The Impact of AI-powered Adaptive Learning Systems on Student Performance in Higher Education

Abstract

This research evaluated the effects of AI-integrated adaptive learning technologies on learner outcomes in higher education in Pakistan. A quantitative approach was used. Data was collected from a sample of 300 undergraduate students from 5 public sector universities. The universities were located in Lahore, Karachi, Islamabad, Peshawar, and Quetta. Each participant was assigned to either an experimental or a control group. Over the course of one academic semester, the experimental group utilized AI-integrated adaptive learning systems, while the control group was taught using traditional methods. Academic performance and engagement were evaluated via pre-tests, post-tests, and structured questionnaires. The results were analyzed via independent samples t-tests and ANOVA. The findings demonstrated that the experimental group, which used AI-integrated adaptive learning systems, achieved significantly higher academic performance and engagement compared to the control group. Furthermore, the AI adaptive learning system was able to adjust to the learner’s individual content, pace, and underlying knowledge gaps. This research, therefore, provides clear evidence supporting the effectiveness of AI-integrated adaptive learning technologies in improving student performance in higher education in Pakistan, and it is targeted at informing policymakers and educational institutions about evidence-based adaptive learning technologies. The study also provides valuable insights for integrating educational technology in developing countries.