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Gen AI policy evolution at Southern Cross University
Teaching case study   Open access

Gen AI policy evolution at Southern Cross University

Ruth Greenaway Professor and Zachery Quince Dr
Australian Government: TEQSA
19/03/2026
Appears in  Recent Faculty of Health Publications
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Abstract

Focus area: Governance Southern Cross University (SCU) took a first principles approach to policy development, supporting a strategic goal of ubiquitous gen AI use and positioning gen AI as an educational tool. An initial, binary model, where academics either permitted or prohibited gen AI use, overlooked disciplinary needs, causing confusion for staff and students, and limiting meaningful engagement. Seeking greater inclusivity and flexibility, SCU transitioned to a five-tier gen AI model, informed by the AI Assessment Scale and supporting the assessment principles of the Southern Cross Model. It mapped a continuum from prohibiting use to open collaboration, specifying permissible uses. The model, though pedagogically robust, proved complex in practice, presenting challenges to staff adoption and consistent implementation. In 2025, SCU introduced the Gen AI Tool Use Descriptors, a pragmatic three-level model of assessment security levels. Assessments now explicitly indicate their gen AI stance at Level 1, 2 or 3. This approach is designed to normalise gen AI as part of academic practice while promoting accountability and meeting the learning and teaching objectives. It is embedded in formal assessment protocols, with specific gen AI guidelines available for each task, evidentiary requirements and a compulsory student declaration, fostering openness and ethical engagement. Implementation of the Gen AI Tool Use Descriptors is underpinned by the Gen AI Descriptor Use Staff Guidelines, which provide assessment specific scaffolding, best practice examples and clear, structured support tailored to different assessment types, enabling academics to confidently integrate gen AI tools into their teaching and evaluation processes. Grounded in robust research on ethical considerations and student learning behaviours, the guidelines help staff define task expectations, document gen AI use and navigate the complexities of balancing gen AI’s benefits and risks. These measures strengthen academic integrity by promoting ethical engagement with gen AI and fostering a culture of transparency, consistency and accountability.

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