Acceptance and use of artificial intelligence and AI-based applications in education: A meta-analysis and future direction

Abstract

The aim of present study was to measure the relationship of UTAUT (Unified Theory of Acceptance and Use of Technology) and TAM (Technology Acceptance Model) variables regarding AI technology and AI-based applications acceptance in education sector. Research was carried out by using PRISMA (Preferred reporting items for systematic review and meta-analysis) guidelines. The relevant studies were searched from major databases that included a) Scopus, and b) Web of Science. Initial search retrieved 309 titles, and 30 relevant articles and conference papers were selected following the search process. Data was analysed using CMA (Comprehensive Meta-analysis) and Meta-Essential software. Findings exhibit that the relationship between UTAUT variables and BI to accept AI and AI-based applications in education was high (PE → BI), medium (EE → BI, SI → BI), and low (FC → BI). The magnitude of the relationship of TAM constructs remained high for all paths (PU → AT, PEOU → AT, PU → BI, and PEOU → BI). Theoretically, this meta-analysis provided a panoramic picture of two leading technology acceptance models regarding the acceptance/adoption of AI and AI-based technology in education sector. This meta-analysis provided a way forward for researchers to extend research on AI-based applications including ChatGPT, intelligent tutoring, AI-based robots, AI-based Chatbots, and AI-based voice assistants. Practically, findings are useful for IT companies, and decision makers of educational institutes in designing and implementing AI and AI-based applications.