Generative Artificial Intelligence dalam Mendukung Implementasi Deep Learning dalam Pendidikan Matematika: A Systematic Literature Review - Yakin Niat Telaumbanua (FARABI: Jurnal Matematika dan Pendidikan Matematika, 2026)
This study aims to examine the development of research on generative artificial intelligence in mathematics education through a systematic literature review approach. A total of 50 references were analyzed thematically to identify article characteristics, thematic categories, main findings, and their implications for mathematics learning. The review results show that generative AI has great potential to support concept explanation, provide quick feedback, personalize learning, and assist teachers in designing learning activities. On the other hand, the findings also indicate that the use of generative AI is not without risks. The challenges include students’ dependence on instant answers, the possibility of misconceptions, and issues of academic integrity. Therefore, the use of generative AI in mathematics education needs to be guided carefully and supported by adequate pedagogical supervision. These findings confirm that the effectiveness of AI integration in mathematics education depends heavily on the pedagogical design used. Accordingly, generative AI should be placed within a deep learning framework that emphasizes conceptual understanding, reflection, and mathematical reasoning. In this way, AI technology functions not only as a tool, but also as a means of strengthening meaningful mathematics learning.