Abstract:

The accelerating integration of Generative Artificial Intelligence (AI) has disrupted traditional assessment practices, demanding a critical re-examination of ethics, pedagogy, and cultural inclusivity. While AI tools offer efficiency, consistency, and personalization in evaluation, they also raise pressing concerns about fairness, transparency, and institutional readiness. Across global contexts, many institutions remain unprepared for the ethical and cultural implications of this transformation. The absence of coherent policy guidance, inconsistent pedagogical alignment, and limited empirical validation in existing frameworks creates a widening gap between technological capability and institutional responsibility. Current conceptual models suffer from two critical limitations: a lack of empirical validation and limited cross-cultural applicability. This leaves many Higher Education Institutions (HEIs) struggling with institutional lag, evidenced by a quantitative finding that 39% of HEIs globally report having no formal AI policy or guidance under development. This policy vacuum elevates the risk of inequitable and ungoverned AI adoption in sensitive areas such as student assessment.

The CARE Framework (Cultural Assessment of Responsive AI through an Ethical Lens) proposes to help bridge institutional and cultural preparedness gaps. This paper will justify the need for a framework and outlines the conceptual and methodological foundations required for its development. Future research will draw on a proposed three-phase mixed-methods design, mapping how international educators and administrators could engage to identify ethical, pedagogical, institutional, and cultural factors that must structure a trustworthy AI-driven assessment model. These insights may inform the construction of the CARE Framework through systematic thematic analysis, followed by a plan for cross-cultural validation against established conceptual models of AI assessment. This forward-looking structure demonstrates how the framework can ultimately operationalize fairness and inclusivity in a manner attentive to global educational diversity rather than a singular, Western-centric definition of rigor.

This research-in-progress aims to establish a compelling rationale and design blueprint for a framework enabling higher education institutions to adopt AI responsibly, ethically, and contextually. Through cultural awareness, institutional readiness, and the urgent need for coherent governance, this framework is positioned as a future tool for strengthening ethical AI assessment practices. This research argues the importance of developing a model and articulates future steps for creation and validation. This conceptual contribution invites educators, policymakers, and technology leaders to consider AI not merely as a disruptive force but as a potential partner in cultivating equitable, human-centered learning environments worldwide.

Keywords:

Generative AI, Educational Assessment, Ethics in Education, Cross-Cultural Applicability, Assessment Framework.