Jul 2026· Journal of Higher Education Theory and Practice· 0 citations
TL;DR
This conceptual paper synthesizes insights from ten institutional cases across global contexts and draws on five theoretical foundations, Diffusion of Innovation, the Technology Acceptance Model, Self-Determination Theory, Social Learning Theory, and Academic Integrity frameworks, to propose a process model of AI adoption and use in higher education.
Abstract
Artificial Intelligence (AI) is reshaping higher education by transforming how students learn, how faculty teach, and how institutions manage academic processes. While AI offers opportunities for autonomy, competence, collaboration, and efficiency, it also raises concerns of dependency, quasi-plagiarism, and academic dishonesty. This conceptual paper synthesizes insights from ten institutional cases across global contexts and draws on five theoretical foundations, Diffusion of Innovation, the Technology Acceptance Model, Self-Determination Theory, Social Learning Theory, and Academic Integrity frameworks, to propose a process model of AI adoption and use in higher education. The model explains how faculty engagement, institutional policy, student motivation, peer norms, and integrity enforcement interact to shape learning outcomes, distinguishing authentic use of AI from misuse. By addressing policy gaps, governance challenges, and equity concerns, the study contributes to theory by advancing multi-framework integration and to practice by offering strategies for ethical, responsible, and sustainable AI adoption in higher education.
This conceptual paper synthesizes insights from ten institutional cases across global contexts and draws on five theoretical foundations, Diffusion of Innovation, the Technology Acceptance Model, Self-Determination Theory, Social Learning Theory, and Academic Integrity frameworks, to propose a process model of AI adopt...
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