Education data in sub-Saharan Africa: what do we know?
In the last few years, access to education data[1] has become an increasingly important issue. This is driven mainly by the recognition that education data is vital in ensuring that students in Sub Saharan Africa get quality education and access to decent jobs. The COVID-19 pandemic has led to historic disruptions in learning and access to education, making availability of education data all the more important for targeted policy interventions aimed at addressing the issue.
In this blog, we share some insights from an ESSA project aimed at understanding the quality of existing education data in sub-Saharan Africa. For this project, we analysed education datasets collected between 2010 and 2020 from three data sources. These are the African Education Research Database (a free database of over 4,000 pieces of research by African scholars – created by ESSA and the REAL Centre at the University of Cambridge), UK Data Archive, and DataFirst.
Though we did not expect to find a large number of datasets due to a general lack of education data, it was surprising to find only 68 datasets on education in sub-Saharan Africa. Thus, as the number of datasets in the analysis are limited, what we highlight here is the current landscape of education data in the region, justifying the need to openly share such data with the aim of improving education and youth employment policies in sub-Saharan Africa.
What kind of data do we need to address youth unemployment?
A majority (43 per cent) of the datasets address primary education, followed by secondary education (32 per cent). This is not surprising because many (25 per cent) of children in sub-Saharan Africa aged 6 – 11 are not in primary school (UNESCO,2019). Thus, the critical situation of primary education has attracted the attention of funders and researchers, who have invested more resources to collecting primary and secondary education data to address present gaps in schooling.
By contrast, we found a comparative neglect of early childhood education (2 per cent) and Technical and Vocational Education and Training (TVET) (0 per cent). Our findings are consistent with a similar study with a larger sample (Rose et al. 2019).
The neglect of early childhood education is a concern, considering that this phase plays an important preparatory role in readying children for school and future life opportunities. Likewise, TVET has been identified as a key intervention area in addressing youth unemployment in the region
It will be difficult to address the challenges at the lower levels of education without quality post-secondary education across the continent. This is because research conducted to address challenges facing lower levels of education is mostly led by researchers at universities or colleges. These institutions are also important places where young people gain skills for work and life. Therefore, having current data to inform research and strengthen colleges and universities will help to produce solutions for improving all levels of education.
Figure 1. Proportion of datasets by phase of education
Geographic Distribution of the data
East Africa has the highest share of datasets (39 per cent) followed by West Africa (35 per cent). The region with the lowest share of datasets is Central Africa, accounting for 6 per cent.
It is important to note that the datasets included in the mapping come from English data repositories. This means regions with more non-English speaking countries (e.g., Central and West Africa) are more likely to be under-represented.
East and Southern Africa are known to have large-scale education surveys and evaluations such as datasets from Uwezo, the African Population and Health Research Centre (APHRC), and the Southern and Eastern Africa Consortium for Monitoring Educational Quality (SACMEQ). In contrast, data from West Africa is mainly demographic, health, and living standards surveys.
Figure 2. Proportion of datasets by SSA region
The road ahead
Based on this mapping, a coalition of organisations - ESSA, Zizi Afrique and EdTech Hub - held a workshop, ‘Unlocking data to tell the story of Education in Africa’, to bring together multiple stakeholders with the aim of forming a collective to share education data in sub-Saharan Africa.
The outcomes from our discussions are captured in quotes from workshop participants:
We need to reach out to [the data] users and ensure we are engaging all key stakeholders including teachers. There should be greater consideration of use of the data even before data collection to ensure we are capturing the right information. If done correctly, this can improve learning and teaching (Facilitator from Malawi).
Sharing data in the education sector should be the default and not the exception to make access easier for all. Increasing access to education data will allow for greater utilisation for decision-making. (Facilitator from Kenya).
We have made a commitment to the Global Initiative on Decent Jobs for Youth to continue working together to build a coalition with researchers, students and policy makers on sharing education data in sub-Saharan Africa. Our common goal is to make education data more accessible and make sure that it is used for making positive change within schools, colleges and universities as well as youth employment interventions in sub-Saharan Africa. After all, access to such data can help provide quality education crucial for securing a successful school to work transition. Our vision is for more young people to achieve their career and life ambitions.
by Samuel Asare is an education researcher from Ghana, working with Education Sub Saharan Africa (ESSA).
This article is part of the Decent Jobs for Youth Blog Series: Youth Rights & Voices. The Blog Series highlights the impact of the COVID-19 pandemic on young women and men in the world of work and discusses action-oriented policy responses and solutions. If you would like to comment or contribute, please contact decentjobsforyouth@ilo.org.
[1] Data in this context refers to information collected through research, which is stored as numbers or words and can be analysed multiple times
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