Exploring Lecturers' Experiences with Artificial Intelligence Integration in Lecturing: A Case Study of a Private Higher Education Institution in Rwanda

Abstract

This study explored how lecturers at a private higher education institution in Rwanda experience, interpret, and navigate the integration of artificial intelligence (AI) into their lecturing practices. While prior research within similar institutional settings has quantitatively examined AI’s effect on student performance, engagement, and satisfaction, the lived experiences, challenges, and support needs of lecturers themselves have remained largely unexamined. Adopting a case study design, data were generated through in-depth, semi-structured interviews with four lecturers who were purposively selected and sampled until data saturation was reached. Data were analyzed thematically. Findings, organized around three objectives, revealed that lecturers perceive AI as valuable for personalizing feedback, saving preparation time, and enhancing student engagement, although their experiences were mixed and largely shaped by trial-and-error learning rather than formal guidance. Lecturers also identified infrastructural, competency-related, and institutional barriers, including unreliable internet connectivity, inadequate training, and the absence of a clear institutional policy, that constrained meaningful integration. Finally, participants emphasized the need for continuous professional development, peer mentoring, dedicated technical support, and formal institutional policy to sustain AI adoption. These findings extend the growing quantitative literature on AI in Rwandan higher education by foregrounding lecturers' voices and situated realities, thereby offering nuanced, contextualized insight that outcome-based numeric data alone cannot provide. The study recommends deliberate, adequately resourced, and pedagogically grounded institutional strategies for integrating AI into lecturing in private higher education institutions