Generative AI · Education leadership

Actionable companion · Assessment and evidence of learning

From evidence to district action: Integrating Generative AI into public health education: a mixed methods evaluation of student experiences

AI-assisted editorial implementation guide. The district actions are proposed applications, not findings or recommendations attributed to the original authors. No additional peer review is asserted.

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Evidence and context

Confirm the study population, setting and task before applying its findings to your district.

Original authors’ abstract, reproduced under the linked source license:

Introduction As Generative Artificial Intelligence (GenAI) continues to influence pedagogical practices in higher education, prevailing discourse has largely focused on issues of assessment integrity, often overlooking student perspectives. Yet, understanding student voices is essential to ensure that AI-enhanced teaching and assessment remain student centred, equitable, and aligned with intended learning outcomes. This study aimed to explore postgraduate health science students’ perceptions and experiences of the structured integration of GenAI into teaching and assessment within the Epidemiology and Principles of Research unit at the University of Canberra. Methods A mixed-methods study was conducted using pre- and post-intervention surveys administered to all enrolled students, with 78 participants completing the evaluation. The intervention involved the scaffolded integration of GenAI into a critical appraisal assessment. Quantitative data were analysed using descriptive statistics and Fisher’s exact test to assess changes over time. Qualitative data from open-ended responses were analysed using thematic analysis following Braun and Clarke’s six-phase approach. Results Students reported statistically significant improvements in their understanding of GenAI and perceived ability to use it effectively (p < 0.001). Thematic analysis identified five key themes: tensions between automation and authentic learning; prompt literacy as a new academic skill; GenAI as a support for metacognitive engagement; ethical ambiguity and cognitive dissonance; and future-oriented learning. Conclusion The findings highlight the importance of thoughtful pedagogical designs that center student voice, support critical engagement, and prepare learners for responsible and reflective use in future professional practice.

A 90-day district pilot

  1. Days 1–15 · Appraise. Have the curriculum lead and a teacher read the methods and limitations. Record the study design, sample, comparator, outcomes and evidence gaps. Define a local question that the study can help inform.
  2. Days 16–30 · Design. Redesign one low-stakes assessment: require a first attempt, an AI-assisted revision, a source-check log and a short oral explanation. Use the same rubric for the comparison task. Name an accountable owner and set the baseline, success threshold and budget before implementation.
  3. Days 31–60 · Test. Start with a small voluntary cohort, preserve an accessible non-AI route and require teacher review. Use synthetic or de-identified examples; approve data handling and tool terms through district processes.
  4. Days 61–90 · Decide. Blind-score reasoning, factual accuracy and unaided transfer on a fresh task. Record suspected misconduct separately from demonstrated evidence. Compare with baseline, document uncertainty and stop or revise if learning worsens, access is unequal or critical errors persist.

The board decision brief

Report the learning problem, evidence quality, participating population, total cost including review time, measured benefit, errors, access differences and remaining uncertainties. Make a dated recommendation to stop, revise or expand. A positive perception survey alone does not establish learning improvement.

Attribution and reuse

Zelalem Mengesha; Jennifer Estellore; Jennifer Smith; Mathew Sunil George; Rosemary A. McFarlane; Jinal Parmar. Integrating Generative AI into public health education: a mixed methods evaluation of student experiences. Frontiers in Public Health (2026-07-15). https://doi.org/10.3389/fpubh.2026.1825937

Companion prepared 2026-10-30. Original authorship and DOI are preserved. The abstract is an attributed source extract; the implementation plan is new AI-assisted editorial material, offered under the same CC BY 4.0 license. This guide has not undergone independent peer review.