Student perspectives on optimising AI tools to enhance personalised learning in higher education

This explanatory qualitative paper discusses students' recommendations on how AI tools can be optimised to enhance personalised learning in higher education. The effective adoption and implementation of AI technologies face several challenges, particularly in user acceptance and the balance between AI-assisted and traditional learning methods. The paper adopts the Technology Acceptance Model as a theoretical framework for understanding users' technology acceptance and usage. It posits that perceived usefulness and perceived ease of use are primary factors influencing users' technology adoption, which can guide the development of strategies to improve the implementation and effectiveness of AI technologies in personalised learning. The method used is a qualitative explanatory case study where open-ended questionnaires were administered to 40 students from various faculties at the University of the Free State. The findings reveal that students and lecturers need to be trained in using AI tools and that there should be a balance between using AI tools and traditional teaching methods to enhance personalised learning in higher education. Considering the findings, the study suggests that institutions and lecturers need to address the challenges posed by AI tools immediately, and leverage AI to its full potential in creating an effective and personalised learning environment.