Dr Hazel Farrell
Since the launch of ChatGPT in November 2022 and subsequent surge in Generative Artificial Intelligence (GenAI) technology, the education sector has been impacted significantly, with efforts to develop policies, strategies, and guidelines to support staff and students in navigating the changing landscape. While these technologies offer great potential for enhancing learning experiences, they also pose significant challenges to academic integrity. Assessment methods such as essays, unsupervised open-book or remote exams, and online quizzes, are increasingly vulnerable, as students can access AI tools to produce content that appears to be original but is not their own work.
Although AI detection tools have emerged, their reliability remains limited, and they cannot serve as definitive evidence of academic misconduct. The focus therefore shifts from detection to prevention, with emphasis on authentic learning experiences. This presents an urgent need for higher education institutions to reconsider their assessment strategies to uphold academic standards and ensure that assessments accurately reflect students' knowledge and skills.
This framework supports educators in redesigning assessments to ensure they remain valid, fair, transparent, and aligned with learning outcomes in an AI-enhanced educational landscape.
Assessment redesign is not solely a pedagogical issue but also a governance, quality, and ethical responsibility. National and international bodies now emphasise that assessment practices must remain robust when AI is increasingly accessible.
Key developments include national guidance encouraging AI literacy, transparency, and equitable access; UNESCO’s Recommendation on the Ethics of AI, which emphasises human oversight, inclusion, and accountability; and the evolving EU AI Act, which highlights education as a high-impact context requiring transparency and risk mitigation.
These developments reinforce the central argument of this framework: assessment must be redesigned structurally, rather than focusing on detection.
The goal of assessment redesign is to develop robust, fair, valid, and educationally meaningful approaches that ensure students can demonstrate genuine learning, understanding, and capability. Rather than focusing solely on preventing misuse of AI tools, assessment should be designed to make learning visible and to reflect how knowledge and skills are applied in authentic contexts.
By incorporating a diverse range of assessment types, balancing formative and summative approaches, and thoughtfully distributing high- and low-stakes tasks, educators can create a more resilient and integrity-informed assessment environment. Greater emphasis on process, reasoning, and development over time supports deeper learning and reduces reliance on single, product-focused submissions.
In practice, redesigning assessment presents challenges, including time constraints, large class sizes, and evolving institutional expectations. Nonetheless, careful consideration of where and how GenAI use aligns with educational purpose is essential. Some assessments may appropriately integrate AI to develop student AI literacy and future-ready skills, while others may require independent demonstration of foundational knowledge or professional competence.
Ultimately, the central guiding principle remains the alignment of assessment with programme and module learning outcomes. Assessment decisions — including format, level of supervision, and expectations around AI use — should be driven by what learners are expected to know, understand, and be able to do.
This framework supports educators and programme teams in rethinking assessment design in the context of GenAI. It focuses on ensuring that assessment remains valid, fair, and aligned with learning outcomes while also supporting the development of responsible and effective AI engagement.
Specifically, the framework supports educators to: