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All Journal Journal of Advanced Computer Knowledge and Algorithms Gameology and Multimedia Expert
Nasrullah Rahimi
Kunduz University
Computer Science & IT

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Journal : journal of advanced computer knowledge and algorithms

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The Role of Artificial Intelligence in Mathematics Education: A Systematic Literature Review of Teaching, Learning, Assessment, and Future Challenges Zaidullah Zaheed; Nasrullah Rahimi; Shahwali Shahidi
Journal of Advanced Computer Knowledge and Algorithms Vol. 3 No. 4 (2026): Journal of Advanced Computer Knowledge and Algorithms - October 2026
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v3i4.30450

Abstract

Artificial intelligence (AI) is reshaping how mathematics is taught, learned, and assessed, yet the evidence is scattered across computing, learning-sciences, and education research. This study aims to synthesise what is known about the role of AI in mathematics education and to identify the challenges that will shape its next decade. A PRISMA-informed systematic literature review protocol was applied to a curated corpus of 40 peer-reviewed studies, meta-analyses, benchmark papers, and authoritative books published between 1984 and 2024. The corpus was coded against four research questions covering AI techniques, teaching and learning applications, assessment and feedback, and open challenges, and was synthesised into a conceptual model linking AI technologies, pedagogical functions, learning outcomes, and governance. The results show that intelligent tutoring and adaptive practice systems have the strongest evidence base, with reported effects that are large in controlled studies (0.3 to 0.8 standard deviations) but shrink to roughly 0.2 at scale. Learner-modelling algorithms such as knowledge tracing underpin personalisation, whereas large language models have shifted attention to conversational tutoring and automated feedback, although their mathematical reliability remains uneven. Persistent challenges include algorithmic bias, privacy, invalid generated solutions, over-reliance, and limited teacher involvement. The review concludes that AI is most effective when it complements teachers, provides step-level feedback, and is governed by transparent, verifiable algorithms. The findings offer a research and design agenda for developers, educators, and policymakers.
Co-Authors Shahwali Shahidi Wali Mohammad Wadeed Zaidullah Zaheed