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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.
Transforming Microteaching through Flipbook for Preparing Future Accounting Educators towards SDG 4 Sri Widi Lestari; Khansha Sindra Irfani; Dwi Puji Astuti; Iwan Maulana
Teknodika Vol 24, No 1 (2026): Teknodika
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/teknodika.v24i1.108245

Abstract

his study investigates the role of digital innovation in teacher education by integrating a flipbook-based microteaching handbook into the Accounting Education program. Although printed modules remain widely used in microteaching courses, they often fail to effectively engage digital-native student teachers or support the development of essential 21st-century teaching competencies. Using a quasi-experimental pretest–posttest control group design, 60 fifth-semester students were assigned to an experimental group using the digital flipbook and a control group using printed modules. Microteaching performance was assessed through standardized rubric scores. Results showed significantly greater improvement in the experimental group, t(58)=4.37, p<0.001, with a large effect size (Cohen’s d=0.86). The experimental group achieved an 18.3% learning gain compared to 8.1% in the control group. Questionnaire data also indicated positive student perceptions regarding improved understanding (85%), confidence (92%), and motivation (88%). These findings demonstrate that flipbook-based materials not only enhance microteaching performance but also support higher engagement and digital readiness. Integrating interactive digital learning resources into teacher education can therefore contribute to achieving Sustainable Development Goal (SDG) 4, particularly Target 4.c on preparing qualified and digitally competent educators.