Assessing the Extent of Integration of Artificial Intelligence in Teaching and Learning at Kenyan Universities - Callen Nyamwange (Pan-African Journal of Education and Social Sciences)
Artificial Intelligence (AI) in university teaching is reshaping higher education by enhancing instructional methods, student engagement, and learning outcomes. This study explores the use of AI-driven tools, personalized learning, and adaptive instructional strategies. It establishes the motivation and satisfaction levels in adopting AI over traditional methods in university teaching experience. The study used the Technological Pedagogical Content Knowledge (TPACK) theory (Mishra & Koehler, 2006) and Diffusion of Innovation (DOI) theory (Rogers, 2003) to underscore the role of technology in fostering continuous learning and interaction. Data were collected from students across diverse programs through the Learning Management Systems (LMS) and analyzed using AI-powered learning analytics and natural language processing (NLP) tools. Key metrics included course completion rates, assignment engagement, and assessment performance. The findings reveal that AI facilitates content personalization and real-time feedback and improves student participation, ultimately optimizing the learning experience. This study provides valuable insights into student interactions, preferences, and effectiveness of AI in higher education. It also highlights the need for universities to strategically utilize AI to foster inclusive, adaptive, and efficient teaching environments. The research recommends embracing AI as a transformative tool to maximize its potential in shaping the future of university education in Kenya.