Integrating Artificial Intelligence into Science Education in Primary Schools: A Systematic Literature Review - Apriyani, Paramita Putri; Anggriani, Ni Ketut (Indonesian Journal of Elementary and Childhood Education, 2025)
The development of artificial intelligence (AI) has driven significant transformations in learning through adaptive, personalized, and data-driven systems, including in primary education. In elementary science education, AI has the potential to support conceptual understanding and differentiated learning from early stages of cognitive development. This study aims to map research trends, dominant types of AI technologies, pedagogical impacts, and implementation challenges of AI in elementary science learning. A Systematic Literature Review (SLR) was conducted following PRISMA guidelines. Literature searches were carried out in the Scopus, Web of Science, and Google Scholar databases, covering articles published between 2016 and 2025. Of the 312 articles identified, 33 met the inclusion criteria and were analyzed qualitatively. The findings indicate a significant increase in research on AI in elementary science education in the post–COVID-19 period, with adaptive learning technologies and intelligent tutoring systems dominating the field and contributing to improvements in students’ cognitive learning outcomes and learning motivation. However, the use of AI to support higher-order science process skills remains limited. The main challenges include teachers’ pedagogical readiness, infrastructure disparities, and ethical issues related to student data protection. This review highlights the need for more contextual, pedagogically oriented, and sustainable approaches and policies in the integration of AI into elementary science education.