Education must deal with demographic challenges

10 March 2021


Régis L'Hostis
In 2021, more than a quarter of Africa's population is of school age. By 2035, these young people will be on the job market.

Investing in education requires a good understanding of the potential demand. In sub-Saharan Africa, the population of 6 to 15-year-olds is projected to increase by 60% over the next 30 years, from just over 280 million in 2020 to approximately 450 million in 2050. To ensure quality basic education for all children, it will be necessary to add some 9 million classrooms and recruit 9.5 million teachers. Learn more in the latest edition of PôleMag.

To help governments plan for the future and take effective action today, economists and education planners use simulation models – a tool that represents a country’s current education system and projects the possibilities for medium- and long-term development.

Population dynamics provide the basic data for simulation models. The principle is to compare the potential demand for education – the school-age population – to the supply of education and the resources available in the system. The school-age population is generally projected over a 10-year period, and the model forecasts needs at the different levels of education: from pre-primary, basic education, secondary education, through to higher education, and vocational training.   

“While having population data is a key element in simulation models, understanding how the population will evolve and the part that will be eligible for education is more important,” says IIEP-UNESCO Dakar policy analyst and planner Polycarp Omondi Otieno. “Once the school-age population is identified, we have to hypothesize what it will take to deliver quality education services to them.”

Simulation models can help countries answer questions such as how many schools and associated facilities are needed to meet the demand for education over the next decade? How many teachers will the government have to recruit, at which level, and for which subjects?  How many textbooks, teaching aids will be required? The model projections empower decision-makers with essential information on these and other important issues.

Namibia in focus

IIEP is currently developing a model in Namibia, where the vast landscape and sparse population poses challenges to teacher deployment. “In addition to the low population dynamics, Namibia has a unique case of high teacher flight – or turnover,” explains Otieno. “This makes it challenging to plan and manage schools and to meet the pedagogical needs of every region.” But now, 14 simulation models – one for each national district – are bringing different scenarios to life, helping to set a path towards the establishment of a qualified and sustainable teaching force.

The model is forecasting how many teachers will be needed from pre-primary, through to upper secondary school immediately and in the future, and for each region. In addition to projecting teacher needs by school level, the model looks at how many teachers will be required by subject in upper primary and secondary, while also examining the upgrade of unqualified teachers to ensure a quality teaching force. This model is linked to the national capacity of teacher training institutes to guide the output in the medium and long-term.

Pinpointing the best options

Generally, simulation models develop different scenarios to decide on the best policy options. In other words, those that are financially, socially, and materially sustainable. For example, in order to control a ministry of education’s salary expenditure, decisions can be made in terms of the salary scale, or the compensation for contract and civil servant teachers. Contract teachers will cost the state less, but their non-permanent status may ultimately undermine the social balance of the system. The simulation model can estimate both the financial and social sustainability of the different options and help ministries make informed recruitment decisions.  

“Collaboration between education administrations, statistics agencies, and research institutions is essential. Together, we will be able to better meet the needs of basic education in sub-Saharan Africa, and prepare for the effects of future changes,” says Koffi Segniagbeto, head of IIEP-UNESCO Dakar.

In Sierra Leone, IIEP recently wrapped up its support in the development of an education sector analysis. Now, in preparation for the country’s next education sector plan, IIEP is applying simulation modelling to weigh different development policy choices. Otieno explains that once the model determines the volume of students for each level of education, it can identify various educational inputs needed to deliver education to children. Leaders and managers can then make important policy decisions, such as whether to build more classrooms or schools, and where. 

The type of infrastructure to be built is also an important issue. In recent years, African states facing severe budgetary constraints have sharply reduced their investment in education infrastructure. These costs are now mainly supported by technical and financial partners. Basing their decisions on financial models, some states are now reversing this trend and adopting higher quality thatch classrooms with toilets and sports facilities. These structures cost half that of classrooms with solid walls.

Population dynamics also impact the organization of classes at school. In densely populated areas with poor infrastructure, countries sometimes have to resort to double shift systems in which students are split into two groups, with one coming in the morning and the other in the afternoon. In areas where there are not enough students, one option is to organize multi-grade classes. Simulation models can be used to make regional projections and to adjust school organization to the local school-age population.

Based on a detailed understanding of population trends, education simulation models help policy-makers understand the cost implications and trade-offs associated with each policy decision.