Artificial intelligence applications for improving educational quality in elementary schools: A systematic literature review

Abstract

Elementary school education plays a fundamental role in developing students’ basic skills and competencies, yet it continues to face increasing challenges related to diverse learner needs, instructional quality, and the growing demands of digital transformation. In this context, the rapid advancement of artificial intelligence (AI) offers promising opportunities to enhance learning quality through personalized instruction, adaptive learning systems, and improved instructional efficiency. This study aims to examine the use of artificial intelligence in improving the quality of education at the elementary school level and to analyze its implications for both teachers and students. This study employed a systematic literature review (SLR) approach by analyzing relevant studies published between 2020 and 2025 and retrieved from Google Scholar. A structured screening and selection process was conducted based on predefined inclusion and exclusion criteria, resulting in ten studies selected for in-depth analysis. The selected articles were analyzed using qualitative content analysis to identify patterns related to AI implementation, pedagogical impacts, and challenges in elementary education contexts. The findings indicate that AI in elementary education is predominantly utilized as a pedagogical support tool rather than as a substitute for teachers. The integration of AI contributes to improvements in students’ cognitive understanding, learning motivation, engagement, and instructional differentiation. Additionally, AI supports teachers by providing rapid feedback, enhancing instructional efficiency, and assisting in the delivery of complex learning materials. However, the impacts reported in the reviewed studies tend to be incremental and short-term, with limited empirical evidence demonstrating long-term or transformational effects on learning outcomes. Furthermore, the successful implementation of AI is strongly influenced by teacher readiness, pedagogical competence, and institutional support. Issues related to AI literacy, ethical considerations, and human–AI interaction at the elementary school level remain insufficiently explored. This study concludes that while AI holds significant potential to improve the quality of elementary education, its sustainable and meaningful integration requires strengthened teacher capacity, supportive institutional frameworks, and further research employing longitudinal and experimental designs.

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