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07 Sep 2022
Elaine Unterhalter, Helen Longlands and Rosie Peppin Vaughan

Missing Education Data: Gender, Data and Measurement

This Blog Post is contributed by Elaine Unterhalter, Dr Rosie Peppin Vaughan and Dr Helen Longlands, as part of the NORRAG Blog Series on Missing Education Data which aims to further explore six themes that emerged from the inaugural summit and its accompanying papers and expert consultations. Measures of progress towards gender equality, particularly in girls’ enrolment, are often simultaneously presented by donors and international agencies among the successes of the SDG campaigns so far and as an area highlighted for further attention. However, the indicators used, and data drawn on to measure progress towards the goals have significant shortcomings, such as uneven coverage, and difficulties with addressing the complex issues associated with gender inequalities and intersectionality. On 2nd December 2021, NORRAG and AGEE (Accountability for Gender Equality in Education) jointly organised a closed-door discussion meeting on Missing Education Data, focusing on gaps regarding gender data.[1] This post provides a brief summary of key points that emerged from that discussion alongside relevant developments during the first half of 2022.

Thematic Session: gender, data and measurement

Gender equality in education and sustainable development are connected, albeit in complex ways. The SDGs have placed a spotlight on the importance of gender equity overall (SDG 5) and specifically in education (SDGs 4.5 and 4.7, and the disaggregation of other individual-level indicators). Significant progress has been achieved in many countries in terms of gender parity in enrolment and attendance in primary school, and there have been substantial developments in Education Management Information Systems (EMIS) and in documenting learning outcomes in reading and mathematics. However, large problems relating to gender and intersecting inequalities remain for which data availability is uneven. These notably include conditions in schools, attainment and learning outcomes in a wider range of subjects, and opportunities gained through education. There is thus a need to shift from a narrow focus on gender parity of access to broader perspectives and data that would represent a more substantive understanding of the problem of gender inequalities in education.

From a data perspective, the availability of gender disaggregated education data has increased since the launch of the SDGs in 2015; however, many countries have uneven reporting. Moreover, there has been inadequate attention to and use of data which demonstrates the intersections of gender with other areas of educational inequality associated with, for example, wealth, geography (urban vs. rural), primary language, and others—even when this data can be generated using existing assessments and surveys used to populate SDG 4 data.

Substantive gender equality in education has many facets, including how gender operates within and between political, economic, social, and cultural institutions. There are a number of frameworks that draw on data to try to present a more holistic and comprehensive view of what gender inequality in, or associated with education looks like. For example, a recent working paper by Delprato (2021)[2] estimates that for SDG 4.1, 79% of possible 2- and 3-dimensional intersectional inequalities that could be generated using extant data are not yet presented in global datasets; such innovative use of data could give insights into some of the complexities of gender inequalities in education. In some countries, sex-disaggregated data is more available at the national level than at the global level, suggesting that our global data systems have important gaps that might be filled with better coordination with national data systems. Finally, there are gaps in how we have designed our data systems to capture measures of how gender operates through educational institutions. 

What are the highest priority data gaps around gender equality in education?

First, there are enormous variations in where the data gaps are. For example, across Africa, the indicators for SDG 4.1.1, which speaks to the quality of education and the skills gap, vary hugely in availability. Many of the gaps relate to the inability to disaggregate data in multiple ways: it is usually possible by gender, but it remains difficult to relate this to wealth quintiles, rural / urban locations, and so on. This requires linking with household data. Although many countries have survey data that could be used, it is a complex process, and there is a need to build capacity and to provide additional financial resources, especially for data dissemination and use..

Second, it is important that we have data to look beyond gender parity in schooling access, including information on curricular materials, representation, (un)conscious bias, and gender norms. However, issues such as these are often seen as being outside the scope of educational planning, or too complex to be addressed. The AGEE project is an example of an initiative attempting to bring in data relating to wider gender inequalities to the field of education. An example of good practice is recent work by IIEP in Sierra Leone and Nigeria, which aims to bring a multidimensional and intersectional approach to gender, with related implications for data and tracking.[3] For future improvements, it is also imperative to look at how a more holistic and intersectional approach to gender equality in education is included in strategic planning documents.

Improved data is key for future progress. Bringing together actors from different gender constituencies can be very generative both in highlighting gaps and identifying innovative sources of data across areas often siloed, such as education and health. For example, under COVID-19, the increased gathering of household data by health workers has enabled linking up with education data in GEC / FCDO projects.[4]. In South Africa, it has been possible to analyse data on health care provision, social grants, and school outcomes to target the most vulnerable children.  A crucial step is ensuring that those most affected are not only consulted but involved in designing and using tools to generate and repurpose data for these broader analytical and decision-making processes.

Overall, there are three priority areas of missing data: first, core elements of the learning process and gender (e.g., curricula and pedagogy); second, data relating to the school environment (e.g. SRGBV, menstrual health and hygiene); and third, indicators from outside the education sector (e.g. time use, social norms, child marriage etc). Other overarching concerns are digital inequalities and intersectional data. A further point emerging from the discussion was the importance of reforming data collection systems to go beyond the binary and bridge data gaps around gender identity and sexual orientation, to reflect the complexity of the issue.

Addressing the gaps: the role of researchers, policymakers and civil society

There are large measurement burdens on governments, especially in Africa and in the wake of COVID-19. Therefore, one strategy is to go for the ‘low hanging fruit’ of data that is already available. It can shift the momentum significantly if civil society organisations and academics draw on such data to provide policy evidence, which can then be used to change the ways government and education departments use information systems to think about and identify goals. For example, demonstrating how it is possible to go beyond sex disaggregated data and towards intersectional perspectives, using data to show who are the most marginalised girls and what needs to be done to address their needs were among cited priorities.

Another step towards addressing data gaps is through improved training. IIEP provides technical support for governments, particularly through the ‘Gender at the Centre’ initiative, including training on using data, knowledge production and sharing. As part of this, they also do important work on social norms, across the education, health and economics sectors.

Finally, as discussed above, a key means through which real progress could be achieved is through connecting different constituencies. The approaches taken by mainstream statisticians and feminists are usually different, but collaboration is necessary, and possible if the different approaches are recognised. Participatory and inclusive approaches have not traditionally been used, but are hugely valuable and can be drawn on to gain agreement on what needs to be measured, and to generate new data. Multi-stakeholder approaches are therefore the goal, but bring their own challenges and are easier to say than do. There is currently a capacity gap around bringing together different stakeholders, who often have different language and epistemologies. There are a few examples of this working effectively in practice, such as the WASH joint monitoring project (WHO/UNICEF) which is creating gender sensitive indicators; and also the Menstrual Health and Hygiene project by Columbia University; and UN Women in Kenya bringing together civil society and the Kenya National Bureau of Statistics. By bringing in expertise from civil society and academia, it is more likely you will generate data that people understand, and use.

In order to foster collaboration with different groups of stakeholders, some tools could be generated: e.g., a guide for bringing actors together from different silos, and sharing examples of effective data use through collaboration. The recent work by AGEE on this provides an important example of such consultative approaches to gender sensitive data in education. Furthermore, there is a need for a database of the existing underused data that could fill the current gaps. The Gender Equality Framework based at UNESCO GEM, and the Gender Equality in Education Snapshot developed alongside this by UNGEI, are both considered important initiatives in this direction. The next stages of the AGEE project seek to use consultations to bring perspectives from different groups to build the AGEE Framework dashboard to present a composite indicator of gender equality in education.

This is an important moment for missing data on gender and education. We are half-way through the SDG cycle (2015-2030), and currently, there is a willingness in many arenas to scale up attention to gender. At the same time, gender inequalities persist, and both the COVID-19 pandemic and climate crises have brought both increasing and new forms of educational inequality, at the same time as increased challenges for data collection – such as the disruption to collection during COVID-19, and the new types of data needed in relation to climate and education. Yet there is also some cause for optimism, both in terms of increasing technical possibilities and new types of data being collected, and also opportunities for collaboration between different constituencies working on gender and education from different perspectives. 

Elaine Unterhalter is Professor of Education & International Development at University College London Institute of Education, and Co-Director of the Centre for Education and International Development. Her work is concerned with global and national policy and practice around gender equality in education, paying attention to intersectionality, the capability approach and human development. She has led research projects working in South Africa, Kenya, Nigeria, Tanzania, and Bangladesh. Her most recent publication is the edited collection Critical reflections on public private partnerships (2021, co-edited with Jasmine Gideon). She is the Principal Investigator on the AGEE project.


Dr Rosie Peppin Vaughan is a Lecturer in Education & International Development at UCL’s Institute of Education. Her research focuses on transnational advocacy on girls’ and women’s education, and also draws on the capability approach and the concept of human development to explore the evaluation of educational equality and social justice. She is a Co-Investigator on the AGEE project.



Dr Helen Longlands is a Lecturer in Education and International Development at UCL Institute of Education, University College London, and Programme Leader for the MA Education, Gender and International Development. Her research interests are interdisciplinary and concerned with gender, inequalities and social justice, with a particular focus on masculinities, transnational relationships of power, and the interconnections between the spaces of education, gender, work and family. Her latest publication is Gender, Space and City Bankers (2021). She is a Co-Investigator on the AGEE project.


[1] The speakers were: Isabella Schmidt (Statistics Specialist, UN Women); Albert Motivans (Head of Data and Research, Equal Measures 2030); and Fabricia Devignes (Senior Education and Gender Specialist, Gender at the Centre Initiative, IIEP-UNESCO). Others attending included representatives from international agencies, NGOs and ministries.

[2] Delprato, Marcos (2021) Global mapping of missing data for SDG4. Centre for International Education, University of Sussex UK.

[3] See for example:

[4] See for example lessons from the field linking edcuation and health systems during COVID-19: 

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