Abstract
Gen AI is increasingly prevalent in higher education, presenting an opportunity for academics to optimize their workloads. However, Gen AI’s efficiency can enable the commodification of knowledge, and such commodification may enable students to question academics’ legitimacy. This qualitative study seeks to answer the following question: From a graduate student’s perspective, under what conditions and at which points in the assessment process, might an academic’s Gen AI use threaten or sustain academic legitimacy? Fourteen graduate students (i.e., master’s and doctoral) completed a reflexive writing exercise and interviews to answer the research question. Participants expressed that Gen AI should be a tool used by academics yet stressed that an academic’s greater reliance on Gen AI in the assessment process made participants devalue an academic’s expertise. While graduate students struggled to define appropriate Gen AI use for assessment, participants emphasized an academic’s Gen AI use for assessment needed to be made transparent and thoughtful. Finally, participants noted that academic–student relationships were crucial to student development and not an educational element Gen AI could replace. Gen AI’s use by academics needs to be carefully integrated into assessment to ensure its efficiency is not supplanting an academic’s legitimacy. An academic’s use of one’s expertise needs to remain at the forefront of the assessment process to develop a student’s expertise. Otherwise, an academic’s role in the educational process, and higher education institutions by extension, will be questioned if Gen AI’s efficiency supplants academics’ legitimacy.
Context and implications
Rationale for this study: Using Gen AI for assessment to spur efficiency affects students’ perceptions of academics’ legitimacy. This can lead to students devaluing academics and higher education.
Why the new findings matter: An inappropriate reliance on Gen AI by academics can threaten higher education’s legitimacy and value among stakeholders.
Implications for practitioners and policy-makers: This study is important for academics, graduate students and policy-makers. Academics and graduate students must adapt to a world where Gen AI proficiency is expected for efficiency, but this should not come at the expense of academic legitimacy and expertise. Academics must transparently communicate how and why Gen AI is part of the assessment process. Otherwise, if students are unable to distinguish academics’ critiques from Gen AI’s, and policy-makers do not provide educational quality assurances, the value of academics’ expertise will be diminished. This erosion of perceived expertise may not only threaten academics’ legitimacy but, ultimately, higher education’s.