GAIA-EDU: A Generative Artificial Intelligence Framework for AI Augmented Academic Ecosystems in Higher Education

Abstract

As Generative Artificial Intelligence (GenAI) becomes more common in higher education, integrative methods will be needed to navigate the changing landscape. This paper proposes a holistic model for transforming the academic landscape that relies on AI tools and systems rather than simplistic ones, within the GAIA-EDU (Generative Artificial Intelligence for Academic Instruction and Advancement) framework. GAIA-EDU is all about using AI across all parts of higher education, including improving the academy's AI-infused ecosystems, teaching and learning, research and knowledge creation, assessment and feedback, academic administration, and the institution's decision-making processes. GAIA-EDU aims to address problems with integrating customizable generative AI tools and the changing roles and skills of knowledge workers. GAIA-EDU, like other higher education institution frameworks, aligns with the latest trends in educational frameworks and generative AI tools. GAIA-EDU, therefore, aims to facilitate the incorporation of functional generative AI tools for pedagogical purposes in higher education. This paper offers a thorough conceptual framework for researchers, educators, and policymakers aiming to develop, evaluate, and deploy generative AI-enhanced teaching and learning systems in higher education.

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