Artificial Intelligence and student learning in higher education: Opportunities, challenges, and future directions

Abstract

There is growing interest in how Artificial Intelligence (AI) is impacting on teaching and learning in higher education, presenting new opportunities and possibilities for personalized learning, academic support, feedback and engagement. Its increased adoption, however, has sparked debate on academic honesty, techno-dependency, privacy and security of data, access disparities and the evolving role of teachers and students. This qualitative study explored participants’ perceptions and experiences of the use of AI in student learning within higher education. The data collecting method employed was semi-structured interview method among the participants of the higher education institutions. Thematic analysis was used to identify common themes linked to the educational advantages, obstacles, and prospects for the use of AI in learning. The results showed that AI tools can help to improve access to information, give instant feedback, enable personalized learning, increase understanding of challenging concepts and facilitate independent learning. The participants also raised worries about the lack of accurate or unbiased information, limited critical thinking, plagiarism, ethics, and low AI literacy, and overreliance on AI-generated text. The results further underscored the importance of institutional policies, teacher guidance, student training, ethical frameworks, and equitable access to AI technologies. However, the study concludes that AI shows great promise in enhancing student learning in higher education, provided that it is utilized responsibly as an educational aid, not a replacement for human reasoning, engagement with teachers, and active student participation. The study has implications for universities, teachers, and policymakers interested in pedagogically utilizing AI in higher education ethically, inclusively, and meaningfully.