The structure of Rwanda’s basic education system is asymmetric, with many more students enrolled in early grades than in later grades. According to 2018 data from the Rwandan ministry of education (MINEDUC), student enrolment in primary 1 (517,243) was about double the enrolment in primary 6, and eleven times the number of children at the end of secondary 6. This lopsided structure is the result of a rapid increase in the intake of students at primary 1 level and the balance of progression, dropout and repetition observed in each cohort of students. All these factors mean that predicting, and planning for, the number of students attending a grade next year is far from simple.
Laterite’s proof of concept shows that it is possible to use Markov chains and available data to create evidence-based models to support planning and decision-making for the education sector. Our approach deploys Markov chains to model the enrollment structure in the Rwandan school system using data from MINEDUC statistical yearbooks and Laterite’s report on Dropout and Repetition.
Laterite’s proof of concept forecasts enrollment trends in the Rwandan school system up to 2024. The results suggest that the secondary school population will almost double in the next four years, while enrollment rates in primary school will remain at today’s values. This has implications for resource allocation & planning across schools in Rwanda, specifically on the number of teachers that will need to be trained if current pupil-to-teacher ratios are to be maintained.