The Adoption of AI-Enabled Adaptive e-Learning Environment in Palestinian Schools: Integrating Extended Technology Acceptance Model and System Success Model

Abstract

AI-enabled adaptive learning environment is revolutionizing educational landscapes globally by offering personalized learning experiences. Despite their proven effectiveness, the acceptance of these technologies remains largely unexplored in Palestinian schools. This study aims to fill this research gap by investigating the factors influencing the acceptance of AI-enabled adaptive e-learning environment among schools in the Gaza Strip, Palestine. Utilizing the Extended Technology Acceptance Model (ETAM) and the DeLone and McLean Information Systems (IS) Success Model, a total of 202 schools participated in the study. The study examined several latent variables, including User Interface (UI), Perceived Ease of Use (PEU), Perceived Usefulness (PU), Information Quality (IQ), System Quality (SQ), Behavioral Intentions (BI), and Actual Use (AU). Statistical analyses, including Structural Equation Modeling (SEM), revealed that PU, PEU, and SQ positively influenced schools' behavioral intentions (BI) towards the actual use of the system. However, IQ showed mixed results, suggesting room for improvement in content delivery. The findings confirm that the level of acceptability among schools is significantly influenced by the system's ease of use, quality, and perceived usefulness, leading to a positive behavioral intention for its actual adoption. Given these results, schools and policymakers should focus on these critical aspects to facilitate broader acceptance and effective implementation of adaptive learning systems. This model can also serve as a framework for future quantitative and qualitative studies in areas of Palestine currently inaccessible due to Israeli occupation, such as the West Bank, or for other countries and can be adapted for use in other contexts.