Leveraging Artificial Intelligence in higher education

Abstract

This concept paper explores the adoption of artificial intelligence (AI) in higher education, arguing that such integration must be guided by established teaching and learning theories, rather than purely technological models like TPACK and TAM. While AI presents opportunities for enhanced teaching, learning and administrative efficiency, it also raises concerns about academic authority, digital competence, and ethical implications. Drawing on Vygotsky’s social cognitive theory, particularly its emphasis on cultural tools and social mediation, we propose a methodological approach that analyses higher education components, their interrelationships, and the formation of an institutional data pool. This Vygotsky-inspired framework advocates for leveraging AI through an institutional content management system (CMS) to foster collaborative knowledge construction. The paper addresses key challenges, including utopian-dystopian divides, ideological biases, and the need for new AI discourse, thereby contributing to a theoretically grounded model for AI integration in higher education.