Theoretical Foundations of Authentic Assessment in an AI-Augmented Era
Theoretical conceptualisations of authentic assessment after the emergence of generative artificial intelligence diverge significantly in their foundational frameworks and pedagogical objectives across higher education literature. On one side of the academic discourse, institutional adaptation models focus on structural disruption and systemic realignment across international tertiary environments (Sullivan et al., 2023). This analytical perspective conceptualises authenticity primarily as a pragmatic countermeasure to technological vulnerabilities, examining broad institutional debates to argue that universities must restructure evaluative mechanisms while addressing acute academic integrity concerns (Sullivan et al., 2023). Under this operational view, authentic tasks operate as functional tools designed to preserve evaluative validity amid pervasive technological availability. In sharp contrast, virtue-oriented approaches position authenticity not merely as structural assessment mechanics, but as an internalised educational outcome grounded in student character development and academic leadership (Rudolph et al., 2023). Rather than treating conversational chatbots strictly as threats to detection protocols or traditional exams, this conceptual framework contends that authentic assessments function as enablers for learners who have cultivated ethical agency, empowering them to navigate artificial intelligence constructively (Rudolph et al., 2023). Meaningful theoretical differences therefore emerge between structural paradigms that treat authenticity as an institutional defensive apparatus and developmental frameworks that define authenticity through character growth. Ultimately, contemporary theoretical synthesis demonstrates that resilient assessment design requires unifying these divergent perspectives, balancing rigorous task redesign with deliberate moral cultivation in tertiary learning environments.