The Role of Artificial Intelligence (AI) and Learning Analytics (LA) in Personalizing Mathematics Learning: A Systematic Literature Review

Abstract

The development of digital technology has opened up new opportunities in education, particularly in improving the effectiveness of mathematics learning through a more personalized approach. This article aims to examine the role of Artificial Intelligence and Learning Analytics in facilitating personalized mathematics learning at various levels of education. Using a Systematic Literature Review method, this article analyzes several studies published in the past five years related to the application of Artificial Intelligence and Learning Analytics in the context of mathematics learning. The results of the study indicate that Artificial Intelligence can provide materials and feedback tailored to students' abilities in real-time, while Learning Analytics allows teachers to monitor and evaluate students' learning progress more accurately and data-driven. The application of these two technologies has been shown to improve students' conceptual understanding, problem-solving skills, and learning motivation. However, challenges such as student dependence on technology, underutilization of feedback, and AI's limitations in addressing students' emotional aspects are important concerns. Therefore, more holistic technology development, adequate teacher training, and ethical policies related to data protection are needed. These findings emphasize the great potential of Artificial Intelligence and Learning Analytics in creating more adaptive, efficient, and meaningful mathematics learning experiences in the digital era.