Demystifying the Dynamic Determinants of Generative Artificial Intelligence (AI) Literacy for Adaptable Sustainable Education

Abstract

This research aims to demystify the dynamic determinants of generative artificial intelligence (AI) literacy for adaptable sustainable education (ASE) through the application of multistage structural equation modeling (SEM). Utilizing a quantitative approach, a structured questionnaire distributed via Google Forms is employed to gather data from a convenient sample of 260 teachers in higher education. The study unfolds over a specified period, incorporating rigorous data filtering techniques to enhance the reliability of responses. Smart-PLS serves as the primary tool for data analysis, allowing for an in-depth exploration of relationships among variables such as generative AI literacy, digital split, computational intelligence, and cognitive inclusion. Dependent variables include teacher perceptions, technological proficiency, and cognitive inclusion, while independent variables encompass awareness of AI and the perceived usefulness of AI in achieving ASE. The outcomes of this research carry significant policy implications for AI, ICT, and educational professionals, providing insights to shape informed strategies for integrating AI literacy into higher education to meet the goals of adaptable sustainable education.