Relational dynamics at the intersection of technology and higher education: perspectives on GenAI use among humanities master’s students
Abstract
The rapid uptake of generative AI (GenAI) tools in academic contexts has prompted a wave of responses regarding pedagogical reconfiguration, assessment, shifting academic norms, values, and practices. While scholarly discourse increasingly examines the benefits, limitations, and ethical implications of GenAI in higher education, students’ perspectives remain underrepresented and often limited to survey-based research focused on academic integrity and plagiarism. To gain a deeper understanding of the multifaceted role GenAI plays in students’ academic lives, this study draws on 14 semi-structured interviews with Humanities (Research) Master’s students at a major Dutch university and is guided by the following research question: How do students navigate their use of GenAI tools in academic contexts? The findings reveal critical self-reflections on skills development, learning trajectories, and the institution’s role in shaping their perspectives, decision-making, and lived experiences. We find that students do not accept GenAI’s role in education as a fait accompli, but instead actively engage in boundary-making practices and legitimization strategies in context-dependent, reflective, and relational ways. These insights serve as a critical counterpoint to dominant techno-solutionist and technologically deterministic discourses, drawing attention to the need for ethical guidelines grounded in the relational dynamics at the intersection of technology and higher education.
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Studies show that teachers believe students are more instrumental about learning than students perceive themselves to be.
“Generally, studies show that teachers believe students are more instrumental about learning than students perceive themselves to be (Sagy et al., 2019; see also Encheva et al., 2025;).”
From Toward Partnership Ethics for Generative Artificial Intelligence in Higher Education (2026) · cites this paper as Encheva et al., 2025
Many participants were unclear about when genAI usage moved from assistance to unethical behaviour.
“As Duah & McGovern described in their UK study (2024), Bearman et al. in their Australian one (2025), and Encheva et al. in their Dutch one (2025), many were unclear about when genAI usage moved from assistance to unethical behaviour.”
From Toward Partnership Ethics for Generative Artificial Intelligence in Higher Education (2026) · cites this paper as Encheva et al., 2025
Research participants wanted the university to offer more guidance.
“Research participants wanted the university to offer more guidance, a pattern also found in other studies (e.g., Encheva et al., 2025;Isiaku et al, 2024;Johnston et al., 2024;Nguyen, 2025;Xia et al., 2024).”
From Toward Partnership Ethics for Generative Artificial Intelligence in Higher Education (2026) · cites this paper as Encheva et al., 2025
Students and teachers worried about genAI leading to the loss of critical thinking skills, creativity, and autonomy.
“Students and teachers worried about genAI leading to the loss of critical thinking skills, creativity, and autonomy, all findings that resonate with previous research (Chan & Hu, 2023;Encheva et al., 2025;Isiaku et al., 2024;Newell et al., 2024;Olsson, 2026;Rahman et al., 2025;Xia et al., 2024).”
From Toward Partnership Ethics for Generative Artificial Intelligence in Higher Education (2026) · cites this paper as Encheva et al., 2025
Many participants believed genAI use is inevitable.
“As in a Dutch case study (Encheva et al., 2025), many believed genAI use is inevitable -even though scholars have suggested refusing or banning genAI for ethical reasons (Carrigan, 2024;de Fine Licht, 2024).”
From Toward Partnership Ethics for Generative Artificial Intelligence in Higher Education (2026) · cites this paper as Encheva et al., 2025
Contrary to teachers' perceptions documented in existing literature, the students participating in the study were strongly committed to learning as an intrinsic good.
“Contrary to teachers' perceptions documented in existing literature, the students participating in our study were strongly committed to learning as an intrinsic good (cf.Encheva et al., 2025).”
From Toward Partnership Ethics for Generative Artificial Intelligence in Higher Education (2026) · cites this paper as Encheva et al., 2025
Students felt uncertain and even fearful of wrongdoing.
“Students, many of whom already suffered from stress and anxiety, felt uncertain and even fearful of wrongdoing -a finding echoing a”
From Toward Partnership Ethics for Generative Artificial Intelligence in Higher Education (2026) · cites this paper as Encheva et al., 2025
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Toward Partnership Ethics for Generative Artificial Intelligence in Higher Education
Gillette, M., Wackenhut, A., & Olsson, E. (2026) · Journal of University Teaching and Learning Practice · doi:10.53761/yf2gt848
“As in a Dutch case study (Encheva et al., 2025), many believed genAI use is inevitable – even though scholars have suggested refusing or banning genAI for ethical reasons (Carrigan, 2024; de Fine Licht, 2024).”
InfluentialAI ethics after generative AI: from consequences to effects
Gianni, R. (2026) · AI & Society · doi:10.1007/s00146-026-03308-y
- Authors
- Encheva, A., van Es, K., & Nguyen, D.
- Affiliations
- Utrecht University (NL)
- Utrecht University, Utrecht
- Corresponding author
- Encheva, Ani
- Venue
- Learning, Media and Technology
- Publisher
- Informa UK Limited
- Published
- 2025-11-18
- Pages
- 1-16
- ISSN
- 1743-9884 (ISSN-L)
- 1743-9892
- OpenAlex
- W4416336618
- Cited by
- 1
- References
- 25
- Citations by year
- 2026: 1
- FWCI
- 1.05
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Learning Media and Technology (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Information Systems › Digital Education and Society
- Social Sciences › Safety Research › Academic integrity and plagiarism
- Keywords
- generative AI, student perceptions, legitimation strategies, relational dynamics, academic integrity, AI ethics guidelines, student agency, learning trajectories, skill development
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