Generative AI and Assessment

At TU Dublin, we take a human-centred approach to GenAI that puts pedagogy and the needs of learners first. We view GenAI as an enabler that can support educational goals and potentially extend human capabilities, while recognising that human intelligence, judgement, critical thinking and creativity remain central to educational practice.  Decisions about the use of GenAI should therefore always begin with a critical consideration of why, whether, and under what conditions these technologies might meaningfully contribute to the achievement of learning outcomes or enhance the learner experience, including whether their use is appropriate or necessary in the first place. At all times, staff who teach at TU Dublin should be guided by our Guidelines on the Responsible use of Generative AI in Teaching, Learning and Assessment. 

On this page, you will find information about different approaches to AI and assessment, the AI Assessment Scale, and GenAI, assessment and academic integrity. For further guidance on the human-centred, pedagogically grounded approach outlined above, and resources to support the critical evaluation of GenAI in your teaching practice, please visit our GenAI guidance pages. These pages include guidance on communicating with learners about GenAI, as well as information about relevant institutional policies, available supports and CPD opportunities.

The 'GenAI Assessment Challenge'

The emergence of generative AI has prompted widespread debate about the future of assessment. While concerns about academic integrity often dominate discussion, the challenge is broader than preventing inappropriate AI use. It encompasses questions of assessment validity, authenticity, equity, workload, skills development, professional preparation, and trust in qualifications. Recent work by Corbin and colleagues (2025) suggests that the assessment challenges associated with GenAI may be best understood as a ‘wicked’ problem: the nature of the challenge may look different from one perspective to another, no single solution will work in every context, and new challenges and possible responses will continue to emerge as the technology evolves.

The GenAI assessment challenge can be viewed through a variety of lenses. The table below outlines some of the most common framings.

In practice, many lecturers will recognise elements of several of these perspectives in their own work.  While they may point towards different responses, there is rarely a single solution that resolves every concern. Instead, assessment design involves making professional judgements that balance educational goals, learner needs, disciplinary values, and practical realities. Framing the Gen-AI Assessment challenge is helpful because it removes the expectation that educators must immediately find the perfect solution. As Corbin et al. note, no single assessment method, policy, or institutional response can be expected to address the GenAI assessment challenge fully or permanently. Instead, effective responses are likely to be context-sensitive, informed by disciplinary values, and continually adapted as technologies and educational practices evolve. The goal is not to "solve" GenAI once and for all, but to make thoughtful, evidence-informed decisions that support learning while maintaining confidence in assessment and academic standards. This may feel like a difficult landscape to navigate, but a clear focus on learning, context and purpose can help guide decisions.

As with most assessment decisions, we recommend starting with the learning you want your assessment to evaluate and support, and designing from there. Expand the accordion below for guidance on this process, including identifying aspects of your assessment that may be vulnerable to 'AI substitution' and beginning to make intentional choices about how your assessment design might restrict GenAI use, remain valid where GenAI is available, or intentionally allow for and integrate it.

Bringing It Together: A Decision-Making Framework