Continue using or gathering dust? A mixed method research on the factors influencing the continuous use intention for an AI-powered adaptive learning system for rural middle school students

作者：Jining Han, Geping Liu, Xinmiao Liu, Yuying Yang, Wenying Quan, Yongfu Chen · 发表于：Heliyon · 年份：2024 · DOI：10.1016/j.heliyon.2024.e33251 · 被引用次数：21 · 研究领域：Technology Adoption and User Behaviour、Online Learning and Analytics、Smart Cities and Technologies

This paper investigates the factors influencing the continuous use intention of AI-powered adaptive learning systems among rural middle school students in China. Employing a mixed-method approach, this study integrates Technology Acceptance Model 3 with empirical data collected from rural middle schools in western China. The main contributions of this study include identifying key determinants of usage intention, such as computer self-efficacy, perceived enjoyment, system quality, and the perception of feedback. The findings provide insights into enhancing rural education through AI and suggest strategies for developing more effective and engaging adaptive learning systems. This research not only fills a significant gap in the understanding of AI in education but also offers practical implications for educators and policymakers aiming to improve learning outcomes in rural settings.