The Impact of Artificial Intelligence on Adaptive Learning: A Comparative Study of Traditional and AI-Based Pedagogies

Abstract

This research examines the impact of AI-based adaptive learning on conventional pedagogy, with a focus on the perceptions, challenges, and future potential of the technology, as viewed by educators. Taking a quantitative research approach, data were collected from 220 university lecturers via a self-administered questionnaire. Correlation analysis showed a moderate positive correlation between demographic factors and perceptions of AI in education (r = 0.351, p < 0.01), and a weaker but significant correlation between perceptions of AI-based learning and challenges/future potential of AI (r = 0.173, p < 0.05). Regression analysis showed that challenges of ethical nature significantly influenced perceptions of AI's future potential (B = 0.548, p = 0.024), but with very low explanatory power (R² = 0.023), which suggests that many factors drive the adoption of AI in learning environments. The results show that AI-based learning enhances learner engagement and personalized learning; however, ethical concerns, infrastructure, and the role of irreplaceable human interaction pose challenges that need to be addressed. The research concludes that AI needs to be positioned as an addition to, not a replacement of, conventional teaching approaches and calls for further research into hybrid AI-human pedagogy models.