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

Abstract

This explanatory qualitative paper discusses students’ recommendations on how AI tools can be optimised to enhance personalised learning in higher education. There are several obstacles to the successful adoption and application of AI technology, two of which are user acceptance and striking a balance between AI-assisted and conventional teaching techniques. The Technology Acceptance Model is used in this research as a theoretical framework to analyse how users accept and use technology. It makes the case that users’ acceptance of technology is mostly influenced by their perceptions of its usefulness and ease of use, which can direct the creation of strategies to enhance the application and efficacy of AI technologies in individualised learning. Open-ended questionnaires were given to 40 University of the Free State students from different faculties as part of a qualitative explanatory case study methodology. The findings reveal that both 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 by establishing clear ethical guidelines and policies for AI usage in higher education and implementing comprehensive AI literacy programs for lecturers and students to ensure they understand the capabilities, limitations, and ethical considerations of AI tools.

Keywords

• artificial intelligence
• personalised learning
• technology acceptance model
• perceived usefulness
• ease of use