The Broken Spider Web: Navigating the Complex Education Data Ecosystem in Cameroon


“Surrounded by data but starving for insight.”

In November 2020, Cameroon adopted the “National Development Strategy 2020-2030”, a reference framework for its development action over the next decade, making education a fundamental pillar for the development of the nation. Despite significant progress in improving access to education, issues revolving around quality and equity remain a major concern with over 77% of students learning-poor.

Unlocking education data can provide valuable insight into the challenges faced by the education system and inform policy and practices for the best routes to tackle these challenges and improve attainment. This is however a very daunting task considering the country’s complex educational system, as well as its diverse range of institutions, programs, and data sources. How can we make sense of the vast amount of data available and use it to improve educational outcomes for learners?

In this article, we explore the challenges and opportunities of navigating Cameroon’s educational data ecosystem. We build on the assumption that by understanding the connections between the key players, data sources, and tools available, we can make informed decisions and drive positive change in education. Specifically, we will discuss the role of government agencies, universities, and NGOs in collecting and analyzing data. By the end of this article, readers will have a better understanding of how to navigate Cameroon’s educational data ecosystem and use data to improve educational outcomes.

A – Complex education data ecosystem with a variety of stakeholders

Cameroon’s education data ecosystem is complex and diverse, with multiple actors and sources involved in the collection, management, and dissemination of information. Government agencies are the primary authority for education data in Cameroon, overseeing the collection and management of data from various educational institutions across the country. Six ministries oversee the education sector in Cameroon. These are the Ministry of Basic Education (MINEDUB), the Ministry of Secondary Education (MINESEC), the Ministry of Higher Education (MINESUP), the Ministry of Employment and Vocational Training (MINEFOP), the Ministry of Social Affairs, and the Ministry of Youth and Civic Education (MINJEC).

Each of these ministries is responsible for a particular subsector of the education landscape and is therefore collecting, analyzing and disseminating data solely for that sector. They all use different methods for collecting and compiling data, making it difficult to compare or aggregate their data. This is mostly due to the absence of a coordination mechanism at institutional levels. The Division of Education, Teaching and Research at the prime ministry could fill this gap, ensuring coordination between these ministries. However, they are understaffed and under-budgeted. One final state actor intervening in Cameroon’s education data ecosystem is the National Centre for Education at the Ministry of Scientific Research and Innovation with the mission of conducting research in the field of education and building the capacity of educational stakeholders. 

Other actors collecting, compiling, and disseminating education data In Cameroon include the National Institute of Statistics, universities, international organizations, local NGOs and actors from civil society. These stakeholders are all motivated by the desire to improve educational outcomes; however, they operate in silos, reducing the scope of their impact. Therefore, there is an urgent need for the creation of a holistic and inclusive education data network ensuring collaboration between actors for increased access, use and sharing of data.

B – MINEDUB and the premise of a functional Education Management Information System

The education data management system championed by the Ministry of Basic Education is by no doubt one of the most advanced in the country today. The Department of Planning, Projects, and Cooperation of the Ministry of Basic Education is responsible for drawing up and updating the school map; centralizing and processing statistical records; collecting data on various education systems; putting in place a databank; and normalizing the data collected. In order to achieve these tasks, they partner with various actors at central and decentralized levels including, regional and divisional delegations, the National Institute of Statistics and international agencies such as UNESCO or UNICEF, the latter providing technical assistance and support for education data collection and analysis. This synergy of actors produces useful and reliable educational data for decision-makers, donors, and other data users. However, data collected remains insufficient as it focuses primarily on broad outcomes like enrollment, attendance, academic performance, resources etc… There are invaluable educational data sources mainly coming from other actors within the data ecosystem which are available but unexploited.

Developing and maintaining a functional, inclusive, and sustainable education data ecosystem is essential for achieving predetermined educational goals. Data is crucial in providing a better understanding of the current situation, setting goals, elaborating benchmarks, and measuring success. In a context like Cameroon with multiple actors intervening in diverse education sectors, it is important to understand the role and capacity of each of these actors, establish a working relationship between them and build solid a network of partners working in tandem towards promoting data-driven decision making in education. Education data mapping stands out as the ideal strategy to achieve this aim. Beyond understanding what education data exists and is accessible, it will involve mapping the various actors, their skills, and experiences, and bridging the gap between them. We aim to do this using the methodology and conceptual framework developed by the Unlocking Data consortium. Case studies from Kenya, Malawi and Sierra Leone using this approach are a testament to the benefit of this process as shown in this guidance note. We look forward to sharing our experience of undertaking this approach in Cameroon with the whole Unlocking Data community.

Image by Freepik

Guidelines for Mapping Education Data in Sub-Saharan Africa

BY TASKEEN ADAM AND IRENE SELWANESS | Originally posted on EdTech Hub

© SHUTTERSTOCK/1417078181

Are you a government official, NGO or researcher looking to understand what education data is available locally? Our new guidance note shares practical lessons learnt from mapping the availability of education data in Kenya, Malawi, and Sierra Leone.

Last year, we posted about the Unlocking Data initiative and its goal to support access, use, and sharing of education data to effectively tell the story of education in Africa. In 2020,  we hosted a series of workshops that aimed to unpack the biggest barriers in data sharing. At these workshops, the community of practice realised that before we can truly discuss (re)using education data effectively, we need to understand what data exists, where the data gaps are, and what data indicators are needed for decision-making. To delve into the topic further, we hosted an event to showcase early ‘Lessons Learnt from Education Data Mapping in Africa’ and created a working methodology for education data mapping.

Moving from theory to practice

Unlocking Data and its partners have been working towards mapping education datasets in selected African countries. Through sharing lessons between the different mapping exercises, we realised that mapping education data happens in different ways. This could involve various stakeholders and can be conducted for a wide range of purposes. We found these different practical aims and approaches to be enlightening and incredibly beneficial to others, so we combined them into a guidance note on mapping Africa’s education data. 

Building on the data mapping methodology, the guidance note takes the theory to practice, sharing practical experiences, lessons learnt, and challenges encountered.

What can you find in the guidance note?

This guidance note would not have been possible without the key insights from the partners we interviewed. We are grateful for their contributions:

  • Eldah Onsomu shared insights on the mapping of Technical and Vocational Education and Training (TVET) data in Kenya
  • Esme Kadzamira shared insights on the mapping of administrative and survey data in Malawi, and
  • Iman Beoku-Betts and Chris McBurnie shared insights from the mapping of the supply and demand for education data in Sierra Leone.

The guidance note explores the different questions, purposes, successes, challenges, and key considerations learnt from these mapping initiatives, highlighting factors that other countries and stakeholders pursuing data mapping may find useful.

Initiating a data mapping project can be quite daunting. We found that it is important to scope it well from the onset, understanding what you are — and are not — hoping to achieve from the exercise. To assist future data mappers in scoping, the guidance note unpacks various rationales and approaches of the three data mapping projects through the following questions:

  1. What are the different purposes driving data mapping? 
  2. Who are the potential stakeholders in the process, and who are the end-users for this data mapping exercise? 
  3. What is the area of focus in education?
  4. What are the types of data that the data mapping intends to cover?

What key challenges did we identify in these data mapping projects?

Our review of  the different mapping projects identified  key challenges that are useful for data mappers to consider:

  1. Accessing and analysing data: Issues such as lack of data availability and/or accessibility, trust in data security, and skills to analyse data impact and the use of, and demand for, secondary data.
  2. Coordinating stakeholders: Data mapping involves multiple stakeholders (e.g., government officials, researchers, and non-governmental organisations) and getting a commitment from and convening and coordinating stakeholders is challenging.
  3. Presentation and dissemination of the mapping project output: Decisions around the most effective means of cataloguing and visualising the mapping output (i.e., whether a presentation, report, database or dashboard) have not yet been ascertained.
  4. Resources: Scoping the timeline and human resources needed for the mapping project is difficult as the amount of data is unknown, existing skillsets within teams vary, and the availability of key stakeholders can be erratic.

What’s next for Unlocking Data?

The strength of Unlocking Data is in its community, therefore, we want to learn more from you! What are you or your organisation doing to support access, use, and sharing of education data? In the next few weeks, we’ll be launching our call for more content, so you’ll be able to share your experiences with the network! To keep up-to-date with our knowledge-sharing blogs, upcoming events, and report releases,  


We held a workshop with Decent Jobs for YouthEdTech Hub and Zizi Afrique to get stakeholders’ views on data relating to youth skills and employment.

On the 6th of May 2021, our workshop brought together over 70 stakeholders in the education sector and industry from over 8 countries: Columbia, Pakistan, Ghana, South Africa, Kenya, Senegal, Canada, and India.

Moderated by John Mugo, Executive Director of Zizi Afrique, the launch saw the participation of various representatives of organizations including the International Labour Organization, MasterCard foundation, eBASE Africa, VVOB, UNICEF, GIZ, UNFPA and Traore Consulting. Through breakout sessions, participants shared their experiences, challenges and solutions in accessing data on education & youth employment in Africa.

In regions where government data is limited, unlocking the patchwork of data collected for baseline evaluations, landscaping studies and feasibility assessments would give decision makers a bigger picture of the state of education in their countries.

John Mugo, who participated in one of the breakout sessions aimed to interact with many people from different contexts to deepen his own understanding and sensitize his attitude on how stakeholders could do better for the benefit of all youth globally.

“The biggest gap is the use of evidence to connect trainers and employers to transform the way youth access opportunities post-training.”

The Chief Executive Officer of ESSA, Lucy Heady was grateful to participants for their contributions and highlighted the need for more collaborations to improve education and work for young people in Africa.

“So much energy, so much ambition from the group, it was really exciting to see”.

Visit the new Youth Foresight, a knowledge facility launched by Decent Jobs for Youth in partnership with Generation Unlimited. Tap into this network of knowledge, action and resources; supporting more jobs for young people.


“Strategies implemented in schools to maximize student learning should be evidence-based.”-The Australian Institute for Teaching and School Leadership 

Evidence-based education is an approach to teaching and learning that emphasises using empirical research to guide classroom instruction decisions and practices. This approach aims to ensure that educational methods and interventions are effective, efficient, and aligned with the latest available scientific findings on how students learn and develop. 

Florio, (2016) traces the foundations of evidence-based education back to the success of evidence-based practices in other fields, such as medicine, healthcare, and management. The growing momentum of evidence-based education over the past three decades has been driven by the desire to move away from reliance on intuition, tradition, or personal experience, and instead base educational decisions on rigorous, objective, and replicable research.

Multiple sources of evidence

Evidence can come from a variety of sources, including randomised controlled trials, longitudinal studies, meta-analyses, and case studies.

Challenges in application

Although the role of evidence in the education system is not currently in doubt, equally research also tells us that teachers rarely apply this evidence to inform their classroom teaching. While this pool of evidence exists ways and means are scarce of mobilising this evidence into usable bits for classroom use. Simply put a lot of innovative education interventions exist but only a handful are put to use due to a lack of awareness of their existence as well as application evidence on how to use them. 

According to the Glossary of education reforms, the debates about and around evidence use in education systems depend largely on the existence and actual use of the available evidence. For instance, policymakers at national and sub-national levels, teacher trainers, teachers and researchers sometimes argue that the body of existing evidence is too big a forest to mine what is useful, or even impossible, for schools and educators to act thoughtfully and appropriately on available evidence, given that it is not synthesised and therefore would classify it as unavailable. In other cases, governments, schools and school systems may largely or entirely ignore available evidence; subsequently, perpetually known school problems may go unaddressed on one hand, while effective, well-established teaching practices and innovations are never adopted and the system is plunged into a “rudderless mass” of evidence-informed policy initiatives. 

Increasing Use and Users of Evidence

So how can we increase the uses and users of education evidence in the education ecosystem? While this blog was not intended to answer this question it was intended to ignite other questions. While previously funders have supported extensive efforts to expand the production of evidence in education the wind is blowing from generation towards uptake of the evidence generated. Think of it this way: researchers and organisations have carried out research over several years whose results and learnings lie with them or the funder. Proponents of evidence-based practice propose platforms for knowledge sharing and collaboration generated through co-creation initiatives to synthesise such findings into one document or theme. Such platforms act as repositories of published research outputs, grey research as well as public goods such as ed-tech, guidelines and frameworks which go a long way, especially in making research products available, accessible and affordable. 

Such co-creation initiatives by different actors in the education ecosystem overcome the multiplicity of evidence generation. Tons of papers inform of student theses lie in libraries and occupy space in their online repositories while there is no chance that the findings lying there will ever be found and at least shared if not implemented. The immense evidence in those Masters and PhD theses does not become invalid just because they are unpublished or are published in “predatory” journals based on some classification. Evidence is evidence unfortunately the “fountains of knowledge” repositories do not communicate with each other. How do they even ensure the originality of the student’s work in the face of AI? How can we motivate the students and faculties to get their work published to enhance the visibility of the evidence generated? 

Barriers to evidence use

This blog cannot be complete without addressing the politics and gatekeeping in access to data which cuts across the data landscape. Even within the government different departments cannot share evidence and even when it is possible none is willing to use the other departments’ evidence-sometimes departments within the same organisation. Issues of the government not trusting the credibility of evidence generated by non-state actors demand co-creation. Where funders are involved, gatekeeping comes in the form of ownership of the evidence generated. A probable solution to this challenge apart from co-creation is establishing communities of learning where evidence generators and users share a platform to discuss the generation and use of evidence.

“Expanding the skill to recognise quality research is essential to help teachers and school leaders become better consumers of evidence.” ~Teacher Magazine

The assumption so far is that while evidence is available synthesised or otherwise, the users have the requisite capacity to use the evidence in their processes and decision-making. Far from it, evidence generators must ignite the demand for evidence users to utilise available evidence in education. The trend has been to address the supply side by making research findings as simple as possible and using different mediums to present the evidence. The demand side, however, requires equal attention to ensure we address the width and the breadth-increase the uses and users of the available evidence produced. The establishment of a community of learners as a platform for stakeholders to learn can be used as a platform to set research agendas that guide the whole country’s research compass towards demand-driven research and innovations.

Education system cultures that vary by jurisdiction may not be encouraging or seen to promote the use of evidence because teaching practice is heavily dependent on directions from respective ministries. A study of teachers in Australia showed that teachers sometimes view the adoption of external evidence as a way of taking away the teachers’ autonomy in the classroom. The issue of validation of proven innovations may affect the adoption of evidence especially where assessment data does not support the practitioners’ innovation. There is also observable affinity by the government to hold at a higher value and adopt external evidence compared to locally generated and assembled evidence.  For instance, Kenyan teachers in National schools may fail to adopt innovations from County and extra-county schools.

What comes out clearly and shown by research is that mere accessibility to raw or synthesised research evidence is not generally an effective way of getting it used, even if that evidence is presented to users by knowledge-brokers, in short courses or workshops. What is more likely to work for both policy and practice is the packaging of high-quality evidence into a more usable format and presenting it actively or iteratively via a respected and trusted conduit, or through other mediums such as legislation. Having the users do the research is another promising approach. funders should require grantees to use evidence assembled in evidence hubs and libraries created using their grants in previous projects. This can be facilitated by a supportive evidence-use culture across the education ecosystem.


Have you ever had a performance review that really hit home? One where you felt maybe your manager could see into your soul? Mine came a few years ago. I had been called out for not doing enough to implement a new reporting system. In response I mumbled something about being under pressure with all the other things on my plate.

My manager looked me in the eyes and said, “the thing is Lucy, I know you, if you want to make something happen you can. You just didn’t care enough.” I had no come back. She was right. I hadn’t cared enough, but until that moment I had not seen that this was the problem.

If we, the global education sector, were to give ourselves a performance review, what is the thing we could make happen if only we cared enough? I point the finger at sharing data.


Much is made of the need to build education research capacity in the Global South and yet we fail to invest in one of the simplest ways to do this: let us match scholars from countries in the Global South and their students, with the data sets they need to become experts in education research.

The last 15 years has seen an explosion in research and evaluation in education. We are convinced by the power of strong monitoring and assessment to contribute to effective education systems. Of course, the critic can point to how far we lag behind the health sector or how we are still finding the right mix of research methods to properly influence policy and practice, but no one can deny the progress in understanding impact.


Data sets languish on the hard drives of academics, consultants and funders. In the best case scenario, they are rigorously analysed and published in an open-access journal but frequently they will be used to develop private reports that benefit only a paying client.

If data is only ever analysed by those who collect it, we miss out on the wealth of human imagination that could be brought to bear on it.

Different perspectives bring new thinking, new ways of combining data across studies, new research questions.

Anyone who has done a Master’s degree in a social science knows the pain of finding a good data set to analyse for their dissertation. We go where the data sets are. Data availability defines entire academic careers. Opening up data attracts the best minds to a discipline and increases access to those without the resources to collect primary data.

Last year Addis Ababa University hosted a meeting with the REAL Centre at Cambridge and the Centre for Global Development for African leaders in education research, based on findings from the African Education Research Database. Lack of access to datasets was highlighted by those attending as a major barrier to improving the discipline of education research on the continent and increasing influence with policy-makers.

There are lots of reasons why sharing data is hard: it costs money, data must be properly anonymized, academics are keen to harvest the publications they can before sharing further and so on. But none of these are killer problems if we care enough.

There are numerous examples of data repositories from the UK Data Archive to the Global Health Observatory which have set up approaches to access and governance that suit the needs of their communities.


It unlikely that any new primary data will be collected for months and so all existing data has become even more precious. Many researchers and their students will have had their plans change. While many will be absorbed with responding to the crisis, there will also be many with analytical capacity to spare.

Let’s do what we can now to direct this spare capacity to the education sector and build up the next generation of education researchers.

As a first step, we would like to crowd-source a list of education data sets that are already available so that it is easier for interested researchers to access them.

The next blog in this series discusses how we can accelerate research on these data sets by scholars from sub-Saharan Africa and their students.

Now is the time to open up access to data sets in education, to release those spreadsheets from dusty hard drives. We can do this; we just need to care enough.

We are building a list of open access education data sets.

If you would like to add to this list, or contribute an idea to our blog series ‘Doing more with Data’ please email


It is thought that the extended closure of education institutions following COVID-19 could worsen inequity in many ways. Scholars on the continent can use this moment to provide solutions through analysis of the situation and publication. However, the research output of African scholars has been the lowest in the world.

Connecting African scholars to quality data may help accelerate research output in Sub-Saharan Africa, and improve education and learning on the continent.

Though Africa is home to 17% of the world’s population, less than 1% of the global research output originates from Africa.

Some authors relate this to the poor ranking of African Universities. In the Ranking Web of Universities (2020), only 4 of the African Universities are ranked among the top 500 universities globally. All the 4 are from South Africa. The top ranked University of Cape Town is ranked 276th globally.


Looking at what is written about this, the perspectives of African scholars are poorly represented. First, poorly matched by resources, the expansion of the university in the last decade has yielded an extremely poor lecturer to student ratio.

In most social science classes, it is common to find one lecturer in front of 1,000 students. The teaching workload, exacerbated by marking of scripts in an examination, rather than knowledge driven education system, is one untold scholarly nightmare.

Related to this, the low ratio of Ph.D. holders to graduate students has yielded very poor supervisor ratios. One scholar lamented:

“At one time in my early years of scholarly life I was supervising 11 PhDs and 24 Masters students.”

At the same time, the relatively low salary of university scholars, against the expectations of being the most educated in society, yields pressure. Scholars are often trapped in part-time teaching of commercial courses (referred to as moonlighting in Kenya) or leading a life of consultancies.

Access to research funding is poor, as most universities have sunk their capital into the development of infrastructure to accommodate the swelling student populations.

Combined, these circumstances present the worst recipe for research output.


In 2018, documentation by Duermeijer and others established that in Africa, scientific production grew by 39 % between 2012 and 2016, the fastest in the world. However, much of what is published is in the health sector and other areas of the economy. Despite the fact that most scholars are in education (within universities), publications in education are relatively low.

The education closure following COVID-19 offers a moment of reflection on how we, African scholars, could change the landscape.

Though teaching is moving online for most universities, the burden of moving to class and marking physical scripts is less. Many research consultancies have dried up now, and a dip in field research opportunities is expected in the period of recovery that follows.

This period, and the next months, present a grand opportunity for scholars to pick up analysis and writing. This may be the best time for African scholars to pick up the broken pieces, and demonstrate their resilience.


Many solutions to the improvement of scientific output have been sought, including facilitating greater access to data and analytical tools, increasing funding, and restoring a balance between teaching and research workloads.

Despite the low scientific output, the amount of data generated on Africa’s soil is immense. Most of these, however, sit idle on closed datasets and in unpublished research reports, gathering ‘dust’ in the hard disks and flash disks of scholars and programme officers.

While collecting good data is expensive, many organizations and funders have invested heavily to collect data on various development issues. Most of these datasets are hardly scratched to generate knowledge.


First, a call is made to African organizations and funding partners to make their data available, but also contribute modest resources to facilitate analysis and publication. Making data available is a powerful imperative to our commitment to Africa’s development.

On the other hand, senior scholars can work with junior scholars and graduate students to land on the data, mine knowledge, publish, tell our stories and help improve learning and development for Africa.

Investing in rapid cleaning, anonymization and publishing of data can be possible, as Africa is not low on statisticians. At the same time, creating fellowships is necessary to incentivize analysis, publication and presentation in conferences to share this knowledge.

Now we will wait to see who reads this, and who wants to achieve this goal with us. 

 We are building a list of open access education data sets. Here are some of the education data sets that are available by the Zizi Afrique Foundation,

  • A national study on youth and skills among youth not in education, employment or training in Kenya (2019).
  • A study of youth supply and demand among entry level youth employees and employers in various sectors in Kenya (2019).
  • A study on youth and skills among youth not in education, employment or training in Kenya (2019). 

If you would like to add to this list, or contribute an idea to our blog series ‘Doing more with Data’ please email