Reconceptualising Evaluation and Assessment in the Era of AI: From Human-Centred Assessment to Hybrid Intelligence

Artificial intelligence (AI) is reshaping the conceptual, methodological, and ethical foundations of educational evaluation and assessment. Contemporary assessment models are increasingly challenged by the erosion of clear boundaries between human and machine authorship, complicating assumptions about what constitutes learner-generated performance, knowledge, and competence. The classical assessment paradigm, grounded in the assumption that learner performance reflects individual and independently produced cognition, is increasingly inadequate in educational environments in which AI authors tasks, scores responses, generates feedback, converses with learners, and accompanies students as a partner in the learning processes. This editorial introduces five contributions to this special issue and uses them to advance a broader conceptual agenda for evaluation and assessment in the age of AI. We position the role of assessment in the age of AI across two interconnected areas: assessment and evaluation for AI-integrated learning, where learners collaborate with AI systems to co-construct knowledge and improve performance, and AI-assisted and AI-mediated assessment, in which AI supports, shapes, and increasingly participates in the processes of evaluation, feedback, and decision-making. Across both domains, we develop an intersection of the evidence generated by the five articles included in this special issue, extending beyond the individual contributions to identify broader conceptual, methodological, and practical implications for assessment in the age of AI. We argue that AI’s integration into the learning-assessment ecosystem requires a fundamental reconceptualisation of assessment theory, validity, and learner agency under conditions of hybrid intelligence. We conclude by outlining a future research agenda for evaluation and assessment in AI-mediated educational environments.