Learning Analytics dalam Mendukung Personalized Learning di Pendidikan Sekolah Dasar: Peta Pengetahuan dan Arah Penelitian Masa Depan

Riska Zafitri Cahyanti, Salsabila Aulia, Regina Dealova, Sintayana Muhardini, Haifaturrahmah Haifaturrahmah

Abstract


The development of Learning Analytics (LA) and Artificial Intelligence (AI) has accelerated data-driven learning, yet comprehensive evidence regarding their integration to support personalized learning in primary education remains limited. This study aims to analyze research trends, key themes, and future directions of LA and AI integration in personalized learning for primary schools. A Systematic Literature Review (SLR) was conducted using publications retrieved from Google Scholar, Elicit, Scite.ai, and SciSpace. The review included peer-reviewed articles published in English or Indonesian between 2017 and 2026 that addressed LA, AI, or their integration in education, while irrelevant, duplicate, and non-scholarly publications were excluded. The findings identified six major research themes: the evolution of LA, learning data analytics, adaptive learning, student engagement and learning outcomes, implementation challenges, and AI integration. The study concludes that integrating LA and AI supports adaptive, evidence-based personalized learning and provides a conceptual foundation for developing effective, ethical, and sustainable learning practices in primary education.

Keywords


Learning Analytics, Artificial Intelligence, Personalized Learning, Sekolah Dasar, Pembelajaran Adaptif.

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References


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Copyright (c) 2026 Riska Zafitri Cahyanti, Salsabila Aulia, Regina Dealova, Sintayana Muhardini, Haifaturrahmah Haifaturrahmah

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