Navigating the future: Exploring in-service teachers' preparedness for artificial intelligence integration into South African schools - Musa Adekunle Ayanwale; Sibusiso D. Ntshangase; Owolabi Paul Adelana; Kunle Waheed Afolabi; Umar A. Adam; Stella Oluwakemi Olatunbosun (Computers and Education: Artificial Intelligence)
This study contributes to existing research on how to integrate Artificial intelligence (AI) into school systems globally. This research explores in-service teachers' preparedness for integrating artificial intelligence into schools. We conducted this research within the context of the South African school system with teachers of various specializations, including sciences, social Sciences, mathematics, and languages. Drawing on the extended Unified Theory of Acceptance and Use of Technology (UTAUT2), we gathered teachers' perspectives through eight variables of technology integration, social influence, AI ethics, attitudes, TPACK, perceived self-efficacy, AI professional development, and AI preparedness. To analyze the 430 teachers' data involved in this study, we used a structural equation modeling analytical approach with SmartPLS software version 4.1.0.0. Our results indicate that technology integration, social influence, attitudes, and perceived self-efficacy influence teachers’ preparedness for AI. However, TPACK and ethics do not influence preparing teachers to integrate AI into schools. This study further presents interesting insight based on the mediation and moderation analysis of the variables. We discuss our findings and highlight their implications for practice and policy.