Title: The Humble Educator and the Digital Native: Analyzing Uganda's Readiness for the AI-Driven Pedagogical Paradigm Shift
Authors: Dr. Arinaitwe Julius, Asiimwe Isaac Kazaara
Volume: 10
Issue: 1
Pages: 284-291
Publication Date: 2026/01/28
Abstract:
This mixed-methods study assessed Uganda's readiness for AI-driven pedagogical transformation by examining technological infrastructure, educator competencies, and policy frameworks across 105 educational institutions in four geographical regions between January and June 2025. Using stratified random sampling, the study recruited 420 educators, 315 students, 84 school administrators, and 45 policymakers, achieving 80% statistical power for detecting medium effect sizes. Quantitative data were collected through validated questionnaires and institutional audits, while qualitative insights emerged from 24 in-depth interviews, 12 focus group discussions, and policy document analysis. Data analysis employed descriptive statistics, independent samples t-tests, one-way ANOVA, multiple linear regression, chi-square tests, factor analysis, and structural equation modeling using SPSS 27.0, AMOS, and NVivo 14. Results revealed profound inadequacies across all readiness dimensions. Technological infrastructure assessment showed significant disparities (F=203.89, p<0.001, ?²=0.86), with rural public institutions exhibiting critically low AI-ready infrastructure indices (22.6%) compared to urban private schools (71.4%), characterized by insufficient computer-to-student ratios, severely limited internet connectivity (1.2 Mbps in rural areas), and unreliable electricity supply. Educator competency analysis demonstrated substantial urban-rural gaps across all domains (all p<0.001, Cohen's d=0.61-1.68), with overall AI awareness scores averaging only 34.7 out of 100 and self-reported readiness at 38.9%. Multiple regression analysis (R²=0.68, p<0.001) identified AI awareness (?=0.42) and pedagogical technology integration knowledge (?=0.38) as strongest predictors of educator readiness. Policy framework evaluation revealed critical governance deficits, with only 36.4% overall policy support adequacy and merely 23% of institutions accessing national AI education guidelines. Structural equation modeling demonstrated excellent fit (CFI=0.96, RMSEA=0.065) and revealed that policy support exerted powerful total effects on AI readiness (?=0.72, R²=0.72) through direct and mediated pathways via infrastructure (?=0.21) and educator competence (?=0.20). The study concluded that Uganda was substantially unprepared for AI-driven pedagogical transformation, with rural institutions serving 78% of students facing particularly acute challenges. Recommendations emphasized phased infrastructure development with equity-focused investment, comprehensive national educator AI literacy programs, and formulation of robust policy frameworks with governance safeguards. The findings suggested that successful AI integration required addressing foundational deficits through systematic, long-term interventions rather than premature technology deployment, with policy frameworks serving as critical enablers for coordinated, equitable transformation across Uganda's diverse educational landscape.