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Raising Ethical Awareness of GenAI Use Through Student Self-Assessment in the Transition to Higher Education

◐ medium · 2026-08-20 · generative-ai, ethics, self-assessment, assessment, academic-integrity, agency, higher-ed

Synthesis: Pedlow and Maldon (2026) investigate how guided reflection embedded within self-assessment can support students to engage responsibly and confidently with generative AI (GenAI) in learning and Assessment, while maintaining academic integrity. Conducted at an Australian university (Edith Cowan) with commencing undergraduate and postgraduate students across nursing, health sciences, engineering and science (2021–2025), the study implemented pre- and post-semester self-assessments combining Likert-scale confidence items with an open-ended prompt inviting reflection on the ethical implications of GenAI use. Findings indicate that students recognised both the benefits and limitations of GenAI, demonstrating growing ethical awareness and critical evaluation of its role in academic work. Reflections revealed persistent tensions between efficiency and academic integrity, uncertainty about institutional expectations, and a shift from risk aversion and fear toward deliberate boundary-setting, disclosure, and critical vigilance. Students reported an increased sense of personal responsibility, describing the reflective process as confidence-building during their transition to higher education. The authors frame ethical GenAI use not as compliance but as a developmental capability, positioning guided reflection within self-assessment as a scalable, student-centred pedagogical strategy that fosters readiness, self-regulated learning, and learner agency.

Key Findings

  • Guided reflection raised ethical awareness: students moved from pre-intervention risk aversion and fear (e.g. "I have never used GenAI as I'm too scared of breaching academic integrity") toward more defined strategies for ethical engagement around disclosure, accountability, and critical vigilance over outputs.
  • Confidence in academic integrity increased most strongly across all domains (largest gains in referencing and paraphrasing), while confidence in using GenAI for learning and Assessment showed more modest gains — gains were largest among students with the lowest initial confidence.
  • Undergraduates vs. postgraduates diverged: undergraduates showed the strongest gains in academic integrity skills but decreased confidence in using GenAI for learning/assessment (a realignment of understanding toward its limits and complexities), whereas postgraduates improved consistently from a lower baseline in assessment-related GenAI use.
  • Tensions between efficiency and integrity persisted: reflections surfaced ongoing concerns about referencing, acknowledgement, fairness, reliability, hallucinations, and intellectual property — procedural and ethical complexity that a reflective intervention alone did not resolve.
  • Reflection fostered learner agency and personal responsibility: students described the reflective process as confidence-building during their transition to university, linking ethical use to professional identity and resisting over-reliance on GenAI.
  • Self-assessment reframes ethical inquiry as pedagogy: embedding GenAI-focused reflection within self-assessment shifts the focus from compliance and detection toward critical, self-regulated engagement, offering a scalable model adaptable across disciplines and year levels.

Study Design & Method

The study used a pre-test/post-test quasi-experimental design (Rogers & Revesz, 2019) underpinned by a descriptive qualitative methodology (Braun & Clarke, 2013). Participants were commencing undergraduate (n=491) and postgraduate (n=206) students at Edith Cowan University recruited via convenience sampling across nursing, health sciences, engineering and science. The intervention was an self-assessment survey, co-designed with students and staff, originally developed in 2021 for academic and digital literacy and expanded with GenAI-specific questions in 2023. It addressed four domains: (1) confidence in academic integrity practices, (2) confidence using GenAI for Assessment preparation, (3) confidence using GenAI for learning, and (4) an open-ended ethical reflection ("Have you considered the ethical implications of using GenAI? If yes, how?"). Quantitative items used a four-point confidence scale and were analysed descriptively with paired-samples t-tests on matched responses (n=25); open-ended responses were analysed using Braun & Clarke's six-phase inductive thematic analysis with peer debriefing for credibility. Pre-surveys (n=697) were administered in Orientation/Weeks 1–2; post-surveys (n=67) in Weeks 12–13. Instrument reliability was excellent (Cronbach's α = .94 pre, .93 post). The authors note high pre-test but variable post-test response rates as a limitation, particularly for the matched subsample.

Implications for AI in Education

This study contributes to scholarship on ethical GenAI use by demonstrating that a concise, scalable self-assessment model — confidence ratings plus a short reflective prompt — can normalise ethical inquiry as part of academic development rather than treating integrity as an externally imposed rule. It supports the shift from surveillance- and compliance-driven responses toward educative, student-centred models of academic integrity that foreground student voice and learner agency, aligning with calls to move beyond detection mechanisms in higher education. The findings reposition educators as facilitators who help students critically and responsibly engage with emerging technologies, and highlight the need for explicit teaching of procedural conventions (referencing, acknowledgement, record-keeping) alongside ethical reflection. For AI-enabled learning, the study reinforces the value of metacognitive awareness and self-regulated learning in GenAI-mediated environments, and points to AI literacy and authentic assessment design as complementary priorities. The CC BY-ND (no derivatives) licence of the paper should be noted when adapting its materials.

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Citation

Pedlow, M., & Maldon, J. (2026). Raising Ethical Awareness of GenAI Use Through Student Self-Assessment in the Transition to Higher Education. Journal of University Teaching and Learning Practice, 23(5). https://doi.org/10.53761/39ey1895. CC BY-ND 4.0.