Harnessing AI-Powered Learning Media in Mathematics Education: A Systematic Review on Improving Students’ Problem-Solving Skills - Lestari, Werdi; Suweken, Gede; Sariyasa, Sariyasa (International Journal of Education, Management, and Technology, 2025)
Although the integration of Artificial Intelligence (AI) in education has received growing attention, limited research has explicitly examined the development and application of AI-assisted exploratory learning media in mathematics. This study aims to analyze the characteristics, implementation, and potential effectiveness of AI-based learning tools in enhancing students’ mathematical problem-solving and critical thinking skills. A Systematic Literature Review (SLR) was conducted, drawing from studies published between 2016 and 2025 in the Google Scholar and Scopus databases. Using predefined inclusion and exclusion criteria, 20 relevant articles were selected and thematically synthesized to identify prevailing trends and research gaps. The findings reveal that AI integration in mathematics education predominantly supports personalized, adaptive, and interactive learning, fostering deeper conceptual understanding and the development of higher-order thinking skills. However, few studies have focused specifically on AI-assisted mathematics learning media. Key challenges identified include insufficient teacher preparedness, ethical concerns surrounding AI deployment, and the complexity of integrating AI tools into existing curricula. The study contributes theoretically by positioning AI as a cognitive and dialogic partner in the learning process, rather than a purely computational instrument. It also offers practical insights into the design and implementation of AI-supported learning environments. The analysis concludes that when integrated with digital tools such as EdCafe AI, GeoGebra, Scratch, and Canva, AI-assisted exploratory media can significantly enhance students’ conceptual mastery and problem-solving capabilities in mathematics. The study recommends targeted teacher training, the development of ethical frameworks for AI use, and increased empirical research to support responsible, student-centered implementation of AI in mathematics education.