Artificial intelligence: An empirical survey of student and staff perspectives

Abstract

There has been a recent upsurge in debates about the role and potential of artificial intelligence (AI) in transforming traditional learning environments globally, and more recently, these discussions have expanded to include developing countries. While proponents of AI praise it as a new normal that educators must embrace or risk falling behind, sceptics caution that AI poses significant risks to academic endeavours, often citing ethical dilemmas and widely reported misuse of these technologies. This study employed an explanatory sequential mixed methods design to explore student and staff perspectives on AI in teaching and learning. Data were collected from 375 students and 187 staff via a quantitative questionnaire, as well as from 30 students and 18 staff through follow-up semi-structured interviews. The findings revealed that although students and staff largely agreed on AI's potential to transform university teaching, learning, and research, there were significant differences regarding feedback enhancement, personalisation of learning, critical thinking, and the efficiency and accuracy of data analysis in research. The study recommends that stakeholders engage in ongoing dialogue, research, and professional development to navigate the opportunities and challenges presented by AI in education.