Frameworks for Artificial Intelligence Literacy in Higher Education (#1620)

Authors

Rojas Contreras, Mauricio

Mendoza Bejarano, Jose Liviston

Villamizar Carrillo, Laura

Villamizar Peña, Oscar Albeiro

Quintana, Leydi Carolina

Abstract

The rapid integration of generative artificial intelligence (AI) systems and AI-driven tools in social and professional domains has made AI literacy a critical competency for students, educators, researchers, and administrators in higher education. This study synthesizes current research on AI literacy frameworks in the context of universities, highlighting their dimensions, units of analysis, gaps, and emerging trends. A systematic literature review was conducted, focusing on the essential components of an AI literacy framework for higher education. The search equation, developed using a generative AI tool, was applied to the Scopus database and the AI-powered search engine Undermind, yielding 173 documents. Inclusion and exclusion criteria were applied, resulting in 20 articles for analysis. The findings reveal a growing trend towards interdisciplinary and competency-based approaches to foster AI literacy in higher education. Key components identified include technical knowledge, ethical considerations, social responsibility, critical thinking, collaboration, innovation, and adaptability. However, challenges persist, such as the need for empirical validation of conceptual models, adaptation to rapidly evolving AI technologies, and addressing equity gaps. Future research should focus on integrating universal and personalized frameworks, minimizing equity gaps, and iteratively adapting to the implications of AI advancements. This study provides a foundation for exploring strategies to equip higher education stakeholders with the necessary AI literacy skills to navigate and thrive in an AI-driven future.