Generative AI technologies and their role within assessment design

Assessment serves multiple purposes within education (Brown, Bull and Pendlebury, 2013). One of its primary functions is to provide evidence of student learning that accurately reflects the efforts of an individual, and clearly demonstrates mastery of their knowledge, understanding, and skills. However, recent advances in, and the availability of, generative AI technologies mean that such tools now have the potential to be increasingly used by students for the completion of their assessments. This necessitates careful consideration of assessment design to ensure that where generative AI tools might be used by learners, their use is responsible, and the contribution of the individual learner to the work can be clearly demonstrated.

Importantly, consideration of the implications of generative AI technologies should not be used to automatically favour one assessment type over another, such as for example the increased use of invigilated on-campus examinations, which themselves have both benefits and limitations in assessing students’ learning (Buckley, 2023). Instead, this offers a timely opportunity for academic members of staff to consider good assessment design and more broadly seek to answer the questions: Why are students are being assessed? To what extent are they being assessed? What is being assessed and why? This should be undertaken alongside carefully examining how evidence of individual student learning and the associated achievement of learning outcomes is being collected at a programme, rather than module, level.