SYSTEMATIC LITERATURE REVIEW: AN ANALYSIS OF THE ROLE OF ARTIFICIAL INTELLIGENCE IN PERSONALIZING LEARNING TO DEVELOP ELEMENTARY SCHOOL STUDENTS’ COMPETENCIES

Abstract

This study aims to analyze the role of Artificial Intelligence in personalized learning
and its contribution to the development of elementary school students’ competencies. This study
employs a qualitative approach using the Systematic Literature Review (SLR) method, drawing
on eight scientific articles retrieved from Google Scholar over the past five years. The research
stages include literature identification, selection, evaluation, and synthesis. The results show that
Artificial Intelligence supports more adaptive and personalized learning by tailoring instructional
materials to students’ learning needs. Artificial Intelligence also contributes to enhancing student
engagement, learning outcomes, and 21st-century competencies such as digital literacy and critical
thinking. However, its implementation still faces challenges, including teacher readiness,
infrastructure, and the digital divide.