To Use or Not to Use: Investigating Student Perceptions of Faculty Generative AI Usage in Higher Education
- URL: http://arxiv.org/abs/2603.25932v1
- Date: Thu, 26 Mar 2026 21:54:57 GMT
- Title: To Use or Not to Use: Investigating Student Perceptions of Faculty Generative AI Usage in Higher Education
- Abstract summary: Students expressed concerns about GenAI use by faculty in teaching and grading contexts.<n>Findings informed the future use of GenAI in teaching and learning in higher education.
- Score: 15.041760305727053
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: While Generative AI (GenAI) rapidly integrated into higher education, existing research has primarily focused on regulating student use. As a result, student perspectives on faculty adoption of GenAI remained unexplored. In this study, we analyzed survey responses from 156 undergraduate and graduate students to examine their attitudes toward both student and faculty use of GenAI. We classified students into four groups based on their attitudes, including GenAI Optimists, Student Support Group, Faculty Support Group, and Non-supporters. Findings show that 37% of participants do not support GenAI use by either students or faculty, while 31% support GenAI use in both contexts. We also conducted thematic analysis to understand participants' concerns on faculty GenAI usage. Results revealed that (1) a majority of students (79%) questioned the validity and reliability of GenAI-generated responses, and (2) 37% of students feared that faculty overreliance on GenAI created a "futile cycle" that might reduce faculty critical thinking. Our findings showed that students expressed concerns about GenAI use by faculty in teaching and grading contexts, with pedagogical concerns being most prominent. These findings informed the future use of GenAI in teaching and learning in higher education.
Related papers
- Quick Build, Careful Check? Generative AI Use in Hackathons [83.0493885475068]
We report an exploratory interview study with participants at an AI-themed hackathon in central Europe.<n>We found that participants used GenAI for purposes beyond coding, including learning unfamiliar topics, brainstorming, and preparing documentation.<n>We also found that all participants converged on an unwritten practice of checking GenAI output before using it, yet their ability to actually verify was constrained by time pressure and limited domain knowledge.
arXiv Detail & Related papers (2026-07-31T08:59:18Z) - Is Solving Better Than Evaluating GenAI Solutions? [45.714140455691485]
This study compares evaluating GenAI-generated solutions with traditional problem solving in a junior-level algorithms course.<n>We found no statistically significant differences between groups in midterm scores, final exam scores, overall course grades, or exam problems structurally aligned with the homework interventions.<n>Students received significantly higher homework scores when evaluating GenAI-generated solutions, but this localized advantage did not translate into downstream gains.
arXiv Detail & Related papers (2026-07-30T02:08:29Z) - Generative AI Usage of University Students: Navigating Between Education and Business [0.0]
This study investigates generative artificial intelligence (GenAI) usage of university students who study alongside their professional career.<n>The study highlights both the potential and challenges of GenAI usage in education and business.<n>While GenAI can significantly enhance productivity and learning outcomes, concerns about ethical implications, reliability, and the risk of academic misconduct persist.
arXiv Detail & Related papers (2026-02-18T09:37:56Z) - Generative AI Practices, Literacy, and Divides: An Empirical Analysis in the Italian Context [32.495879271249414]
This study presents the first comprehensive empirical mapping of GenAI adoption, usage patterns, and literacy in Italy.<n>Our findings reveal widespread adoption for both work and personal use, including sensitive tasks like emotional support and medical advice.<n>We identify a significant gender divide where women are half as likely to adopt GenAI and use it less frequently than men.
arXiv Detail & Related papers (2025-12-03T11:01:28Z) - Reduced AI Acceptance After the Generative AI Boom: Evidence From a Two-Wave Survey Study [40.26767449635043]
We examine shifts in public attitudes toward AI before and after the launch of ChatGPT.<n>The proportion of respondents finding AI "not acceptable at all" increased from 23% to 30%.<n>These shifts have amplified existing social inequalities in terms of widened educational, linguistic, and gender gaps post-boom.
arXiv Detail & Related papers (2025-10-27T17:47:58Z) - Understanding Student Attitudes and Acceptability of GenAI Tools in Higher Ed: Scale Development and Evaluation [22.35484281040714]
This study introduces a validated survey instrument designed to assess students' perceptions of generative AI (GenAI)<n>The instrument includes six thematic domains: institutional understanding, fairness and trust, academic and career influence, societal concerns, and GenAI use in writing and coursework.<n>Students from multilingual households perceived greater clarity in institutional policy, while first-generation students reported a stronger belief in GenAI's impact on future careers.
arXiv Detail & Related papers (2025-08-03T21:22:34Z) - From Recall to Reasoning: Automated Question Generation for Deeper Math Learning through Large Language Models [44.99833362998488]
We investigated the first steps for optimizing content creation for advanced math.<n>We looked at the ability of GenAI to produce high-quality practice problems that are relevant to the course content.
arXiv Detail & Related papers (2025-05-17T08:30:10Z) - The GenAI Generation: Student Views of Awareness, Preparedness, and Concern [1.5709900716890133]
Outpacing the development of uniform policies and structures, GenAI has heralded a unique era and given rise to the GenAI Generation.<n>This study examines students' perceptions of GenAI through a concise survey with optional open-ended questions.<n>Students with greater curricular exposure to GenAI tend to feel more prepared, while those without it more often express vulnerability and uncertainty.
arXiv Detail & Related papers (2025-05-04T19:37:13Z) - Engineering Educators' Perspectives on the Impact of Generative AI in Higher Education [4.06279597585806]
This study reports findings from a survey of engineering educators on their use of and perspectives toward generative AI.<n>We asked them about their use of and comfort with GenAI, their overall perspectives on GenAI, the challenges and potential harms of using it for teaching, learning, and research, and examined whether their approach to using and integrating GenAI in their classroom influenced their experiences with GenAI and perceptions of it.
arXiv Detail & Related papers (2025-02-01T21:29:53Z) - Early Adoption of Generative Artificial Intelligence in Computing Education: Emergent Student Use Cases and Perspectives in 2023 [38.83649319653387]
There is limited prior research on computing students' use and perceptions of GenAI.
We surveyed all computer science majors in a small engineering-focused R1 university.
We discuss the impact of our findings on the emerging conversation around GenAI and education.
arXiv Detail & Related papers (2024-11-17T20:17:47Z) - Misconceptions, Pragmatism, and Value Tensions: Evaluating Students' Understanding and Perception of Generative AI for Education [0.11704154007740832]
Students are early adopters of the technology, utilizing it in atypical ways.
Students were asked to describe 1) their understanding of GenAI; 2) their use of GenAI; 3) their opinions on the benefits, downsides, and ethical issues pertaining to its use in education.
arXiv Detail & Related papers (2024-10-29T17:41:06Z) - Hey GPT, Can You be More Racist? Analysis from Crowdsourced Attempts to Elicit Biased Content from Generative AI [41.96102438774773]
This work presents the findings from a university-level competition, which challenged participants to design prompts for eliciting biased outputs from GenAI tools.
We quantitatively and qualitatively analyze the competition submissions and identify a diverse set of biases in GenAI and strategies employed by participants to induce bias in GenAI.
arXiv Detail & Related papers (2024-10-20T18:44:45Z) - Understanding Student and Academic Staff Perceptions of AI Use in Assessment and Feedback [0.0]
The rise of Artificial Intelligence (AI) and Generative Artificial Intelligence (GenAI) in higher education necessitates assessment reform.
This study addresses a critical gap by exploring student and academic staff experiences with AI and GenAI tools.
An online survey collected data from 35 academic staff and 282 students across two universities in Vietnam and one in Singapore.
arXiv Detail & Related papers (2024-06-22T10:25:01Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.