Artificial intelligence integration and learner achievement in competence-based education in higher education institutions in Uganda

Abstract

The rapid emergence of Artificial Intelligence (AI), is reshaping higher education through real-time tutoring, personalised learning, and advanced knowledge synthesis. In Uganda, the adoption of Competence-Based Education (CBE) emphasises learner-centered pedagogy, critical thinking, and practical skill development. While AI presents opportunities to strengthen CBE, its unstructured use may undermine independent inquiry, critical thinking, and authentic competency development. The study investigated how institutional readiness, stakeholder perceptions, and AI use patterns relate to learner achievement within a competence-based curriculum in an AI-powered environment. It further identified strategies for integrating AI to support competency attainment, academic performance, assessment outcomes, and learning outcomes while preserving the principles of CBE in Ugandan higher education institutions. A cross-sectional quantitative design was employed, involving academic staff (n = 52) and students (n = 513) from public and private universities in Uganda. Participants were recruited through convenience sampling using online platforms. Data were collected using structured questionnaires measuring institutional readiness, stakeholder perceptions, AI usage patterns, learner achievement, and pedagogical strategies for AI integration. Both descriptive and inferential statistics were analysed using the JASP statistical tool and Python-based data analysis tools. The findings revealed moderate institutional readiness for AI adoption, with technology recording the highest readiness (M = 3.2), followed by pedagogy (M = 2.9), while policy and governance readiness remained low (M = 2.4). Stakeholders perceived AI as supporting competency achievement (M = 4.1, 85%) and self-directed learning (M = 4.0, 80%), although concerns were raised regarding independent problem-solving (M = 3.6, 65%) and assessment authenticity (M = 3.8, 70%). Students reported frequent use of AI tools, particularly ChatGPT (81.1%), Gemini (56.8%), and Copilot (38.8%), primarily for concept clarification (89.2%), research (81.1%), and idea generation (70.3%). Correlation analysis revealed a moderate positive relationship between AI use frequency and academic performance (r = 0.544), while chi-square analysis confirmed a significant association between AI use and academic performance (χ2 = 241.898, p < 0.001). The study concludes that effective AI integration in CBE requires AI literacy training, lecturer capacity building, institutional policy frameworks, and competency-oriented assessment approaches to enhance learner achievement while preserving the integrity of competency development.