Use of artificial intelligence tools by doctoral students: a mixed-methods explanatory-sequential investigation
Muhammad Naveed Akbar
Abstract
Increasing use of AI tools in higher education comes with a need to develop a clear understanding of how students (by demography and study discipline) employ them, for what purposes and in what terms their use is evaluated. This will inform the development of future guidelines and training for staff and students. In the current mixed-methods study, a cross-sectional survey was first administered to a convenience sample of 105 doctoral students (71 females, 34 males), followed by semi-structured interviews with a subset of seven participants (four females, three males). This had several aims; to identify patterns of AI tool use and its perceived helpfulness; to explore AI use with regard to aspects of time management, stress and study progress; to construct a predictive model of AI tool use and to explore, in-depth, students’ views on beneficial and problematic aspects of AI. Findings suggested AI was widely used. Males were more likely to use it for data analysis and research planning, with greater use by students in non-scientific disciplines. Use was significantly related to stress and time management. Several potential benefits and problems were identified. Benefits included aiding research, for example, assisting and improving coding/programming, use in proofreading and writing and as an explanatory tool for rendering complex information accessible. Potential problems included environmental cost, violation of intellectual property rights, provision of misleading and/or inaccurate information and risks of plagiarism and hindered creativity. Limitations of the study are discussed alongside implications for policy and training with suggestions for further work.