From Exploration to Efficiency? Examining the Impact of Generative AI on Mathematical Thinking and Agency in K-12 Mathematics Education

Keyu Chen

European Journal of Education Science, 2026, vol. 2, issue 2, 10-19

Abstract: Generative Artificial Intelligence (GAI) is rapidly transforming teaching and learning practices in K-12 education. While these technologies provide students with immediate access to explanations, solutions, and personalized support, they also raise concerns about the nature of learning itself. This paper first reviews the current application of generative AI in K-12 mathematics education and then examines three related shifts in students' learning: from concept understanding to answer acquisition, from process exploration to task completion, and from sustained thinking to efficiency-oriented learning. In response, it proposes a student-centered framework that positions AI as a scaffold for concept interpretation and answer verification, open-ended inquiry and human-AI dialogue, and productive cognitive engagement supported by hierarchical prompts and delayed feedback. The paper further discusses how curriculum design, classroom practice, and future research can support the responsible use of generative AI while preserving students' mathematical thinking, learning agency, and conceptual understanding. By synthesizing existing literature and offering a theoretically grounded framework, this review aims to guide educators and policymakers in harnessing the potential of GAI without compromising the depth and authenticity of mathematical learning experiences.

Keywords: generative artificial intelligence; mathematics education; k-12 education; student-centered learning; educational technology (search for similar items in EconPapers)
Date: 2026
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