How does assessment of learning need to change for a world where AI is ubiquitous? A research agenda

Phillip Dawson and Thomas Corbin

Chapter 14 in A Research Agenda for Artificial Intelligence and Academic Integrity, 2026, pp 212-222 from Edward Elgar Publishing

Abstract: Much debate about academic integrity and artificial intelligence (AI) relates to assessment. Significant concerns have been raised around the assessment of learning due to AI tools’ ability to produce outputs that receive passing grades with limited input from students. This chapter summarizes important fundamental assessment topics, such as assessment validity, the purposes of assessment, assessment security, and programmatic assessment. These concepts are crucial for scholars who wish to study academic integrity pertaining to students’ assessed work, which often receives scant attention in the academic integrity literature. The chapter presents a research agenda for the field and focuses on (a) supporting assessment validity in a time of AI, (b) evaluating and comparing the effectiveness of approaches to restricting AI use, and (c) ways to ensure student learning at a whole-of-qualification level. These are crucial questions if the field of academic integrity is to meaningfully address the challenge that AI poses for assessment.

Keywords: Assessment; Validity; Artificial intelligence; Academic integrity; Programmatic assessment; Assessment security (search for similar items in EconPapers)
Date: 2026
ISBN: 9781035343638
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