The Use of AI in Elementary School Learning: A Systematic Literature Review

Abstract

This study systematically reviews the implementation of Artificial Intelligence (AI) in elementary education, focusing on the role of AI in enhancing teaching effectiveness, personalized learning, and student engagement. The research synthesizes various studies from the past decade to identify key AI technologies, the challenges faced, and the requirements for successful adoption in primary schools. The findings reveal that AI technologies, such as biosensors, voice recognition systems, and AI-powered platforms, significantly contribute to creating adaptive learning environments and providing real-time feedback, thus supporting personalized and experiential learning. However, the study also highlights challenges such as inadequate infrastructure, teacher competence, and ethical concerns regarding data privacy and algorithmic bias. Addressing these challenges requires investment in infrastructure, ongoing teacher training, and clear ethical guidelines to ensure equitable access to AI-driven learning. The study concludes that while AI holds great potential to transform primary education, its successful implementation depends on overcoming these barriers and fostering a culture of innovation within schools. The results offer practical recommendations for educators, policymakers, and technology developers to optimize AI use in primary schools, ensuring that it becomes an inclusive tool for enhancing educational outcomes.