Investigation of artificial intelligence readiness factors at open and distance education institutions

Artificial intelligence (AI) technologies, which play an active role in almost every aspect of our lives today, have led to a paradigm shift in education, promoting a learner-centered and personalized approach. AI technologies offer numerous advantages in open and distance learning such as personalized learning, adaptive learning, decision support services, fast and correct feedback delivery, automated assessment, recommendation systems, etc. However, the complexity of AI's technical features and the lack of sufficient knowledge about these technologies make AI adoption and implementation challenging. This study aims to examine readiness factors that contribute to successful AI adoption among distance learning institutions. The theoretical framework of the study utilized the Technology-Organization-Environment model (Tornatzky ve Fleischer) and the Diffusion of Innovation Theory (Rogers, 2003). Additionally, a phenomenological research design was employed to understand AI readiness of distance learning institutions. Therefore, semi-structured in-depth interviews were conducted with 15 international domain experts. The research data were analysed descriptively using NVivo 14, and thematic coding was applied. The analysis revealed the following themes related to the AI readiness of distance learning institutions: organizational readiness, technological readiness, environmental readiness, ethical readiness for AI, as well as gaps and recommendations. Then the findings regarding these themes and sub-codes were interpreted in detail in separate sections. In the conclusion and discussion section of the study, numerous findings, recommendations, and strategies were shared to provide insights for academics, administrators, and decision-makers. Finally, the study presented the "AI Readiness Institutional Assessment Checklist" as a managerial influence to guide decision-makers and administrators during AI adoption.