Primary school dropout remains a critical barrier to achieving universal education in Uganda, with socioeconomic factors identified as key determinants. This study investigated the extent to which household poverty and ancillary school costs contributed to primary school dropout among children aged 6–14 years in four regions of Uganda. A cross-sectional survey was conducted among 1,200 households sampled using a multi-stage cluster sampling approach. Quantitative data were collected using a structured household questionnaire administered to caregivers, while qualitative data were gathered through focus group discussions and key informant interviews. Univariate analysis described the characteristics of respondents and the prevalence of school dropout. Bivariate analysis using chi-square tests and independent samples t-tests examined associations between household poverty indicators, ancillary cost burden, and dropout outcomes. Mixed effects logistic regression models were fitted to estimate adjusted odds ratios while accounting for within-district clustering. Results revealed that 29.4% of school-age children had dropped out of primary school. The odds of dropout were significantly higher among children from the poorest households (AOR = 6.82; 95% CI: 4.71–9.87), those in households with annual income below UGX 600,000 (AOR = 4.15; 95% CI: 2.93–5.88), and those facing high ancillary cost burdens exceeding UGX 150,000 annually (AOR = 3.47; 95% CI: 2.29–5.25). School fees, uniform costs, and examination fees were the most cited cost barriers. The study concluded that household poverty and ancillary school costs were independently and jointly associated with increased risk of primary school dropout. It is recommended that the Government of Uganda expand the capitation grant coverage to include all ancillary costs, introduce targeted conditional cash transfers for the poorest quintile
households, and establish community-based bursary funds to bridge the financing gap for vulnerable learners.

School-level 'gaming practices' — covert, systematic strategies through which school administrators manipulate learner registration, attendance records, and examination entry in order to inflate institutional performance metrics before national assessments — constitute a critically underexamined mechanism of learner exclusion in Uganda's primary education system. This study examined the nature, prevalence, and institutional determinants of gamingpractice-induced learner exclusion before the Primary Leaving Examinations (PLE) in Uganda, focusing specifically on how such practices operate, which learner profiles are most disproportionately targeted, and what structural, socioeconomic, and institutional factors predict the probability of exclusion. A cross-sectional quantitative design was employed, using a structured questionnaire administered to 500 Primary Seven learners and recent school leavers from 30 purposively selected primary schools across rural and urban districts in Uganda. Data were analysed using univariate descriptive statistics, bivariate Pearson chi-square tests, and binary logistic regression. The study found that 42.8% of respondents had been excluded through one or more gaming practices, with the most prevalent mechanism being invisible withdrawal or de-registration from examination rolls (66.4% of excluded learners). Learners who had personally witnessed gaming practices were 16.8 times more likely to have been excluded (Adjusted OR = 16.8; 95% CI: 9.4-30.0; p < 0.001) after adjusting for school type, location, household income, parental education, parental advocacy, and class repetition history. Exclusion rates were highest in government schools in rural areas (81.4%). The study concluded that gaming practices constitute a systemic and structurally embedded violation of the right to education, disproportionately targeting the most economically and socially marginalised learners, and recommends urgent policy reform including mandatory independent audit of PLE candidate rolls, community-based accountability mechanisms, and strengthened child rights complaint pathways.

This study set out to map primary-to-tertiary attrition rates and structurally model their determinants within Uganda's education system, motivated by the persistent gap between near-universal primary enrolment and the markedly low proportion of learners who ultimately accessed tertiary education. A simulated cross-sectional cohort of 850 learners was constructed proportionally from Uganda's four administrative regions to reflect patterns documented in national education statistics, with each record capturing demographic characteristics, key structural determinants — including household income, parental education level, distance to school, school type, and a composite school infrastructure quality index — as well as attrition status recorded at four successive pipeline transitions: Primary One to Primary Seven (P1–P7), Primary Seven to Senior Four (P7–S4), Senior Four to Senior Six (S4–S6), and Senior Six to tertiary entry (S6–Tertiary). Data were analysed through univariate descriptive statistics, bivariate chi-square tests, independent-samples t-tests, and point-biserial correlations, before structural equation modelling (SEM) was applied with maximum likelihood estimation and robust standard errors, specifying Household Socioeconomic Capital, School Infrastructure Quality, and Geographic Accessibility as latent predictors of attrition. Findings revealed a monotonically accelerating pattern of cumulative attrition, rising from 21.4% at the P1–P7 transition to 38.7% at P7– S4, 46.2% at S4–S6, and 61.8% at S6–Tertiary, with the Northern region recording the highest overall attrition rate at 56.3%. Bivariate analysis confirmed statistically significant associations between attrition and all structural determinants examined (p < 0.001), though individual effect sizes fell within the small-to moderate range. The structural model demonstrated good fit (CFI = 0.954, TLI = 0.941, RMSEA = 0.046, SRMR = 0.038) and identified Household Socioeconomic Capital as the strongest direct determinant of attrition (β = −0.42), followed by School
Infrastructure Quality (β = −0.31) and Geographic Accessibility (β = 0.27 direct; β = 0.34 total), with the total effect of geographic accessibility incorporating a significant indirect pathway through which remoteness eroded household socioeconomic capital, thereby amplifying attrition risk through a second, compounding channel. The study concluded
that learner attrition across Uganda's education pipeline was structurally produced by the interlocking influence of
household poverty, school infrastructure deficits, and geographic remoteness, and recommended that effective policy
responses address these determinants simultaneously through targeted household financial support, infrastructure investment in remote government schools, and expanded geographic accessibility interventions such as school transport schemes, satellite campuses, and all-weather road development.

Multi-sectoral coordination remains a fundamental challenge in the effective implementation of social policies in subSaharan Africa, and Uganda presents a particularly instructive case given its complex governance architecture, diverse
sectoral mandates, and persistent service delivery gaps. This study investigated multi-sectoral coordination challenges in Ugandan social policy implementation, guided by three specific objectives: to examine the nature and extent of inter-agency communication barriers, to assess the relationship between resource allocation efficiency and policy implementation fidelity, and to evaluate the structural pathways through which leadership commitment and stakeholder participation influence overall coordination effectiveness. A cross-sectional survey design was employed, with data collected from 312 purposively sampled policy implementers drawn from five key social sectors — health, education, water and sanitation, agriculture, and social protection — across twelve districts in Uganda. Primary data were gathered using a structured, pre-tested questionnaire containing validated Likert-scale instruments. Descriptive statistics revealed that inter-agency communication scored a mean of 3.42 (SD = 0.87), while resource allocation efficiency recorded the lowest mean of 2.89 (SD = 1.02), suggesting persistent bottlenecks in financial coordination. Bivariate Pearson correlation analyses confirmed significant positive associations between all coordination predictor variables and overall coordination effectiveness (r = 0.714 for ICS; r = 0.632 for RAE; p < .001). A Structural Equation Model (SEM) was estimated using AMOS, yielding excellent model fit indices (CFI = 0.967; RMSEA = 0.043; CMIN/DF = 1.32), with the full model explaining 58.7% of the variance in overall coordination effectiveness. Path analysis revealed that inter-agency communication exerted the strongest direct effect (β = 0.412, p < .001), while sector overlap conflicts exerted a significant negative effect (β = −0.198, p = .001). The study concluded that structural communication deficits, fragmented resource flows, and sector overlap conflicts constitute the primary impediments to effective social policy implementation in Uganda. Recommendations include the institutionalisation of interministerial coordination frameworks, the establishment of unified budget tracking systems, and the strengthening of
participatory policy implementation platforms at district and sub-county levels.

Uganda's education and skilling policy discourse has, over the past decade, converged on the language of a 'skills gap' to explain youth unemployment and weak labour absorption, attributing the problem largely to mismatches between what graduates know and what employers need. This study interrogated that framing empirically and conceptually, asking whether the 'skills gap' is a verifiable labour-market phenomenon or a case of conceptual displacement in which structural, wage, and firm-level constraints are relabelled as deficiencies of graduates and training institutions. Adopting a cross sectional analytical design, the study surveyed 420 formally registered firms across 14 districts of Uganda, capturing firm characteristics, training investment behaviour, wage offers, graduate qualification profiles, and firms' self-reported perception of a skills gap among recently hired graduates. Data were analysed using univariate description, bivariate chi-square and t-test comparisons, and a multilevel mixed-effects logistic regression with firms nested within districts to account for geographic clustering and unobserved district-level heterogeneity. Overall, 60.2% of firms reported a skills gap among recent graduate hires. Bivariate analysis showed that firm size, training investment, and qualification mismatch were significantly associated with reporting a skills gap (p

School dropout remains one of the most persistent structural inequalities in Uganda's education system, and nowhere is this more acute than in the Karamoja sub-region. This study examined regional disparities in school dropout between Karamoja and national trends, drawing on a cross-sectional comparative design with a stratified random sample of 847 respondents, including students, teachers, parents, and local education officials, drawn from 32 schools across three Karamoja districts — Moroto, Kotido, and Napak — and a nationally representative comparison stratum of 18 districts across Uganda's four administrative regions. The study was anchored in the Social Exclusion Framework and Human Capital Theory. Descriptive analysis revealed that Karamoja's overall dropout rate stood at 57.6%, compared to 28.7% nationally, with the upper secondary level recording the starkest contrast at 72.4% versus 44.2%. Bivariate analysis using chi-square tests confirmed statistically significant associations between dropout and key determinants including poverty, gender, distance to school, cultural norms — particularly early marriage and cattle herding obligations — and teacher quality, all significant at p < 0.001. Structural Equation Modeling established that school absenteeism fully mediated the relationship between structural deprivation and dropout in Karamoja (β = 0.53, p < 0.001), with the Karamoja model explaining 67.4% of dropout variance compared to 53.1% nationally. Binary logistic regression further identified early marriage (OR = 6.83, p < 0.001), cattle herding obligations (OR = 4.57, p < 0.001), and poverty (OR = 3.84, p < 0.001) as the strongest predictors of dropout in Karamoja. The study concluded that Karamoja's dropout crisis is not merely a reflection of national trends but represents a structurally distinct and compounded educational emergency requiring targeted, context-sensitive policy intervention. It recommended the establishment of a Karamoja-specific educational emergency fund, integration of nomadic-responsive schooling models, and a district-level early warning system anchored in EMIS data.

Persistently weak learning outcomes in many basic-education systems have been attributed jointly to inadequate teacher quality and chronic under-resourcing of schools, yet the independent and combined contributions of these two factors to downstream skills deficits were rarely quantified within an analytic framework that respected the nested structure of educational data. This study examined the extent to which teacher quality and school resourcing predicted literacy-numeracy skills deficits among primary school learners, using a multilevel modelling approach that accounted for the clustering of students within schools. A cross-sectional dataset comprising 1,451 students nested within 60 primary schools was analysed. Teacher quality was operationalised as a composite index of qualification and experience; school resourcing was operationalised as a composite index of per-pupil funding, textbook availability, infrastructure, and staffing ratios; and the outcome, a skills deficit score, captured the magnitude of literacy-numeracy shortfall relative to grade expectation, with higher scores denoting greater deficit.
Univariate description, bivariate association testing, and multivariate two-level mixed-effects regression (students nested within schools) were conducted, followed by sensitivity analyses comparing the multilevel specification against naive pooled ordinary least squares (OLS), cluster-robust OLS, an outlier-trimmed multilevel model, and a random-slope multilevel model.
The null model intraclass correlation coefficient was 0.335, indicating that approximately a third of the variance in skills deficits resided between schools. In the adjusted multilevel model, teacher quality (b = -0.281, SE = 0.015, p < .001) and school resourcing (b = -0.525, SE = 0.202, p = .010) remained independent, statistically significant predictors of lower skills deficits after accounting for baseline ability, socioeconomic status, locale, and household reading support. Sensitivity analyses confirmed the stability of the teacher-quality effect across specifications, while naive OLS was shown to understate the standard
errors attached to school-level predictors. The findings indicated that both teacher quality and school resourcing exerted independent, policy-relevant, and reasonably stable associations with downstream skills deficits, and that failure to model the multilevel structure of such data risked misleading inference regarding school-level policy levers.

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.

This study examined the impact of Constituency Development Funds (CDF) on parliamentary accountability and legislative independence in Uganda, drawing on a sample of 312 respondents comprising Members of Parliament, parliamentary staff, civil society representatives, and community leaders. Employing a quantitative cross-sectional survey design, the study collected primary data using a structured, pre-tested Likert-scale questionnaire. Statistical analyses encompassed univariate descriptive statistics, Pearson correlation analysis, multiple linear regression, and Structural Equation Modelling (SEM) using maximum likelihood estimation. Results revealed that CDF transparency (β = .42, p < .001) and CDF oversight mechanisms (β = .35, p < .001) were significant positive predictors of parliamentary accountability, while CDF political interference exhibited a significant negative effect (β = -.28, p = .001). The regression model explained 52.1% of the variance in parliamentary accountability (R² = .521, F(3, 308) = 111.7, p < .001). SEM path analysis confirmed the structural relationships, with model fit indices indicating excellent model-data correspondence (CFI = 0.963, RMSEA = 0.048, χ²/df = 1.87). Parliamentary accountability significantly predicted both legislative independence (β = 0.51, p < .001) and constituency representation (β = 0.44, p < .001). The study concluded that CDF management quality—particularly transparency and oversight—is a critical determinant of parliamentary accountability in Uganda. Recommendations included strengthening CDF audit frameworks, depoliticizing fund allocation, and enacting independent parliamentary oversight legislation.

This study examined the relationship between legislators' educational qualifications and legislative oversight effectiveness in Uganda, motivated by persistent concerns over weak parliamentary and local council oversight of public resource utilization despite successive cohorts of more formally educated legislators entering office. The study was guided by one main objective and three specific objectives, namely: to examine the influence of educational qualification on the quality of legislative scrutiny; to assess the mediating role of oversight-related knowledge and skills in this relationship; and to establish the moderating effect of legislative experience on the link between education and oversight effectiveness. A cross-sectional survey design was adopted, drawing a sample of 220 legislators and council members from national and selected local government legislative bodies, selected through stratified random sampling. Data were analysed using univariate statistics (frequencies, percentages, means and standard deviations), bivariate techniques (one-way ANOVA, Pearson correlation and chi-square tests of association), and structural equation modelling (SEM) to test the hypothesised direct, mediated and moderated pathways linking education to oversight effectiveness. The univariate results showed that the majority of legislators held a bachelor's degree (42.3%), followed by certificate/diploma holders (33.6%) and postgraduate holders (24.1%). Bivariate analysis revealed a statistically significant difference in mean oversight effectiveness scores across educational categories (F(2,217) = 86.38, p < .001), with postgraduate holders recording the highest mean score (M = 75.4, SD = 8.9) compared to bachelor's degree holders (M = 63.1, SD = 8.8) and certificate/diploma holders (M = 52.4, SD = 7.8). A significant positive correlation was also found between years of legislative experience and oversight effectiveness (r = .234, p = .0005), and a significant association between educational qualification and the level of oversight engagement (χ²(4) = 72.89, p < .001). The structural equation model demonstrated good fit and confirmed that educational qualification
exerted both a direct effect and an indirect effect on oversight effectiveness through oversight-related knowledge and skills, while legislative experience positively moderated this relationship. The study concluded that educational qualification is a significant, though not sole, determinant of legislative oversight effectiveness in Uganda, and that, knowledge, skills and experience meaningfully condition this relationship. The study recommends targeted continuous professional development for legislators with lower formal qualifications, mainstreaming of oversight-specific induction training for newly elected legislators irrespective of qualification, and the institutionalization of mentorship pairing experienced legislators with less experienced colleagues to strengthen oversight capacity across Parliament and local councils.