🎓 Teaching, Learning & Assessment

Pillar 3 focuses on how Artificial Intelligence is integrated into pedagogical design, delivery, and evaluation. This pillar is evaluated through three core indicators: curriculum design and course development, personalised learning and academic support, and assessment, grading, and feedback. Ten sub-indicators provide a detailed picture of how AI is used to enhance the educational experience and maintain academic integrity.

The first set of sub-indicators examines the institutional approach to integrating AI into curriculum design, ensuring a deliberate and structured incorporation of AI tools and principles. This includes the use of AI to support course and assessment design, enabling more efficient creation of content and adaptive pathways for learners. A key element is the inclusion of AI literacy in the broader curriculum, equipping students with the understanding needed to critically engage with AI. The extent to which institutions offer courses or degree programs specifically focused on AI as a discipline, contributing to workforce readiness and capacity, is also covered.

The second group of sub-indicators addresses the personalisation of learning and support services including customising learning experiences, improving student engagement, and enhancing retention through data-informed interventions. Access to AI-driven academic support services and platforms is also incorporated into this indicator group.

Finally, the framework examines how AI is used in assessment and feedback, including the provision of real-time feedback, deployment of adaptive assessment tools, and the presence of bias validation processes to ensure fairness in automated grading systems.