A Computational Meta-Analysis and Fuzzy Logic Insights Leveraging Artificial Intelligence and Machine Learning for Enhancing Learning Efficacy in Elementary Education - Harishchandra Singh, Prashant Vats, Kamiya Vats (International Journal of Intelligent Systems and Applications in Engineering, 2024)
This meta-analysis investigates the impact of technology on the learning effectiveness of elementary students by synthesizing a diverse range of empirical studies. In an era where educational technology is increasingly integrated into classrooms, understanding its nuanced effects on foundational learning becomes imperative. The study explores academic achievement, cognitive development, and socio-emotional learning dimensions, providing a comprehensive overview of the existing literature. The analysis encompasses various forms of technology, including digital tools, interactive platforms, and educational software. By aggregating findings from multiple studies, this meta-analysis aims to discern patterns and trends, shedding light on the intricate relationship between technology use and educational outcomes for young learners. Key considerations such as the digital divide, teacher preparedness, and parental involvement are scrutinized to offer a holistic perspective on the complex dynamics at play. The synthesis of research findings will contribute to an informed dialogue among educators, policymakers, and researchers, guiding future practices and initiatives in elementary education.