Artificial intelligence in mathematics education: Innovation, independence, and the future of learning

Abstract

Artificial intelligence (AI) continues to exert a significant influence on mathematics education through personalised learning, adaptive instruction, automated feedback, and intelligent learning support. While existing literature has underscored the potential of AI to enhance teaching and learning, there has been comparatively less emphasis on its implications for learner independence and the future trajectory of mathematics education. Guided by Self-Regulated Learning Theory, this conceptual paper examines the ways in which AI is transforming mathematics education through a critical synthesis of recent literature, investigating its role in educational innovation, learner autonomy, and future learning practices. Drawing upon contemporary scholarship in artificial intelligence, mathematics education, and self-regulated learning, the paper posits that AI presents substantial opportunities for improving learning experiences and broadening access to educational support. However, an excessive reliance on AI may compromise independent thinking and learner agency if not implemented judiciously. The paper concludes that the educational value of AI is contingent upon its capacity to support self-regulated learning while preserving the reasoning, reflection, and problem-solving processes that are foundational to meaningful mathematical understanding.