCameroonGuatemalaSenegalAngolaEthiopiaCongoPapua N.GuineaSierra LeoneD.R.CongoMauritaniaGuinea-BissauSudanN

157、igeriaBelizeEgyptMadagascarBurundiGambiaNepalBoliviaS.Tome/PrincipeTimor-LesteMyanmarAlgeriaU.R.TanzaniaEswatiniZimbabweKenyaRwandaKyrgyzstanLesothoViet NamPhilippinesMongoliaBangladeshPalestineKiribatiAdjusted gender parity indexRuralTotalUrbanYoung women are at adisadvantage and urban youngwomen e

158、ven more so Young women are at adisadvantage and rural youngwomen even more so Young men are at adisadvantage and urban youngmen even more so Young men are at adisadvantage and rural youngmen even more so 0.200.400.600.801.001.201.401.60AfghanistanGuineaChadCte dIvoireUgandaBeninZambiaMozambiquePaki

159、stanCameroonGuatemalaSenegalMalawiAngolaEthiopiaCongoPapua N.GuineaSierra LeoneD.R.CongoMauritaniaGhanaSudanNigeriaBelizeEgyptMadagascarBurundiGambiaKyrgyzstanZimbabweCambodiaKenyaLesothoS.Tome/PrincipePhilippinesMongoliaBangladeshAdjusted gender parity indexPoorestTotalRichestYoung women are at adi

160、sadvantage and the poorestyoung women even more soYoung women are at adisadvantage and the richestyoung women even more soYoung men are at a disadvantage andthe poorest young men even more soSource:WIDE database.a.By locationb.By wealth14G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024

161、G E N D E R R E P O RTFIGURE 8:Girls performance in mathematics and science is improving relative to boys as they move from primary into lower secondary Femalemale gap in share of students achieving minimum proficiency level in mathematics and science,grade 4 and grade 8,2019-10-505101520CyprusPortu

162、galChileFranceItalyHungaryIran,Isl.Rep.U.A.EmiratesSwedenUnited StatesGeorgiaNew ZealandIrelandKuwaitQatarRussian Fed.LithuaniaAustraliaFinlandNorwayTrkiyeKazakhstanSingaporeRep.of KoreaHong Kong,ChinaJapanBahrainOmanSaudi ArabiaSouth AfricaFemale-male gap in minimum proficiency(percentage points)In

163、 Oman,grade 8 female students have a 14 percentage-pointadvantage over their male peers Grade 8-10-505101520ChileItalyGeorgiaPortugalHungaryIrelandCyprusUnited StatesRussian Fed.SingaporeIran,Isl.Rep.TrkiyeRep.of KoreaU.A.EmiratesHong Kong,ChinaSouth AfricaSwedenNorwayLithuaniaFranceNew ZealandQatar

164、FinlandAustraliaJapanKazakhstanOmanKuwaitBahrainSaudi ArabiaFemale-male gap in minimum proficiency(percentage points)In Oman,grade 8 female students have a 21 percentage-pointadvantage over their peers Grade 4Source:VIEW database.However,it should be noted that these gaps relate to the achievement o

165、f minimum proficiency,as suggested by data from 76 education systems that took part in the 2022 PISA survey.In reading,the adjusted gender parity index in the median country is higher among girls at a high level(Level 4 and above)of performance(1.23)than at the minimum level(1.15)(Figure 9a).But boy

166、s tend to have a considerable advantage over girls in science and mathematics at the higher end of performance.In science,the median adjusted gender parity index is 1.04 at the minimum level but 0.92 at the high level(Figure 9b).In mathematics,there is gender parity(1.00)at the minimum level of prof

167、iciency,but the adjusted gender parity index is only 0.75 at the high level of proficiency(Figure 9c).In the Dominican Republic and El Salvador,boys are five times more likely to be among the top performers,although this result should be put in the context that only 0.1%to 0.2%of students achieved t

168、hat level.a.Mathematicsb.Science15G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTFIGURE 9:The gender gap differs at average and top performance levelsAdjusted gender parity index in share of students achieving minimum and high proficiency level,15-year-olds,20220

169、.00.20.40.60.81.01.21.41.61.82.0Costa RicaChileEl SalvadorMexicoPeruIsraelAlbaniaBrazilJapanUnited KingdomSingaporeArgentinaMacao,ChinaHungaryMalaysiaUnited StatesFranceAustraliaKazakhstanItalyIrelandUkraineUruguayGermanyCanadaNew ZealandHong Kong,ChinaColombiaSwitzerlandViet NamPortugalGreeceNether

170、landsAustriaPhilippinesPolandSerbiaDenmarkTrkiyeRomaniaEstoniaU.A.EmiratesBrunei Daruss.BelgiumSpainQatarKoreaCzechiaSwedenBulgariaThailandSaudi ArabiaNorwayLithuaniaPanamaLatviaSlovakiaParaguayJamaicaMongoliaIndonesiaMaltaFinlandCroatiaRep.MoldovaIcelandSloveniaDominican Rep.GeorgiaMontenegroGuatem

171、alaNorth MacedoniaMoroccoPalestineUzbekistanJordanAdjusted gender parity indexLevel 2 and aboveLevel 4 and aboveGirls are doing better than boys Boys are doing better than girls 0.000.200.400.600.801.001.201.401.601.802.00CambodiaUzbekistanCosta RicaPeruMexicoEl SalvadorChileKazakhstanBrazilUruguayI

172、talyArgentinaViet NamRomaniaColombiaMalaysiaIsraelGeorgiaMontenegroParaguayUkraineDominican Rep.ThailandPanamaPhilippinesIrelandUnited StatesSpainDenmarkHungaryAustriaSerbiaUnited KingdomLatviaFranceRep.MoldovaAustraliaIndonesiaGermanyPolandHong Kong,ChinaPortugalGreeceSwitzerlandNew ZealandCanadaNe

173、therlandsSingaporeJapanBelgiumBrunei Daruss.CzechiaSaudi ArabiaMacao,ChinaTrkiyeKoreaLithuaniaSwedenEstoniaBulgariaGuatemalaU.A.EmiratesMaltaNorwayMoroccoSlovakiaQatarJamaicaCroatiaIcelandSloveniaMongoliaNorth MacedoniaAlbaniaFinlandPalestineJordanAdjusted gender parity indexLevel 2 and aboveLevel 4

174、 and abovea.Readingb.Science16G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTFIGURE 9 CONTINUED:Dominican Rep.El SalvadorPanamaUzbekistanSaudi ArabiaPhilippinesCosta RicaPeruColombiaArgentinaChileMexicoBrazilGuatemalaMoroccoCambodiaItalyParaguayUruguayUkraineIsra

175、elKazakhstanMontenegroGreeceSerbiaRep.MoldovaJamaicaGeorgiaRomaniaUnited StatesHungaryAlbaniaAustriaIrelandFranceViet NamPortugalLatviaUnited KingdomDenmarkSpainQatarNew ZealandMalaysiaIcelandAustraliaGermanyBulgariaThailandCroatiaU.A.EmiratesCanadaNorth MacedoniaTrkiyePolandLithuaniaCzechiaMaltaNor

176、wayBelgiumSwitzerlandSwedenMacao,ChinaJapanNetherlandsEstoniaBrunei Daruss.Hong Kong,ChinaSlovakiaRep.of KoreaMongoliaSingaporeSloveniaFinlandPalestineIndonesiaJordanAdjusted gender parity index0.000.200.400.600.801.001.201.401.601.802.00Level 2 and aboveLevel 4 and aboveSource:WIDE database,GEM Rep

177、ort team analysis of 2022 PISA data.c.MathematicsTHE TERTIARY EDUCATION PARTICIPATION GENDER GAP IS GROWINGIndicator 4.3.2 is the gross enrolment ratio for tertiary education.It divides the number of people enrolled in tertiary education,regardless of age,by the number of people within five years of

178、 the standard age for upper-secondary completion(usually 19 to 23 years old).However,the indicator does not account for differences in the duration of programmes between countries(for example,whether a bachelors degree typically takes three or five years).Moreover,the indicator does not distinguish

179、between different levels of tertiary education.For example,two countries with similar enrolment ratios might have quite different profiles,with one having far more people studying in short-cycle or long-cycle programmes or even in postgraduate degrees.Global enrolment in tertiary education grew over

180、 the previous decade,but at a slower pace after 2015:the gross enrolment ratio increased from 29%in 2010 to 37%in 2015,but only to 40%five years later.Gross enrolment ratios range from below 1%in South Sudan to over 150%in Greece,where many are still enrolled to maintain certain social benefits even

181、 though they are not actually attending.At the lower end,16 countries have a female gross enrolment ratio below 10%,all of which are in sub-Saharan Africa except Afghanistan,even before the Taliban government banned tertiary education for women.In most countries,females are more likely than males to

182、 be enrolled in tertiary education.In 2020,the gross enrolment ratio for women was 43%compared to 37%for men.Of the 146 countries with data,106 have a gap in favour of females and 30 22 of which are in sub-Saharan Africa have a gap in favour of males.The higher the rate of tertiary enrolment,the mor

183、e likely there is to be a gap in favour of females.Of the 50 countries with the highest enrolment ratios,only the Republic of Korea has a sizeable gap in favour of males,compared to 47 countries with a sizeable gap in favour of females(Figure 10).17G LO BA L E D U C AT I O N M O N I TO R I N G R E P

184、 O RT 2 024G E N D E R R E P O RTFIGURE 10:There is a large gender gap in tertiary education participation Gross enrolment ratio for tertiary education,by sex,201822020406080100120MalawiMaliMauritaniaD.R.CongoAfghanistanMozambiqueU.R.TanzaniaEthiopiaNigeriaPakistanSt Vincent/Grenad.CameroonTurkmenis

185、tanGhanaNepalLuxembourgSt LuciaBangladeshGabonGuatemalaSri LankaMarshall IsCabo VerdeSouth AfricaBotswanaEl SalvadorNamibiaViet NamBrunei Daruss.Br.Virgin IsAzerbaijanSyrian A.R.MexicoMalaysiaThailandSan MarinoPalestineIran,Isl.Rep.EcuadorKyrgyzstanHungaryCosta RicaFijiMontenegroU.A.EmiratesSwitzerl

186、andChinaAlbaniaIsraelGermanyKazakhstanGeorgiaCroatiaItalyKuwaitMongoliaMaltaBulgariaBelarusCanadaRep.of KoreaHong Kong,ChinaDenmarkNew ZealandSingaporeChileUnited StatesFinlandSpainIcelandArgentina%FemaleMale126%Source:UIS database.Yet the gender gaps are in the opposite direction in terms of intern

187、ationally mobile students.The inbound mobility rate,which is the number of students from abroad studying in a country expressed as a percentage of total tertiary enrolment in that country,shows that male students are more likely to travel for studies.Globally,student mobility increased from 2.2%in 2

188、015 to 2.7%in 2020 before experiencing a decline due to COVID-19.Mobility increased in all regions except sub-Saharan Africa.But the gender parity index of mobile students fell globally from 0.89 in 2010 to 0.85 in 2015 and 0.82 in 2020.It was even lower in Europe and Northern America(0.77)and espec

189、ially Northern Africa and Western Asia(0.55).The only region where female students are more mobile than male students is sub-Saharan Africa(Figure 11).THERE IS A GENDER GAP IN TVET BUT NOT IN ADULT EDUCATION AND TRAININGIndicator 4.3.3,which measures the participation rate in technical-vocational ed

190、ucation among 15-to 24-year-olds,regardless of whether they are at the secondary,post-secondary,non-tertiary or tertiary levels,shows a contrasting situation.Unlike indicator 4.3.2 on tertiary education,which counts participation regardless of age,this indicator only counts participation among youth

191、s in this particular age range.In contrast to tertiary education,the gender gap in technical-vocational education is smaller and tends to favour males.Of the 146 countries with data,40 have a sizeable gap in favour of males(in excess of 3 percentage points)in contrast to just 3 countries(Curaao,Isra

192、el and Seychelles)in favour of females.Across countries,participation in technical-vocational programmes ranges from zero to 36%.The lowest participation rates(less than 10%)are found primarily in the Caribbean,the Pacific and sub-Saharan Africa.The highest rates(more than 25%)are found almost exclu

193、sively in Europe,the exceptions being the Plurinational State of Bolivia,Seychelles,Singapore and Uzbekistan.18G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTFIGURE 11:More men than women tertiary students are internationally mobile Inbound mobility rate,region a

194、nd by sex,20002100.51.01.52.02.53.020002005201020152020%WorldEastern and South-eastern Asia01234520002005201020152020%Northern Africa and Western AsiaSub-Saharan AfricaLatin America and the CaribbeanCentral and Southern AsiaFemaleMale0510152025303520002005201020152020%OceaniaEurope and Northern Amer

195、icaSource:UIS database.19G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTGlobal indicator 4.3.1 focuses on the participation rate of youth and adults in formal and non-formal education and training in the previous 12 months.While participation in formal education

196、and training can be measured by asking both providers and beneficiaries,non-formal education and training opportunities can only be estimated systematically by asking those who benefit from them.The data that inform this indicator,therefore,primarily come from labour force surveys compiled by the In

197、ternational Labour Organization and analysed by the UNESCO Institute for Statistics.For adults aged 25 to 54,the median participation rate in formal and non-formal education and training across 115 countries with recent data is 3%,ranging from 2%in low-and lower-middle-income countries to 3%in upper

198、-middle-income countries and 7%in high-income countries.In Europe,the median is 8%;all countries with participation rates above 10%are in this region.Globally,there is gender parity in participation rates with males at 3.1%and females at 3%.Of the 113 countries with data by sex,only 6 have a gender

199、gap of more than 5 percentage points,and in all cases,it is in favour of females.All but one of them are located in northern Europe(Denmark,Estonia,Finland,Iceland and Sweden,which has the largest gap of 14 percentage points);the other country is the Dominican Republic.GENDER GAPS IN ADULT LITERACY

200、ARE ALSO DISAPPEARINGGlobally,the youth literacy rate increased from 87%in 2000 to 91%in 2015,but only by 0.8 percentage points in the five years to 2020.The number of illiterate youth fell from 107 million in 2015 to 99 million in 2020,of which 36 million were in Central and Southern Asia and 49 mi

201、llion were in sub-Saharan Africa.Women make up 56%of all illiterate youth.FIGURE 12:What little progress is observed in adult literacy is the result of more young,educated people in the populationLiteracy rate by age group and sex,two waves of household surveys,selected countries2014 Women2014 Men20

202、22 Women2022 Men4050607080901005559 5054 4549 4044 3539 3034 2529 2024 1519%Age group2016 Women2016 Men2022 Women2022 Men5559 5054 4549 4044 3539 3034 2529 2024 1519Age group2014 Women2014 Men2022 Women2022 Men4050607080901005559 5054 4549 4044 3539 3034 2529 2024 1519%Age group2015-16 Women2015-16

203、Men2020-21 Women2020-21 Men5559 5054 4549 4044 3539 3034 2529 2024 1519Age group a.Kenyab.Nepal20G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTFIGURE 12 CONTINUED:2014 Women2014 Men2022 Women2022 Men4050607080901005559 5054 4549 4044 3539 3034 2529 2024 1519%Age

204、 group2016 Women2016 Men2022 Women2022 Men5559 5054 4549 4044 3539 3034 2529 2024 1519Age group2014 Women2014 Men2022 Women2022 Men4050607080901005559 5054 4549 4044 3539 3034 2529 2024 1519%Age group2015-16 Women2015-16 Men2020-21 Women2020-21 Men5559 5054 4549 4044 3539 3034 2529 2024 1519Age grou

205、pNotes:For every country,the continuous line represents the literacy rate of each age group by sex in the most recent survey.The dashed line represents the literacy rate of each age group by sex in the earlier survey but has been shifted to the left to facilitate comparisons.For instance,the dashed

206、line for the 201516 DHS in India has been shifted by 5 years to the left so that the literacy rate of 15-to 19-year-olds in 201516 corresponds to the literacy rate of 20-to 24-year-olds five years later,in 202021.The dashed line has also been shifted by 5 years in Nepal(where the two survey rounds a

207、re 6 years apart)and by 10 years in Cambodia and Kenya(where the two survey rounds are 8 years apart).Source:DHS country Final Reports.c.Cambodiad.IndiaThe adult literacy rate,for people aged 15 to 64 years,has increased from 81%in 2000 to 86%in 2015 and to 87%in 2020,an increase of just 1.2 percent

208、age points in five years.The number of illiterate adults dropped from 783 million in 2015 to 763 million in 2020,of which 367 million were in Central and Southern Asia and 205 million were in sub-Saharan Africa,where the number increased by 9 million.Women are 63%of all illiterate adults.These estim

209、ates are based to a large extent on the misleading assumption that having completed four years of education is equivalent with being literate,which does not hold in many poor countries.Self-reporting of the ability to read and write is still being used in some population censuses and labour force su

210、rveys.But it is also problematic.The UIS has been incorporating into its literacy estimates information from household surveys,notably the Demographic and Health Survey(DHS)and the Multiple Indicator Cluster Survey(MICS),which include a rudimentary but direct measure of the ability to read a simple

211、sentence.One disadvantage is that these surveys only sample adults aged 15 to 49 years,and usually only women.Even so,household surveys shed light on the process by which adult literacy rates change.There are two potential mechanisms in operation.First,as younger,more educated cohorts replace older,

212、less educated cohorts,the adult literacy rate increases by virtue of the changing population composition.Second,adult literacy rates can also change through adult literacy programmes.However,data from two DHS rounds in selected low and middle-income countries show little evidence that the latter mec

213、hanism is at play:literacy programmes,even when effective,rarely reach the scale required to have a visible impact at the population level.21G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTIn India,two successive rounds of the DHS were carried out five years apart

214、 from each other,in 201516 and in 202021.If adult education programmes were effective and at scale,then the literacy rates of,say,the cohort of 30-to 34-year-old women in 202021 should be higher than the literacy rates of the cohort of 25-to 29-year-old women in 201516.But in India,as in Cambodia,Ke

215、nya and Nepal,the literacy rates of these cohorts remain the same or have even decreased somewhat.Improvement in the literacy status of women has been exceptionally fast.In India,46%of 45-to 49-year-old women but 90%of 15-to 19-year-old women were literate in 202021,closing a gender gap of almost 30

216、 percentage points in 30 years.In Cambodia,womens literacy rates exceed those of men in the youngest cohorts(Figure 12).The cohort analysis also documents differences in countries trajectories.For instance,it shows the devastating impact of the Cambodian genocide:adults in their 40s have lower liter

217、acy rates than their peers in their 50s.It also shows that countries in the same region can achieve different rates of progress.For example,in western Africa in Sierra Leone,where some of the lowest literacy rates in the world are found,female literacy rates have increased exponentially:in 2019,only

218、 18%of 35-to 39-year-old women but 74%of 15-to 19-year-old girls could read.Male literacy rates have also increased rapidly.By contrast,male literacy rates have progressed very slowly in the Gambia,Liberia and Mauritania.In Gambia,64%of 45-to 49-year-old men and 72%of 15-to 19-year-old young men are

219、 literate,an increase of just 8 percentage points in 30 years.In Liberia and Mauritania,youth literacy rates appear to have even fallen in the latest five-year period(Figure 13).GIRLS NEED SEPARATE SANITATION FACILITIES IN SCHOOLSIn the countries still furthest behind from achieving gender parity in

220、 access to education,one of the most important issues is the availability of single-sex sanitation facilities.Separate bathrooms for boys and girls are often a prerequisite for girls to attend school because of concerns over their safety.Over 20%of primary schools in Central and Southern Asia and in

221、 Eastern and South-eastern Asia lack functional single-sex bathrooms;in Mali and Togo,they are lacking in 83%and 94%of schools,respectively.Single-sex bathrooms are more common in secondary than in primary schools.In Burundi,for example,35%of primary and 100%of upper secondary schools had single-sex

222、 bathrooms in 2018.But this might be too late for some girls,given very high levels of over-age enrolment:that year,31%of primary school students were at least 2 years over-age for their grade.A lack of menstrual hygiene facilities,stigma and stress lead many girls to missing up to one week of schoo

223、l a month,increasing the chances of falling behind and dropping out(UNICEF,2023a).A lower share of primary schools with single-sex bathrooms is associated with a higher out-of-school rate for girls than for boys in upper secondary education(Figure 14).This negative relationship may also reflect broa

224、der gender bias.In Afghanistan,the lack of single-sex bathrooms in three quarters of primary schools in 2018 may have been indicative of an overall lack of priority for gender equality in education,even before the Taliban takeover in 2021.FIGURE 13:Literacy rates for adult men have stagnated in The

225、Gambia,Liberia and MauritaniaLiteracy rate by age group and sex,selected western African countries,2019211020304050607080901000%The GambiaMauritaniaLiberiaSierra Leone45-4940-44Age group35-3930-3425-2920-2415-19WomenMenSource:DHS Country Final Reports.22G LO BA L E D U C AT I O N M O N I TO R I N G

226、R E P O RT 2 024G E N D E R R E P O RTFIGURE 14:The availability of single-sex toilets in primary education is associated with relatively lower out-of-school rates for girls of secondary school ageShare of primary schools with single-sex sanitation facilities and adjusted gender parity index for out

227、-of-school rates of upper secondary youth in low-and lower-middle-income countries,201622TogoMaliNigerAfghanistanEritreaLiberiaCongo0.20.40.60.81.01.21.41.60102030405060708090100Primary schools with single-sex basic sanitation facilities(%)Adjusted gender parity for upper secondary out-0f-school rat

228、eMore girls than boys are out of schoolMore boys than girls are out of schoolParitySource:UIS database(single-sex sanitation facilities)and VIEW database(out-of-school).WOMEN DOMINATE THE TEACHING PROFESSION BUT THERE IS LARGE VARIATIONGlobally,women are overrepresented in the teaching force.Among 8

229、4 countries with data at all four levels of education,the average share of educators who are female are 96%in pre-primary education,76%in primary education,59%in secondary education and 44%in tertiary education.Women are the majority in 89%of countries in primary and 83%of countries in secondary edu

230、cation(Figure 15).But in some,mostly central and western African countries,women are still underrepresented.For instance,in Chad and Togo just 1 in 5 primary school and 1 in 10 secondary school teachers are female.In the Democratic Republic of the Congo,just 6%of university teaching staff are female

231、.Countries where the majority of those teaching in universities are female are commonly in the Caribbean(e.g.British Virgin Islands and Cuba),the Caucasus(e.g.Armenia and Azerbaijan),Central Asia(e.g.Kazakhstan and Kyrgyzstan)and Eastern Europe(e.g.Albania and Belarus).23G LO BA L E D U C AT I O N M

232、 O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTFIGURE 15:The majority of teachers in primary and secondary education are womenShare of female teachers,by education level,2020220255075100Female(%)Note:Each figure shows the share of female teachers.For each level of education,countries are or

233、dered from the one with the lowest to the one with the highest share of female teachers.Source:UIS database.a.Pre-primaryb.Primaryc.Secondaryd.Tertiary24G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTTechnology affects girls education opportunities and outcomes T

234、he 2023 Global Education Monitoring Report presented the ways in which information and communication technology(ICT),especially digital technology,is shaping education.Technology can bring education opportunities to groups who are otherwise hard to reach,for instance in crisis situations(Box 4).It c

235、an lift barriers to accessing education content.It can benefit learners through online learning platforms and personalized learning experiences,which cater to diverse learning needs,including learning at ones own pace through video tutorials and interactive exercises(UNESCO,2023c).In certain context

236、s and if accessible to them these can better suit girls needs(Box 5).Depending on the context,technology can exacerbate or prevent gender inequality in education,both in terms of access to and the effects of ICT use,which can differ by gender.With the growing use of technology,gender gaps have emerg

237、ed in many countries in terms of freedom to access technology.Biased social and cultural norms inhibit equitable access to technology and the Internet at home,in school and in society.Attitudes and perceptions that girls are more vulnerable to online risks can severely restrict girls access to techn

238、ology,leading to restrictive practices that limit their engagement with digital technology(Crompton et al.,2021;Naylor and Gorgen,2020).The COVID-19 pandemic brought some of these divides into sharp relief through the abrupt turn to online learning in many countries.Mahajanga,Boeny-Rouweidah and oth

239、er child using the school computer to expand her knowledge,computer with internet access,at ease in their environment.Madagascar.Credit:UNICEF/UNI441157/Andriantsoarana25Gender gaps exist in education and social outcomes,ranging from digital skills to exposure to various risks.Girls and womens progr

240、ess depends on the context.They have been,and in many countries continue to be,behind in the acquisition of digital skills.But the situation is changing rapidly in some countries,where favourable employment opportunities are opening up.Technology,and the misinformation it generates,can leave girls a

241、nd women ever more vulnerable to violence and the propagation of gender stereotypes.But it also creates opportunities to communicate empowering messages,to which traditional education channels were not particularly suited.BOX 4:ICT can facilitate access to education and improve learning for girls in

242、 crisis contextsIn crisis situations,where girls are even more vulnerable,ICT can offer an education lifeline.In Afghanistan,where the Taliban have banned girls education,Radio Sada-e-Badghis broadcasts recorded sessions of lessons taught by volunteer teachers,helping girls continue their secondary

243、school education.They reportedly reached 70%of girls in the Badghis province(Omar,2023).Online learning platforms have provided a lifeline for the few girls who can access online resources.The UK-based online learning platform FutureLearn reports enrolling more than 33,000 Afghan students,most of th

244、em female,since they offered free access to its premium digital learning platform during the ongoing ban imposed the Taliban regime(Financial Times,2024).Several studies have focused on the use of radio for providing access to education for girls(UNESCO,2021).Educational radio programmes can be effe

245、ctive when applied with certain pedagogical approaches.An evaluation of an intervention in arid and semi-arid zones in Kenya found that radio was effective in improving reading and mathematics when girls listened to radio in groups(Amenya et al.,2021).In Sierra Leone,the Every Adolescent Girl Empowe

246、red and Resilient(EAGER)project of the International Rescue Committee supported 32,500 marginalized adolescent girls(FCDO,2023),combining radio programming with cash transfers and support from a female mentor within the community(Sarr et al.,2020).One programme offered secondary school girls access

247、to digital resources through low-cost tablets in the Zaatari refugee camp in Jordan.Evaluations suggested it increased girls confidence and motivation to stay in school(Rowe,2016),enhanced their desire to learn,improved academic performance(Wagner,2017),and helped reintegrate out-of-school adolescen

248、t girls back into the educational system(UNESCO,2018).At the height of the Boko Haram crisis in Adamawa state,Nigeria,the Technology Enhanced Learning for All programme used mobile and radio technology to support 22,000 disadvantaged children,including those who were internally displaced(Premium Tim

249、es Nigeria,2016).Within six months of listening to the programme,literacy and numeracy skills improved,in particular among girls(Jacob and Ensign,2020).26G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTBOX 5:Some technology-based approaches can support disadvantag

250、ed girls and womens learning in poor and rich countriesSpecific education technologies are not expected on their own to be better suited to either sex,as research has shown that learning styles do not differ by gender.Yet features in the design of some technologies might appeal more to either boys o

251、r girls.There are also external circumstances where technology may be able to help overcome some of the constraints girls and women face in accessing equitable learning opportunities(Pitchford et al.,2019),which have led to positive effects on their learning(Evans and Yuan,2021;Jordan and Myers,2022

252、).A few examples,mostly from Africa,highlight a range of interventions.Radio.An intervention that targeted out-of-school girls in Balochistan province,Pakistan(Raza,2022),combining daily 45-minute radio broadcasts with hygiene kits and printed educational materials,led to gains in literacy,numeracy

253、and civic education outcomes(Myers et al.,2023).SMS.Used alongside other types of technology,interventions that use short messaging services(SMS),also called text messages,can improve learning,even though most studies tend to show no variation in these effects by sex.In Botswana,a project using SMS

254、and phone calls for learners in grades 3 to 5 showed no gender differences in gains in numeracy(Angrist et al.,2022).But in Bangladesh,a study which analysed the effect of a programme combining SMS nudges with conditional cash transfers found that it increased secondary school enrolment for girls an

255、d reduced child marriage with relatively low implementation costs(Fujii et al.,2021).In Uganda,a model adopted by the Promoting Education in African Schools project(PEAS,2021),based on the use of radio lessons combined with paper-based resources and support from teachers via SMS,showed that it benef

256、ited girls learning and that girls were more interested in listening to radio than boys(Damani et al.,2022).In Kenya,M-shule(mobile school in Kiswahili),an SMS platform,was developed with the aim to improve childrens and especially girls learning outcomes by enabling them to catch up when they misse

257、d classes.Personalized educational content and quizzes are delivered through SMS on low-tech mobile phones,without the need for an Internet connection.The platform,which reached 23,000 households with grade 1 to 4 students in 20 counties,has been found to improve examination scores by 7%if used for

258、more than an hour per week(Myers et al.,2023).Learning applications.The iMlango project aimed to improve Kenyan pupils learning outcomes,enrolment and retention across some 200 primary schools by using technology along with financial incentives to encourage attendance among the most marginalized gir

259、ls(Ndiku and Mwai,2016).The use of Maths-Whiz in the project,a virtual math tutor,led to improvement in girls numeracy(IMlango,2022).The use of the learning application(app)Onebillion on tablets in Malawi showed significant gains in numeracy and literacy for grade 1 and 2 learners,with girls benefit

260、ing more.When standard pedagogical practices were used,gender differences emerged in grade 1,while interactive practices ensured that boys and girls learned equally well(Pitchford et al.,2019).In the United Republic of Tanzania,an evaluation of RoboTutor software found significant gains in literacy

261、and numeracy but no significant differences by sex(McReynolds et al.,2020).Online learning.In contexts where access to fast Internet is universal and affordable,online learning can help women with competing work and family responsibilities(Waterhouse et al.,2022).The flexibility of online learning a

262、llows learners to choose a time,rhythm and place compatible with their work and family responsibilities.In Australia,a study of adult women found that the choice to study online was largely determined by their family and caring responsibilities(Stone and OShea,2019).Learning in prison can be a chall

263、enging process for women(Cooney,2018)as they face unique barriers to learn and earn degrees(Incarceration Nations Network,2020;Weissman,2022).In the prisons of the US state of Texas,male inmates are more than three times as likely as their female peers to access higher education programmes(Weissman,

264、2022).Also in the United States,women prisoners in Hawaii(Elias,2022)and in New England(Smith,2022)that followed online courses had a positive impact on their learning.A study of 306 female prisoners that took part in an e-learning programme in Portugal found that the course achieved its goals and p

265、articipants wanted to pursue their studies using this modality(Monteiro et al.,2023).27G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTGIRLS ARE OFTEN ON THE WRONG SIDE OF THE DIGITAL DIVIDEThe availability of distance education opportunities depends on the rates

266、of ownership and use of devices,such as mobile phones,tablets and laptops,as well as access to services such as the Internet.There is a gender gap in mobile phone ownership,with 81%of men and 75%of women owning a device in 2023.The gender gap decreases by country income,ranging from 17 percentage po

267、ints in low-income to 1 percentage point in high-income countries.The divide is more pronounced in smartphone ownership.Women in South Asia are 42%less likely than men to own a smartphone(GSMA,2023).A 2022 survey showed significant gender gaps in mobile ownership in 3 out of 12 countries,with a diff

268、erence of 29 percentage points in Pakistan,20 in Bangladesh and 17 in Ethiopia.In Pakistan,1 in 5 adolescent women aged 15 to 19,but almost 1 in 2 adolescent men,owned a phone(MacQuarrie et al.,2022).There is also a gender gap in Internet use,with 70%of men and 65%of women using the Internet in 2023

269、(ITU,2023a)(Figure 16).This 5-percentage-point gap is equivalent to 244 million more men than women using the Internet globally.The gap widens in lower-middle-income(8 percentage points)and low-income countries(14 percentage points).A study of 12 countries reported gender gaps in Internet use exceed

270、ing 40%in Bangladesh,Ethiopia and India(GSMA,2023).Gender gaps in both mobile phone ownership and access to the Internet are exacerbated when they interact with poverty and location.For example,in Sierra Leone in 201718,the gender parity index of mobile phone ownership was 0.81 in urban areas and 0.

271、48 in rural areas;likewise,it was 0.86 among the richest households and 0.34 among the poorest households(Myers et al.,2023)(Figure 17).FIGURE 16:The poorer a country,the wider the gender gap in Internet useInternet use,by country income group and sex,20230504030201060708090100LowLowermiddleWorldUpp

272、ermiddleHigh%20518034596570819394FemaleMaleSource:ITU(2023).FIGURE 17:The poorer the household,the larger the gender gap in mobile phone ownership in Sierra LeoneMobile phone ownership by household wealth and sex,Sierra Leone,2017180504030201060708090100PoorestPoorMiddleRichRichest%FemaleMale12 22 3

273、4 59 74 35 53 59 86 76 51534644406980837471050403020106070809010020-2425-2930-3435-3940-44%Source:Myers et al.(2023)based on the 201718 Multiple Indicators Cluster Survey.28G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTThe intersection of wealth and sex suggests

274、 that affordability is a key barrier to womens mobile ownership and Internet use.In Kenya,where 49%of men and 34%of women owned a smartphone in 2021(GSMA,2022b),more than half of women surveyed reported affordability as the primary barrier(Myers et al.,2023).In some countries,girls try to circumvent

275、 lack of access to devices by owning SIM cards without a mobile phone or borrowing phones from others (Girl Effect,2023).The intersection of location and sex suggests that social norms,including perceptions of digital risks and safety,significantly influence girls engagement with the digital world(C

276、rompton et al.,2021),often leading to more frequent monitoring of girls compared to boys(UNICEF,2021a).A survey of girls aged 14 to 21 and their parents in Ethiopia,India,Jordan,Kenya,Nigeria,Rwanda and the United Republic of Tanzania showed parents tendency to believe that girls require more protec

277、tion than boys from potential online distractions and temptations(Girl Effect,2023).Lack of agency exacerbates the gender digital divide(Gattorno et al.,2022).In Ghana,sociocultural norms discourage girls from visiting cybercafes(Steeves and Kwami,2017).In Gujarat,India,mobile phone bans for unmarri

278、ed women and girls under 18 were imposed in 2016 to prevent distraction from studies,with fines for usage and rewards for informants(Khan,2016).In India,boys were more likely than girls to have access to computers outside of school,both at home and in computer centres and cybercafes.While both boys

279、and girls used computers at school,boys were more likely to make use of the Internet(Basavaraja and Sampath Kumar,2017).A study on COVID-19 responses in Nigeria revealed that fathers were significantly less likely to allow girls to use the Internet(Malala Fund,2020).In Ghana,more than 1 in 5 caregiv

280、ers considered their sons education more important than their daughters.In families where parents expressed education preferences for boys over girls,girls were spending less time on remote learning(Aurino et al.,2022).Family approval emerges as a notable barrier to owning a phone.In Pakistan,22%of

281、women who did not own a phone cited lack of family approval as the primary obstacle,compared to just 4%of men(GSMA,2023).In Bangladesh and India,girls often face harsh judgements for using mobile phones due to prevailing social norms(Vodafone Foundation,2018).A survey conducted by the BRAC Institute

282、 of Governance and Development of 6,500 rural households in Bangladesh found that 63%identified a male member as being the most able to use digital devices in the household,nearly double the rate for a female member(Joshi et al.,2023).In sub-Saharan Africa,household attitudes to gender,gender roles,

283、cost considerations,security concerns and restrictions on mobility contribute to unequal access to technology for girls at home(Webb et al.,2020).While technology was a lifeline for learning during the COVID-19 pandemic,competing family responsibilities meant learning continuity was challenging for

284、girls and women.In Ethiopia,only 22%of girls had their time spent on chores reduced to accommodate home study versus 57%of boys(Jones et al.,2021).In Kenya,74%of adolescent girls but only 46%of boys reported that household chores distracted them from remote learning during COVID-19 school closures(K

285、enya Presidential Policy and Strategy Unit and Population Council,2021).Female teachers also had to take on most of the household and child-rearing duties in addition to their teaching duties.Such obstacles limited female teachers opportunities to experiment and develop their capacity in the use of

286、technology in Ghana(Ananga et al.,2021)and in East Java,Indonesia(Febrianto et al.,2022)In several contexts,a larger proportion of women than men who own Internet-enabled phones do not use the Internet.Non-usage rates were found to be about twice as high for women than for men in India(12%vs 5%),Ken

287、ya(23%vs 10%)and Nigeria(27%vs 15%)(GSMA,2023).In a study of six Latin American countries,35%of women and 24%of men reported not knowing how to use a smartphone,while 40%of women and 33%of men reported not knowing how to use the Internet(Agero et al.,2020).During the implementation of the One Laptop

288、 Per Child program in Ghana,there was a significant gender divide in the use of the devices,particularly in urban settings,as girls were often expected to assist with household chores(Steeves and Kwami,2017).Such barriers to girls access to technology mean that interventions focused on hardware tend

289、 to have low impact for girls(Nicolai et al.,2023;Steeves and Kwami,2017).Similar evidence of low impact from other studies(Evans and Yuan,2021;Jordan and Myers,2022)is a reminder of how hardware was inadequately integrated into pedagogical processes and its deployment was ultimately unsustainable(A

290、mes,2019;Souter,2021).29G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTAfrican governments have integrated gender dimensions into their ICT national plans.Botswanas national broadband strategy sets gender-specific targets for smartphone access,digital literacy an

291、d ICT graduates,and proposes a strategic plan by the Universal Service and Access Fund to bridge gender disparities.Nigerias National Broadband Plan(20202025)seeks to enable 5 million more women to use the Internet by 2023.Rwandas 2024 ICT Hub Strategy includes a gender section.The government is com

292、mitted to accelerate telephone use in rural areas through Connect Rwanda,which places special emphasis on female farmers.In Senegal,the Digital Senegal 20162025 plan has committed to incorporating gender considerations in all broadband policy decisions.GENDER GAPS IN DIGITAL SKILLS ARE RAPIDLY CHANG

293、INGSDG global indicator 4.4.1 is a self-reported measure of the use of ICT.In 2015,nine tasks were specified to be part of the global indicator.As these were meant to be carried out on a computer or a tablet,there have since been demands to amend the list of tasks assessed,for instance,to also captu

294、re activities that can be performed with smartphones or to drop activities that are becoming obsolete.The International Telecommunication Union(ITU)has added measures on safety,such as the use of passwords,privacy settings and verifying the reliability of information found online.Overall,the data pa

295、int a picture of considerable gender disparity in ICT skills,albeit one that has several nuances.Data from 90 countries in 201421 overrepresent upper-middle-and high-income countries(as there are data for almost 50%of them)but still provide a global picture(as data for almost 30%of low-and lower-mid

296、dle-income countries are available).Two of the nine ICT skills are used to demonstrate gender disparity among youth and adults:being able to use a basic arithmetic formula in a spreadsheet and being able to write a computer program using specialized programming language.The data are presented for tw

297、o age groups:15-to 24-year-old youth and 25-to-74-year-old adults.Data come from the ITU database and,in the case of youth,from Multiple Indicator Cluster Surveys.Depending on their complexity,ICT skills require a minimum level of literacy and numeracy skills,while their distribution in the populati

298、on is also determined by the availability of infrastructure,devices and relevant labour market opportunities,as well as the gender stratification of these jobs.With respect to spreadsheet skills,the prevalence in the youth population is about 1%in low-,14%in lower-middle-,33%in upper-middle-and 57%i

299、n high-income countries.The average gender parity index increases from 0.82 among adults to 0.91 among youth.The percentage of countries that have disparity at the expense of females falls from 79%among adults to 44%among youth,while the percentage of countries that have disparity at the expense of

300、males increases from 11%among adults to 40%among youth.Countries with large disparity at the expense of young women tend to be low-income sub-Saharan African countries and South Asian countries(e.g.Nepal and Pakistan).Countries with large disparity at the expense of young men tend to be Caribbean an

301、d Pacific Small Island Developing States,Arab countries(e.g.Oman and Tunisia)and South-eastern Asian countries(e.g.Thailand and Viet Nam).For example,for every 100 young men with spreadsheet skills,there are only 40 young women in Chad,43 in Gambia and 44 in the Democratic Republic of the Congo with

302、 such skills.In contrast,for every 100 young men with spreadsheet skills,there are 117 young women in Egypt,136 in the Turks and Caicos Islands and 167 in Tuvalu with such skills(Figure 18).30G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTFIGURE 18:There is near

303、gender parity in spreadsheet skills among youthAdjusted gender parity index of the ability to use a basic arithmetic formula in a spreadsheet,by age group,2014210.00.20.40.60.81.01.21.41.61.82.0Adjusted gender parity index15-2425-74GambiaChadD.R.CongoC.A.R.NepalPakistanBrazilMadagascarCte dIvoireLux

304、embourgUnited KingdomTrkiyeGuinea-BissauMalawiSwedenAlgeriaBelarusUzbekistanIran,Isl.Rep.ZimbabweIrelandBangladeshAustriaRomaniaUkraineGreeceItalyFinlandDenmarkSloveniaPortugalHungaryPalestineU.A.EmiratesSaudi ArabiaBotswanaMontenegroMalaysiaNetherlandsGermanyMaltaLithuaniaSpainSwitzerlandSlovakiaBe

305、lgiumMacao,ChinaPeruBulgariaBrunei Daruss.Rep.of KoreaEstoniaCzechiaHong Kong,ChinaKazakhstanLatviaSerbiaJapanPolandColombiaMexicoAzerbaijanIcelandRussian Fed.CroatiaFranceNorwayCambodiaBahrainCyprusNorth MacedoniaQatarViet NamSamoaCabo VerdeSingaporeKiribatiEgyptMauritiusTunisiaCubaSurinameThailand

306、JamaicaBosnia/Herzeg.GeorgiaTurks/Caicos IsOmanTuvaluTonga More males possess the skill More females possess the skillSource:ITU database and MICS Survey Findings reports.With respect to programming skills,the prevalence in the youth population is about 0.5%in low-,2%in lower-middle-,6%in upper-midd

307、le-and 14%in high-income countries.The African Girls Can Code Initiative aims to raise the level of coding skills while also bridging the gender divide(Box 6).The average gender parity index increases from 0.50 among adults to 0.75 among youth.The percentage of countries that have disparity at the e

308、xpense of females falls from 93%among adults to 72%among youth,while the percentage of countries that have disparity at the expense of males increases from 4%among adults to 21%among youth.Countries with large disparity at the expense of young women tend to be high-income European countries.For inst

309、ance,for every 100 young men with programming skills,there are only 21 young women in Ireland,24 in Hungary and 28 in Austria with such skills.In contrast,for every 100 young men with programming skills,there are 105 young women in Malaysia,110 in Saudi Arabia,118 in Albania and 130 in the State of

310、Palestine with such skills(Figure 19).BOX 6:The African Girls Can Code initiative aims to bridge a critical gender gapThe African Girls Can Code Initiative,commissioned by UN Women and the African Union Commission in collaboration with the ITU,aims to bridge the gender divide on a critical digital s

311、kill in Africa(UN Women,2024).The initiative was launched in 2018 with support from the Danish Embassy in Ethiopia.It targets 2,000 young women aged 17 to 25,aiming to empower them to become computer programmers,creators and designers,and preparing them for careers in the ICT sector.The initiative o

312、perates through two main strategies:coding camps and mainstreaming ICT,coding and gender into national curricula.Camps not only provide direct training to girls but also foster an environment of mentorship and networking with field professionals.By 2022,the initiative had trained 600 participants fr

313、om 35 countries,had developed a guide for integrating computing and gender into secondary education curricula and had launched an eLearning platform(UN Women,2022).In April 2022,the initiative entered its second phase,launching two-week coding camps in 11 countries.The first coding camp was held in

314、Rwanda,where participants strengthened their knowledge in coding,robotics and key gender equality concepts.31G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTFIGURE 19:Gender disparity in programming skills is large,especially in rich countriesAdjusted gender parit

315、y index of the ability to write a computer program using specialized programming language,by age group,2014210.00.20.40.60.81.01.21.41.61.82.0IrelandHungaryAustriaSloveniaLuxembourgBelgiumUkraineTurks/Caicos IsCyprusSwedenCzechiaSlovakiaPortugalGermanyFinlandItalySpainSwitzerlandJapanEstoniaUnited K

316、ingdomRussian Fed.NorwayMaltaSerbiaGreeceLithuaniaRomaniaTrkiyeZimbabweBelarusNetherlandsIcelandPakistanSingaporeFranceViet NamD.R.CongoMacao,ChinaCte dIvoireMontenegroNepalPeruLatviaBotswanaEgyptMadagascarAlgeriaDenmarkIran,Isl.Rep.ColombiaBangladeshNorth MacedoniaBulgariaBosnia/Herzeg.CroatiaPolan

317、dMauritiusUzbekistanRep.of KoreaKazakhstanMalawiCubaMexicoSamoaBahrainBrunei Daruss.C.A.R.ChadTunisiaMalaysiaAzerbaijanU.A.EmiratesSaudi ArabiaBrazilSurinameHong Kong,ChinaThailandGeorgiaCambodiaAlbaniaKiribatiPalestineQatarOmanTuvaluGuinea-BissauGambiaTongaAdjusted gender parity index15-24 More mal

318、es possess the skill More females possess the skill25-74Source:ITU database and MICS Survey Findings reports.FIGURE 20:There is no clear link between gender disparity and average youth skill levelsAverage level of ICT skills in the youth population and adjusted gender parity index,20142100.20.40.60.

319、81.01.21.41.61.82.0020406080100Adjusted gender parity index15-to-24-year-oldswho can use a basic arithmetic formula in a spreadsheet(%)00.20.40.60.81.01.21.41.61.82.0020406080100Adjusted gender parity index15-to-24-year-olds who can write acomputer programme in any programming language(%)Source:ITU

320、database and MICS Survey Findings reports.There is no clear association between the level of an ICT skill in the population and the level of gender disparity,although there are higher levels of gender disparity at the expense of women at very low overall levels of spreadsheet skills(Figure 20).a.Spr

321、eadsheet skillsb.Programming skills32G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTThe speed with which skills are getting diffused in the female population is further revealed by Multiple Indicator Cluster Surveys.In a sample of 36 low-and middle-income countri

322、es,20-to 24-year-old women are twice as likely to be able to use a basic arithmetic formula in a spreadsheet than their 40-to 44-year-old peers.But there are considerable differences in the pace of change between countries.In Argentina,there is practically no difference between these two cohorts,whi

323、le in Tunisia,the younger cohort is almost four times as likely as the older cohort to have this skill.There are also differences in the peak age of skill prevalence,which is observed among 25-to 29-year-olds in Suriname,20-to 24-year-olds in Algeria and 15-to 19-year-olds in Nepal(Figure 22).FIGURE

324、 21:Younger women acquire ICT skills in far greater numbersWomen who reported using a basic arithmetic formula in a spreadsheet,selected middle-income countries,by age group,201721510152025300%1519202425293034353940444549Age510152025300%1519202425293034353940444549AgeFijiSurinameAlgeriaLAO PDR Nepal

325、GhanaArgentinaViet NamTunisiaSource:MICS Survey Findings reports.TECHNOLOGY CAN AFFECT GENDER NORMS POSITIVELY AND NEGATIVELYICT permeates and influences social and economic life,including,obviously,education.In the case of influencing gender norms,its strengths are also its weaknesses.ICT can be us

326、ed to increase communication on positive topics.Well-designed messages transmitted through radio,television and digital channels can bypass traditional obstacles for communicating with hard-to-reach groups on issues such as sexual and reproductive health rights.In contrast,ICT can facilitate the dis

327、semination of negative and false information,through the ease with which large volumes of low-quality content circulates on the Internet and social media.TECHNOLOGY FACILITATES ACCESS TO COMPREHENSIVE SEXUALITY EDUCATIONAccessing the Internet is commonly associated with risks to children from exposu

328、re to pornography,which may lead to poor mental health,sexism and objectification,sexual violence,and other negative outcomes(UNICEF,2021b).Yet,technology at the same time can have a positive influence on gender norms through providing access to sexuality education opportunities outside of school.Se

329、xuality education can be directed at the entire population through low-tech channels(Box 7),or it can be targeted,providing interactive and personalized learning experiences in a safe and confidential learning environment.The technology used is low cost,private and effective in tailoring messages fo

330、r specific populations(Brayboy et al.,2018).33G LO BA L E D U C AT I O N M O N I TO R I N G R E P O RT 2 024G E N D E R R E P O RTTechnology-enhanced strategies are effective for traditionally excluded groups and offer greater content and style flexibility(Fiellin et al.,2017;Teadt et al.,2020).Digi

331、tal technology can promote shifts in gender norms that move towards social justice,primarily by providing spaces where dominant gender norms can be challenged(Rentschler and Thrift,2015;Washington and Marcus,2022).Digital strategies in sexual and reproductive health are evolving,with social mediabas

332、ed and interactive technology becoming more common than the mobile phones and text messaging used more often before 2015(Huang et al.,2022).Digital redesign of traditional games,such as Help Pinky,has been used to engage girls in rural India in discussions about menstrual health,addressing informati

333、on gaps and challenging taboos(Jain and Yammiyavar,2015).In Lesotho,the Nokaneng app helps students access information on gender-based violence and on legislation protecting women and girls from violence(AUDA-NEPAD,2023).The CSE Learning Platform,primarily targeting youth in sub-Saharan Africa,aims to encourage knowledge sharing and learning across countries,featuring a digital library and an Ask