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,