Assurance of learning in the age of AI

Abstract

As Artificial Intelligence (AI) continues to evolve and influence higher education, ensuring that Assurance of Learning (AoL) frameworks remain both robust and adaptable, is vital. This paper presents a qualitative document analysis of Australian university AoL frameworks, examining their readiness for AI integration. The findings reveal a sector in early adaptation, marked by a tension between foundational AoL principles and AI's disruptive pace. We observe strategic AI acknowledgement often confined to policy, a nascent reform of graduate attributes to encompass AI literacy, and innovative practices largely isolated at the course or program level. Consequently, core AoL components such as curriculum mapping and assessment design, often remain disconnected from AI-assisted learning, limiting their reliability. This highlights significant conceptual and operational gaps, including varied institutional maturity, fragmented approaches, and a lack of sector-wide consensus or explicit guidance on ethical, observable AI-enhanced assessment. This paper calls for a shift from static quality assurance, defined by periodic compliance checks, to dynamic and systems-aware learning assurance. It proposes a future-focused AoL approach that embeds AI literacy, inclusive assessment design and stronger sector collaboration. As the first in a series, it contributes to ASCILITE 2025 by exploring how human expertise and AI can uphold academic standards.

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