Exploring the Landscape of Artificial Intelligence Application in Mathematics Education: A Scoping Review

Abstract

This thesis explores the integration of artificial intelligence (AI) in mathematics education, highlighting both its potential benefits and inherent complexities. Through a scoping review of existing literature and AI applications, key findings reveal that tools such as Intelligent Tutoring Systems and Adaptive Learning Platforms enhance personalized learning, engagement, and student performance. However, significant challenges such as technology access disparities, the need for extensive teacher training, data privacy concerns, and ethical implications impede widespread adoption. The study emphasizes the importance of ongoing research, particularly longitudinal studies on AI's long-term effects and its role in developing higher-order cognitive skills. It also calls for strategic efforts from educators, policymakers, and technologists to ensure equitable access, effective professional development, and robust ethical guidelines. This research contributes to the growing body of knowledge on AI in education, offering insights that can inform future research, practice, and policy, ultimately advancing the integration of AI in mathematics education.