Role of perceived threats and knowledge management in shaping generative AI use in education and its impact on social sustainability

Abstract

Despite the rapid advancement and integration of Generative AI in various sectors, understanding its role in promoting social sustainability, particularly within the educational domain, remains unexplored. This research is propelled by the urgent need to explore this underexamined area, especially given the critical importance of social sustainability in ensuring equitable and inclusive educational outcomes. To address this gap, this study develops an integrated model that combines the insights of the Technology Threat Avoidance Theory (TTAT), the Technology-Environmental, Economic, and Social Sustainability Theory (T-EESST), and key knowledge management (KM) factors (knowledge acquisition and knowledge application). Using PLS-SEM, the proposed model was evaluated based on data collected through an online survey from 378 university students. The results showed that while perceived threats have a significant negative impact on Generative AI use, knowledge acquisition and knowledge application emerge as critical drivers for its effective use. Interestingly, using Generative AI was found to promote social sustainability significantly and positively. In addition to its theoretical contributions, this study underscores the need for a nuanced understanding of the barriers and enablers of Generative AI adoption, offering valuable insights for various stakeholders aiming to leverage AI tools for sustainable educational outcomes.