This study examined the readiness of Ugandan universities to adopt Action Research (AR) as a mechanism for community engagement, with a case study of Metropolitan International University (MIU). Guided by three specific objectives — assessing faculty awareness and attitudes towards AR, evaluating institutional support structures for ARmediated community engagement, and examining the relationship between AR engagement and community engagement outcomes — the study employed a cross-sectional mixed-methods design involving 248 faculty members and 96 administrators drawn from MIU and five comparator universities using stratified random and purposive sampling. Quantitative data were analysed using univariate descriptive statistics, bivariate inferential tests (chi-square and Spearman's rho), and Structural Equation Modelling (SEM) with maximum likelihood estimation. Results revealed moderate levels of AR awareness (mean = 3.21 at MIU; 2.95 comparators) and a significant positive association between institutional support and community engagement readiness (r = 0.612, p < .001). The SEM model demonstrated acceptable fit (CFI = 0.94, RMSEA = 0.058) and confirmed that institutional support (β = 0.41), faculty awareness (β = 0.33), and administrative policy backing (β = 0.27) were significant predictors of AR readiness, which in turn significantly predicted community engagement (β = 0.52, p < .001). Administrative policy backing did not significantly predict community engagement directly (β = 0.21, p = .089). These findings underscore the need for deliberate institutional investment in AR training, research incentive structures, and community-university partnership frameworks. The study recommends mainstreaming AR in faculty development curricula, establishing dedicated
community engagement offices, and revising university research policy to formally recognise AR as a third-mission activity.

Maize (Zea mays L.) production in Uganda is threatened by devastating diseases including Maize Streak Virus (MSV), Grey Leaf Spot (GLS), and Common Rust (CR), which collectively reduce yields by 30–80% in affected fields. This study developed, tested, and evaluated an AI-based mobile application for early detection and classification of these three major maize diseases in Rukungiri District, Uganda. The application employs a Convolutional Neural Network (CNN) architecture trained on a dataset of 8,420 maize leaf images to classify diseases with high accuracy. The final model achieved an overall accuracy of 94.3%, with precision, recall, and F1-scores exceeding 0.91 for all three disease classes. Field testing with 60 smallholder farmers in Rukungiri demonstrated that the application improved disease identification speed and accuracy compared to traditional visual scouting. Farmers expressed high satisfaction with the app's usability and relevance. The study concludes that AI-powered mobile tools hold significant promise for precision agriculture and disease management in resource-limited settings.

This study assessed the effectiveness of neem (Azadirachta indica) leaf extract in controlling fall army worm (Spodoptera frugiperda) infestations in smallholder maize gardens in Ikulwe Village, Mayuge District, Uganda. The fall army worm (FAW), an invasive pest that first entered sub-Saharan Africa in 2016, had rapidly established itself as the most economically destructive pest of maize in Uganda, causing yield losses estimated at between 20% and 73% depending on infestation severity and management response. The study employed a randomised complete block design (RCBD) with four treatments: neem leaf extract at 100g/L, neem leaf extract at 200g/L, a positive control (lambda-cyhalothrin 5EC), and a negative control (distilled water). Data were collected on larval mortality rate, leaf damage score, and grain yield across three blocks over two growing seasons. Results indicated that neem leaf extract at 200g/L achieved a mean larval mortality rate of 72.4% and a leaf damage score of 2.1 (out of 9), comparable to the chemical control treatment (76.8% mortality, damage score 1.9) and significantly superior to the negative control (18.3% mortality, damage score 6.8). Grain yields in plots treated with 200g/L neem extract (3.12 t/ha) were notsignificantly different from those in chemical control plots (3.28 t/ha). The study concluded that neem leaf extract at 200g/L constituted an effective, affordable, and environmentally sustainable alternative to synthetic insecticides for FAW management among smallholder maize farmers.

Utafiti huu ulichunguza athari za Teknolojia ya Habari na Mawasiliano (TEHAMA) katika kuboresha ufundishaji na ujifunzaji katika Kampala University na Metropolitan International University zilizopo Kampala, Uganda. Madhumuni ya utafiti yalikuwa ni kutathmini jinsi matumizi ya TEHAMA yalivyoathiri ubora wa ufundishaji, ushiriki wa wanafunzi, na matokeo ya ujifunzaji. Utafiti ulitumia muundo wa utafiti wa mseto (mixed methods) ukijumuisha mbinu za kiasi na ubora. Sampuli ya washiriki 240 ilichaguliwa kwa kutumia mbinu ya uteuzi wa nasibu na makusudi kutoka vyuo vikuu viwili. Data zilikusanywa kupitia dodoso
lililoundwa vizuri, mahojiano ya kina, na uchunguzi wa nyaraka. Uchambuzi wa data ulitumia takwimu za maelezo na uchambuzi wa kiuchanganuzi kwa kutumia programu ya SPSS toleo la 26. Matokeo ya utafiti yalionyesha kuwa TEHAMA ilikuwa na athari chanya na kubwa katika ufundishaji na ujifunzaji (r = 0.74, p < 0.01). Zaidi ya asilimia themanini (82.5%) ya walimu walikiri kwamba matumizi ya TEHAMA yaliongeza ufanisi wa ufundishaji wao. Wanafunzi asilimia sabini na tisa (79.2%) walisema kwamba TEHAMA iliongeza uelewa wao wa masomo. Hata hivyo, vikwazo vikubwa vilivyoripotiwa vilijumuisha upatikanaji mdogo wa vifaa vya TEHAMA (64.6%), mafunzo duni kwa walimu (58.3%), na usumbufu wa muunganiko wa intaneti (71.8%). Utafiti ulihitimisha kwamba uwekezaji wa makusudi katika miundombinu ya TEHAMA,
mafunzo endelevu ya walimu, na sera madhubuti za taasisi ulikuwa muhimu ili kuvuna kikamilifu manufaa ya TEHAMA katika mazingira ya elimu ya juu nchini Uganda.

This study examined the effect of business partnerships and strategic alliances on the performance of Coca-Cola Beverages Uganda Limited. The objectives were to analyse how distribution partnerships influenced sales performance, to determine the effect of supplier alliances on operational efficiency, and to assess the impact of government-private sector partnerships on market expansion. A mixed-methods research design was employed, combining a structured survey of 95 employees, distributors, and alliance partners with in-depth interviews of 12 senior managers. Quantitative data were analysed using descriptive statistics and regression analysis, while qualitative data were subjected to thematic analysis. Findings revealed that distribution partnerships had a significant positive effect on sales performance (β = 0.456, p < 0.001), supplier alliances significantly enhanced operational efficiency (β = 0.371, p < 0.01), and government-private sector partnerships positively predicted market expansion outcomes (β = 0.318, p < 0.05). The study concluded that strategic partnerships and alliances were central to Coca-Cola Beverages Uganda Limited's competitive performance, enabling market penetration, supply chain optimization, and regulatory facilitation. Recommendations included formalizing partnership governance structures, investing in joint capacity building initiatives, and diversifying supplier alliance portfolios to reduce concentration risk.

Competency-Based Curriculum (CBC) has gained growing traction as a transformative framework for restructuring higher education systems across sub-Saharan Africa, yet its application within Ugandan undergraduate institutions remains fragmented and underexplored. This study examined the extent to which CBC principles were integrated into training, assessment, and curriculum delivery practices across selected Ugandan universities, and assessed the factors that predicted student academic outcomes under a CBC framework. A cross-sectional survey research design was employed, drawing on a stratified random sample of 385 respondents comprising 210 undergraduate students and 175 lecturers from eight universities, spanning public, private, technical, and faith-based institutions. Data were collected using validated Likert-scale questionnaires and analysed through a three-tiered statistical approach: univariate analysis to characterise distributional patterns across all study variables; bivariate analysis—including Pearson correlations and one-way ANOVA—to examine associations and group differences; and two-level multilevel modelling to partition outcome variance between individual and institutional levels while controlling for confounding. Findings revealed moderate-to-low mean scores across CBC implementation dimensions, with Curriculum Delivery Quality (M = 3.29, SD = 0.72) and Instructor Training (M = 2.98, SD = 0.93) emerging as areas of particular concern. Correlation analysis established statistically significant and positive associations between CBC Awareness,
Assessment Alignment, and Student Academic Outcomes (r = .559, p < .001 and r = .612, p < .001, respectively).
One-way ANOVA indicated significant differences in CBC delivery across institution types (F(3, 381) = 11.47, p < .001, η² = .083) and programme categories (F(4, 380) = 9.76, p < .001, η² = .093). The multilevel model explained 54% of variance in student outcomes (Conditional R² = 0.54), with Instructor Training Score (β = 0.43, p < .001) and Institutional Support Index (β = 0.27, p = .015) identified as significant institutional-level predictors. These results underscore the urgency of structured CBC professional development for lecturers, standardised institutional policy frameworks, and sustained investment in pedagogical infrastructure to optimise the impact of CBC in Ugandan undergraduate education.

This study examined the relationship between discipline as a form of self-control and STEM academic performance among secondary school students in Uganda, with specific reference to the national STEM Education Policy. Grounded in self-determination theory and Vygotsky's socio-cultural framework, the study sought to determine how student self-control, discipline, and school-level policy exposure collectively influenced STEM outcomes across different school types and geographic settings. A cross-sectional, mixed-methods design was employed, drawing on a stratified random sample of 1,200 students from 60 secondary schools across Uganda's four regions. Quantitative data were collected using structured questionnaires measuring self-control, discipline, and STEM performance, while qualitative insights were gathered through focus group discussions and key informant interviews. Descriptive statistics, Pearson bivariate correlations, ordinary least squares regression, and three-level hierarchical linear modelling (HLM) were applied to analyse the data. Findings revealed that self-control (β = 0.241, p < 0.001) and discipline scores (β = 0.187, p < 0.001) were strong and statistically significant predictors of STEM performance even after controlling for school-level and regional factors. The intra-class correlation in the null model was 0.234, confirming that 23.4% of the variance in STEM scores was attributable to school-level differences, which reduced to 16.7% in the full model after accounting for policy exposure, school type, and urbanisation. Private urban schools consistently outperformed government rural schools, pointing to structural inequalities that undermine the equitable aims of Uganda's STEM policy. Policy exposure was itself a positive predictor of proficiency (β = 0.323, p < 0.001),
suggesting that sustained and quality implementation of the STEM policy has measurable academic dividends. The study concluded that discipline and self-control are not merely moral virtues but are academically consequential competencies whose cultivation should be embedded in Uganda's STEM policy framework. Recommendations include targeted teacher-training on discipline-integrated pedagogy, resource equalisation across rural and urban schools, and a formal monitoring framework for STEM policy implementation.

This study investigated the relationship between e-governance and public service delivery at Uganda Revenue Authority (URA). Using a descriptive and correlational research design, data were collected from 172 respondents including taxpayers, URA staff, and corporate clients. E-governance was operationalized through three dimensions: e-service accessibility, digital transparency, and online tax compliance systems. Service delivery was measured by service efficiency, accuracy, and user satisfaction. Descriptive statistics, Pearson correlation, and multiple regression analyses were employed. Results indicated that e-governance positively and significantly predicts service delivery (β = 0.587, R² = 0.481, F = 44.31, p < 0.001). Online tax compliance systems were the strongest predictor (β = 0.341, p < 0.001). The study recommends scaling up digital infrastructure and digital literacy programs to maximize the service delivery benefits of e-governance at URA.

This study examined the paradox of educated but unemployed graduates in Uganda, conceptualised through the theoretical lens of functional illiteracy — a condition in which individuals possess formal academic credentials yet lack the applied wisdom, soft skills, emotional intelligence, and adaptive competencies required to translate learning into productive and sustainable employment. Using a cross-sectional survey design, primary data were collected from 420 respondents drawn from graduate job-seekers, employers, and university lecturers across four urban centres in Uganda — Kampala, Gulu, Mbarara, and Mbale. Structured questionnaires and semi-structured interview guides were used as primary data collection instruments. Data were analysed at three analytical levels: univariate analysis provided frequency distributions and descriptive statistics of the study variables; bivariate analysis, employing Pearson's chisquare tests and Spearman's rank-order correlation, examined pairwise associations between graduate wisdom deficits, employer-rated employability, and graduate labour-market outcomes; and Structural Equation Modelling (SEM) with maximum likelihood estimation was applied to test a hypothesised conceptual model in which the wisdom gap mediated the relationship between educational attainment and graduate employability. Findings revealed that 68.3% of unemployed graduates were assessed as functionally illiterate despite holding bachelor's degrees or higher, and that the wisdom gap — indexed by deficits in critical thinking, emotional regulation, professional ethics, and contextual problem-solving — accounted for approximately 54% of the variance in employer-rated employability (R² = 0.54, p < 0.001). Structural Equation Modelling confirmed that the wisdom gap fully mediated the attainment-employability pathway (indirect effect = 0.61, 95% CI [0.48, 0.74]), rendering the direct effect of educational attainment on employability non-significant (β = 0.07, p = 0.41) once the mediator was modelled. These results indicate that Uganda's higher education sector produces graduates who are academically credentialed but vocationally unready, largely because curricula continue to prioritise content transmission over wisdom development. The study recommends the systematic integration of applied wisdom pedagogy into university curricula, structural reforms in graduate assessment frameworks, and establishment of employer-academia partnerships to co-design competencybased learning outcomes aligned with the realities of Uganda's labour market.

Uganda's education system stands at a historic crossroads. On one side lies a trajectory of declining learning outcomes,
resource-strained institutions, and a curriculum misaligned with the demands of a digitally-driven economy. On the other lies an unprecedented opportunity: the responsible, strategic adoption of artificial intelligence (AI) as a tool for educational transformation. This article argues that AI's transformative potential in Ugandan education cannot be realized without a parallel commitment to discipline both as pedagogical philosophy and as institutional practice. Drawing on a structural model of AI-mediated educational outcomes, regression analysis of secondary school performance data, and case evidence from pilot AI deployments in East Africa, the article advances a strategy for leveraging AI to deepen learning, expand access, and accelerate Uganda's human capital development without surrendering the moral and intellectual formation that education fundamentally requires.