AI (Artificial Intelligence) Based Adaptive Learning in Mathematics Learning: Opportunities & Challenges Hadi Prayitnoz(a), Imam Sujadi (b), Isnandar Slamet (c) , Farida Nurhasanah (d)
Sebelas Maret University
Mathematic Education
Abstract
Digital transformation in education has opened up significant opportunities to deliver more personalized, adaptive, and effective learning. One of the key innovations is the use of adaptive learning powered by Artificial Intelligence (AI), particularly in mathematics education, which has long been perceived as difficult and challenging. This study aims to systematically evaluate the trends, opportunities, and challenges of implementing AI-based adaptive learning in mathematics education through a Systematic Literature Review (SLR) approach. A total of 25 scientific articles published between 2016 and 2024 were analyzed. The findings indicate a growing trend in the use of AI in adaptive learning, especially since 2018, with a dominance of experimental methods and a focus on learning outcomes, student motivation, and engagement. The main opportunities identified include improved academic performance, enhanced critical thinking skills, personalized learning styles, and sustainable independent learning. However, several challenges were also found, such as limited technological infrastructure, insufficient teacher readiness, digital inequality, and curriculum integration barriers. Thus, while AI-powered adaptive learning offers transformational potential in mathematics education, its success heavily depends on the readiness of the education system to provide adequate policy support, technological infrastructure, and teacher training.
