When the topic of Artificial Intelligence (AI) comes up in relation to educational assessment it tends to be treated with extreme excitement or extreme suspicion, or sometimes a combination of both. The opportunities presented throw up an equal volume of questions and concerns around how and when it should or could be used. An obvious application of AI to educational assessment is to use it for marking (scoring) learners’ responses to test items, against a mark scheme (rubric). Assessments such as GCSE or A level examinations in England comprise many such items, for instance essays and open text responses. And while we’re not currently considering using AI as a prime marker, we are looking at ways to train large language models to support our existing quality assurance arrangements for examination marking.

Irenka Suto, Head of Assessment and Research, Cambridge Centre for Evaluation and Monitoring

As the 21st century began to unfurl, it was becoming increasingly evident that technological ‘connectedness’ was revolutionising not only business and interpersonal relationships but also education. It seemed only a question of time before technology would provide an alternative means for supporting learning (Säljö, 2010), drive changes in assessment design (Bennett, 2002; Shute & Becker, 2010), and prompt efforts to reconfigure existing cycles of teaching, learning and assessment (Shute, Ventura & Kim, 2013; Thornton, 2012).