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January 28, 2026
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March 7, 2026
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March 8, 2026
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Abstract

This study presents a systematic review of the current literature on the integration of adaptive learning and generative AI (GenAI) in developing technological pedagogical content knowledge (TPACK) and statistical literacy of prospective mathematics teachers. By analyzing 76 selected articles published between January 2023 and May 2025, this study uses the PRISMA framework and thematic synthesis with the help of NVivo 12 Plus software. The results of the study indicate that adaptive learning environments supported by GenAI can strengthen learning personalization, provide responsive feedback, and visualize content, which significantly contribute to the development of TPACK, especially in the TPK and TCK domains. In addition, GenAI supports the strengthening of statistical literacy through data-driven instructional tools that foster the ability to interpret, represent, and understand the context of data. This study successfully formulated a conceptual framework for adaptive learning integrated with GenAI that reflects the pedagogical needs and specific content in mathematics education. These findings have important implications for teacher education programs, especially in facilitating professional competencies that are adaptive to technological advances and the demands of ethical and reflective data-driven learning.

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Adaptive LearningGenerative-AI (GenAI)TPACK FrameworkStatistical Literacy

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Copyright (c) 2025 Iyam Maryati, Makmur Harun, Surya Gumilar, Ayu Puji Rahayu

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Maryati, I., Harun, M., Gumilar, S., & Rahayu, A. P. (2026). Adaptive Learning and Generative AI in Mathematics Teacher Education: A Systematic Review. International Journal of Review in Mathematics Education, 1(1), 80–107. Retrieved from https://journals2.ums.ac.id/ijrime/article/view/15936 (Original work published March 7, 2026)
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