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Cited by 11Artificial Intelligence in EducationAcademic integrity and plagiarismDigital Education and Society

Time, emotions and moral judgements: how university students position GenAI within their study

Open access
Bearman, Margaret, Fawns, T., Corbin, T., Henderson, M., Liang, Y., Oberg, G., Walton, J., Matthews, K. E.·2026·Higher Education Research & Development
DOI 10.1080/07294360.2025.2580616
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Abstract

The emergence of Generative AI (GenAI) in higher education has prompted considerable discussion within the research community. Despite their centrality, students’ perspectives remain underexplored. We investigated how students position GenAI in relation to their studies, conducting focus groups with 79 students across four Australian universities. Taking a sociotechnical stance and employing reflexive thematic analysis, we identified three primary themes: (1) studying with and without GenAI; (2) mixing messages and assumptions; and (3) ‘coming from me’: self-trust and resistance to dependency. Crossing these themes were axial threads of time, emotions, and moral judgement. Our findings illuminate a complex, dynamic and uncertain landscape of relationships in which students prioritise their developing values and moral positions over institutional messaging. Amongst diverse and changing practices, students generally conveyed a sense that their educational work should come from, and be owned by, themselves. This concept of ownership could productively inform academic integrity discussions. Institutions may need to move beyond rules and restrictions, to foster environments where students can develop nuanced relationships with GenAI whilst maintaining academic autonomy. This research demonstrates the value of centring student voices in shaping scholarly practice and policy, particularly in contexts of significant technological change.

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Crossref · 10.1080/07294360.2025.2580616

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24 of 24 references verified0 citation errors · 0 not checkable

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  • In the study location, several students talked about becoming dependent on genAI, suggesting usage diminished their sense of agency.

    “Unlike in Bearman et al.'s case, where most students”

    From Toward Partnership Ethics for Generative Artificial Intelligence in Higher Education (2026) · cites this paper as Bearman et al., 2025

    In ‘Coming from me’—trusting self and resisting dependency (p. 11), students discuss the risk of becoming dependent on GenAI. The Discussion (p. 12) says some feared a potential loss of agency over time, but it does not establish that using GenAI had already diminished their sense of agency; it says most positioned themselves as possessing agency. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • Focus group interviews have been shown to elicit reflection and discussion about genAI (non)use in relation to educational lifeworlds.

    “Focus group interviews have been shown to elicit reflection and discussion about on genAI (non)use in relation to educational lifeworlds (e.g., Bearman et al., 2025).”

    From Toward Partnership Ethics for Generative Artificial Intelligence in Higher Education (2026) · cites this paper as Bearman 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 Bearman et al., 2025

  • Participants frequently spoke about genAI in relation to moral character.

    “Significantly, our participants frequently spoke about genAI in relation to moral character, a result that resembles the”

    From Toward Partnership Ethics for Generative Artificial Intelligence in Higher Education (2026) · cites this paper as Bearman et al., 2025

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Research works printed but not linked: 4

  1. Braun, V., & Clarke, V. (2021). Thematic analysis: A practical guide . Sage. https://uk.sagepub.com/ en-gb/eur/thematic-analysis/book248481.
  2. Charmaz, K. (2014). Constructing grounded theory (2nd ed.) . Sage. https://au.sagepub.com/en-gb/ oce/constructing-grounded-theory/book235960.
  3. Creswell, J. (2012). Educational research: planning, conducting and evaluating quantitative and qualitative research (4th ed.). Pearson.
  4. Lebovitz, S. (2019). Diagnostic doubt and artificial intelligence: An inductive field study of radi­ ology work. Proceedings of the International Conference on Information Systems, Munich, Germany, 1-17. https://aisel.aisnet.org/icis2019/future\_of\_work/future\_work/11.

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Authors
Bearman, M., Fawns, T., Corbin, T., Henderson, M., Liang, Y., Oberg, G., Walton, J., & Matthews, K. E.
Affiliations
  • Deakin University (AU)
  • Monash University (AU)
  • The University of Queensland (AU)
Corresponding author
Bearman, Margaret
ORCID
Venue
Higher Education Research & Development
Publisher
Informa UK Limited
Published
2025-11-11
Volume
45
Issue
4
Pages
884-898
ISSN
  • 0729-4360 (ISSN-L)
  • 1469-8366
DOI
10.1080/07294360.2025.2580616
OpenAlex
W4416126746
Cited by
10
References
23
Citations by year
2026: 9 · 2025: 1
FWCI
10.48
Type
journal article
Language
en
Open access
Licence
Locations
  • Higher Education Research & Development (publishedVersion, cc-by-nc-nd)
  • Monash University Research Portal (Monash University) (submittedVersion, cc-by-nc-nd)
  • Figshare (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Social Sciences › Safety Research › Academic integrity and plagiarism
  • Physical Sciences › Computer Science › Information Systems › Digital Education and Society
Keywords
generative AI, student perceptions, higher education, academic integrity, moral judgment, emotions, time, student ownership of learning, AI dependency, academic autonomy, student resistance, student voice

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