A Systematic Review of AI-Enhanced Mathematics Learning: Implications for Student Motivation, Interest, and Engagement Rani Rizka Ramdani (a *), Kana Hidayati (b)
Department of Mathematics Education, Yogyakarta State University, Indonesia.
(a*) ranirizka.2023[at]student.uny.ac.id, (b) kana[at]uny.ac.id
Abstract
The rapid development of artificial intelligence (AI) has revolutionized various aspects of education, offering significant potential to improve the quality of mathematics learning. While much research has focused on cognitive benefits, affective aspects such as student motivation, interest, and engagement are often less explored. This study aims to systematically examine how AI integration impacts student motivation, interest, and engagement in mathematics learning across various educational levels. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, this systematic review synthesizes findings from 12 relevant, peer-reviewed articles published between 2018 and 2025, which were selected from six reputable international databases. The results of the analysis show that the use of AI-such as ChatGPT, AI-based gamification, and other generative platforms-significantly and positively impacts student motivation, interest, and engagement. This improvement is achieved through personalized, interactive, and contextual learning approaches that can reduce students^ cognitive load. While this positive impact was found at all education levels, research is most dominant at the secondary school level, and the study identifies a literature gap at the primary and tertiary education levels. Furthermore, a key finding includes implementation challenges related to teachers^ readiness to optimally integrate AI. Therefore, the successful utilization of AI depends on aligning the type of technology with pedagogical goals and strengthening the professional capacity of teachers to create effective, sustainable learning oriented towards enhancing students^ affective aspects.
