Artificial intelligence in higher education mathematics: a systematic review of ai-based platforms, challenges, and teaching transformation

Yee, Ming Chew and Set, Foong Ng and Kok, Shien Ng (2026) Artificial intelligence in higher education mathematics: a systematic review of ai-based platforms, challenges, and teaching transformation. Voice of Academia (VOA), 22 (2). pp. 26-38. ISSN 2682-7840
Identification Number (DOI): 10.24191/ VoA.v22i2.13413
Abstract

This study presents a systematic review of artificial intelligence (AI) applications in higher education mathematics, focusing on AI tools, associated challenges, and their implications for teaching transformation. Guided by PRISMA methodology, 16 studies published between 2021 and 2025 were selected from Scopus and Google Scholar. This review identifies generative AI tools, particularly ChatGPT, along with adaptive learning platforms such as ALEKS and KnowRe Math, as the most widely examined technologies. These tools support personalised and self-paced learning, enhance conceptual understanding through interactive features, and provide timely feedback. However, their key challenges include over-reliance on AI, data privacy concerns, and the need to preserve the critical role of educators in fostering deep and meaningful learning. Findings suggest that AI has the potential to transform teaching practices by enabling more adaptive, studentcentred learning environments. However, its effectiveness depends on responsible and pedagogically informed integration. This review contributes to the field by synthesising current evidence and highlighting key considerations for effective implementation of AI in higher education mathematics.

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