A Conceptual Framework for Academic Management to Enhance Assessment Quality in International Schools in the Age of Artificial Intelligence

Federico Verri

Authors

Federico Verri -

Keywords:

Academic Management, Assessment Quality, International Schools, Educational Leadership, Artificial Intelligence

Abstract

This scholarly paper claims that the quality of assessment in international schools can no longer be considered as a technical issue that is limited to rubrics, moderation or examination security per se. Academic management means the organizational ability to achieve policy, curriculum, assessment design, staff judgment, stakeholder communication, and quality assurance processes in the age of artificial intelligence to ensure reported outcomes are credible. This article has two objectives. First, it explains why international schools have a unique quality of assessment dilemma: they usually integrate transnational curricula, high parental expectations, fee-based, high reputational pressure, and increased exposure to AI-assisted student work. Second, it offers a theoretical model of academic management that can enable leaders to safeguard the quality of assessment without making schooling a surveillance. The literature analysis is based on scholarly research in academic integrity, educational leadership, organizational trust, stakeholder engagement, and generative AI in education. The suggested framework comprises of six mutually dependent areas, namely policy coherence, assessment architecture, staff capability and calibration, AI governance, stakeholder role clarity, and quality assurance feedback loops. The main argument is that it is not because of detection tools or specific penalties that the quality of assessment is guaranteed, but because of an entire school management system that helps to make valid learning evidence more transparent, decisions more predictable, and standards more justifiable. The article adds a management-based perspective to the educational leaders in overseas schools and presents a more plausible answer to AI, which is not banning, but more robust academic administration of assessment planning, professional judgment, and institutional responsibility.

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