Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal AL JABAR: Jurnal Pendidikan dan Pembelajaran Matematika
Iwan Maulana
Universitas Negeri Surabaya
Mathematics

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
GENERATIVE ARTIFICIAL INTELLIGENCE IN MATHEMATICS EDUCATION: A SYSTEMATIC REVIEW OF DATA-DRIVEN APPLICATIONS, LEARNING THEORIES, AND IMPLICATIONS FOR SUSTAINABLE DEVELOPMENT GOAL Khoirul Anwar; Adelia Sherlyna; Alyssa Marfinda Salsanifa; Havi Ayuning Tyas; Syahda Eka Prayudistyan; Genta Aldi Saputra; Iwan Maulana
AL JABAR: Jurnal Pendidikan dan Pembelajaran Matematika Vol. 5 No. 2 (2026): April
Publisher : LPPM Institut Ahmad Dahlan Probolinggo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46773/x224sd70

Abstract

The rapid advancement of generative artificial intelligence (AI) has introduced transformative opportunities in mathematics education, yet its implications for pedagogical practices, learning theories, and sustainable development remain underexplored. This systematic review examines the intersection of generative AI and mathematics education, focusing on data-driven applications, theoretical frameworks, and their alignment with Sustainable Development Goal 4 (SDG 4), which advocates for inclusive and equitable quality education. We synthesize existing research to identify key trends, challenges, and opportunities across multiple dimensions, including higher education, STEM disciplines, adaptive learning, and ethical considerations. By analyzing diverse scholarly works, we uncover how gesnerative AI supports personalized learning, enhances problem-solving skills, and fosters engagement while addressing disparities in educational access. The review highlights the role of generative AI in promoting active learning through interactive tools, yet it also reveals concerns regarding algorithmic bias, data privacy, and the need for teacher preparedness. Our findings suggest that while generative AI holds significant potential to democratize mathematics education, its responsible integration requires robust pedagogical strategies and policy frameworks. The study contributes to ongoing discussions on AI-driven educational innovation by offering evidence-based insights for researchers, educators, and policymakers aiming to harness generative AI for sustainable educational development.
Co-Authors Adelia Sherlyna Alyssa Marfinda Salsanifa Genta Aldi Saputra Havi Ayuning Tyas Khoirul Anwar Syahda Eka Prayudistyan