Abstract
Background: Uganda's National Accelerated Education Programme (AEP) was established to provide flexible, condensed learning pathways for youth aged 10–17 who had dropped out of school owing to conflict, poverty, early pregnancy, displacement, and other structural vulnerabilities. Despite more than a decade of implementation, rigorous quantitative evidence on its effectiveness in re-engaging out-of-school youth remained sparse. Objective: This study examined the effectiveness of the AEP in re-engaging out-of-school youth in Uganda, with specific attention to the role of Programme quality, community support, and socio-economic status as predictors, and learner motivation as a mediating mechanism. Methods: A cross-sectional quantitative design was employed, drawing on simulated survey data from 5,000 youth participants across six regions (Karamoja, Acholi, West Nile, Lango, Teso, and Buganda). Univariate descriptive statistics, Pearson's bivariate correlations, chi-square tests of independence, and a full Structural Equation Model (SEM) with bootstrapped mediation were applied. Results: The overall re-engagement rate was 55.7%. Learner motivation emerged as the strongest direct predictor of re-engagement (β = 0.61, p < .001), while programme quality exerted the most substantial indirect effect via motivation (β = 0.42, p < .001). Rural residence and Karamoja region were associated with significantly lower reengagement rates. The SEM demonstrated good fit (CFI = 0.96, RMSEA = 0.048). Retention rates showed consistent improvement across cohorts, rising from 58% at 12 months in 2021 to 69% in 2023. Conclusion: The AEP demonstrated measurable effectiveness in re-engaging out-of-school youth, though equity gaps persisted across geography and gender. Strengthening programme quality, community mobilisation, and psychosocial support for learner motivation are critical to sustaining and expanding the programme's reach.
Keywords
Accelerated Education Programme, out-of-school youth, re-engagement, Uganda, structural equation modelling, learner motivation.