Navigating The Landscape of AI-Powered Personalized Learning in Primary Education: A Systematic Literature Review
Keywords:
AI, Personalized Learning, Basic Education, Systematic Literature ReviewAbstract
The integration of AI has brought about a significant transformation in primary education; however, the existing literature remains fragmented. This study aims to map the landscape of AI-powered personalized learning through a comprehensive literature review. The methodology employed is a systematic literature review, adhering to the PRISMA protocol, conducted in the Scopus database. Of the 114 documents identified, 33 selected scientific articles were analyzed using bibliometric techniques and content analysis with the help of VOSviewer and R Studio. The results of data analysis show a sharp spike in scientific production in 2025, with a total of 24 articles, an increase of up to 12 times compared to the annual average in the previous period. Indonesia leads the global contribution with a total of 7 related publications. The analysis of intellectual networks confirms the research focus on technological modalities for adaptive learning that cater to the unique needs of students. However, field implementation still faces significant challenges, including low teacher self-efficacy, limited infrastructure, and data privacy risks. The study concludes that strengthening the professionalism of educators and establishing a secure digital ecosystem are absolute prerequisites for technological success. Implication: Stakeholders need to restructure teacher training to focus on the interpretation of AI data.
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