Considerations for Effective Online Assessment in the Age of Artificial Intelligence
TL;DR
This critical essay argues that higher education should shift from product-centred assessment to a process-plus-performance model that makes reasoning, evidence selection, revision, feedback use, ethical judgement and intellectual ownership visible.
Abstract
Online assessment offers flexibility, scalability and rapid feedback, yet generative artificial intelligence (GenAI) has weakened the assumption that a submitted product reliably represents a student’s independent learning. This critical essay argues that higher education should shift from product-centred assessment to a process-plus-performance model that makes reasoning, evidence selection, revision, feedback use, ethical judgement and intellectual ownership visible. Drawing on process-writing theory, constructivism, constructive alignment, assessment for learning, self-regulated learning, the Community of Inquiry, authentic assessment and Universal Design for Learning, it examines the limitations of take-home essays, remote multiple-choice tests, AI detection and surveillance. It proposes staged assignments, critical evaluation and transparent disclosure of AI use, authentic and localised tasks, reasoned multiple-choice questions, brief oral verification and targeted secure assessment at key progression points. Because process records can also be fabricated, trustworthy judgement should triangulate written development with live explanation or practical performance. This layered approach supports academic integrity without treating surveillance as the default, while strengthening critical thinking, AI literacy, inclusion and professional accountability.