Unraveling the Factors Influencing the Adoption of Artificial Intelligence (AI) in Education
This research highlights the significance of identifying the primary factors that contribute to the successful integration of artificial intelligence in the field of education, using DEMATEL analysis to examine the causal connections behind the adoption of AI in education.
Abstract
The primary objective of this research was to investigate the key factors that influence student acceptance of Artificial Intelligence (AI) in the context of education. This investigation was conducted using the Statistical Analysis (SA) approach. A cohort of 200 students was selected to participate in the study, contributing quantitative data. The research evaluated seven criteria, including Learning Outcomes (A1), Cost-effectiveness (A2), Accessibility (A3), Efficient Learning (A4), Adaptability (A5), Customization (A6), and Career Readiness (A7). The results of the study emphasized the primary criteria that have a significant impact on student acceptance, namely Learning Outcomes (A1), Cost-effectiveness (A2), and Accessibility (A3). This research highlights the significance of identifying the primary factors that contribute to the successful integration of artificial intelligence in the field of education. The present exploratory inquiry serves as a foundation for future investigations, using DEMATEL analysis to examine the causal connections behind the adoption of AI in education.