UQ's governance of AI and teaching initiatives
UQ's governance framework ensures alignment of AI and teaching initiatives with the University's strategic goals, the Learning and Student Experience Roadmap and The Queensland Commitment. This work will be supported through the Lead through Learning project. Key elements of governance include:
- The DVC(A) oversees these plans in collaboration with the University executive.
- Faculties and schools contextualise actions to manage diverse disciplinary needs and risks associated with different teaching modes.
- Governance is supported by committees, including the Digital Learning Sub-Committee, Assessment Sub-Committee, Teaching, Learning and Student Experience Committee, Committee for Academic Programs and Policy, and Academic Board.
These committees, guided by the DVC(A) and senior executives, work with schools and faculties, monitoring assessment and misconduct data, and feedback from staff and students.
This governance ensures our AI initiatives are strategically integrated, continuously evaluated, and responsive to the evolving needs of the University community.
In responding to TEQSA’s request for information about how UQ is addressing the risk of artificial intelligence, UQ identified key principles to guide our work:
- Employing evidence-informed approaches to understand and respond to the impact of change to teaching, learning and assessment, alongside the evolving experiences of our staff and students.
- Working in partnership with students, staff and community partners to promote a culture of active engagement with AI throughout the entire educational journey.
- Integrating AI across all appropriate aspects of our work, curriculum and teaching to equip graduates with the skills for future AI applications in their disciplines, while also enhancing the quality and efficiency of teaching activities.
- Developing new assessment approaches to maintain credible assessment of learning outcomes and to strengthen assessment integrity in response to emerging AI capabilities.
- Monitoring assessment practices University-wide to maintain assessment security and credibility alongside student integrity.
- Prioritising student wellbeing and equity of access and reducing anxiety by providing clear and integrated guidelines on acceptable AI use in assessments, particularly at transition points such as first and final years or course work to higher degree research studies.
- Maintaining data management governance to ensure cybersecurity and the privacy of student and staff data.
- Supporting staff to adapt to the rapid changes required by evolving AI with appropriate guidance and resources.
