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Purpose <p>This study examines how artificial intelligence (AI) tools influence learners’ interest, performance, and perceptions in mathematics and identifies contextual factors shaping their impact in Ghanaian classrooms.</p> Method <p>A cross-sectional survey design was employed, utilizing a structured questionnaire to assess learners’ interest, performance, perceptions of mathematics, and AI use. Quantitative data were analysed with Structural Equation Modeling in AMOS (v.23) to estimate the effects of AI on outcome variables.</p> Findings <p>AI use showed statistically significant positive effects on learners’ interest (β = 0.644, <i>p</i> &lt; 0.01), academic performance (β = 0.416, <i>p</i> &lt; 0.01), and perceptions of learning mathematics (β = 0.587, <i>p</i> &lt; 0.01). AI-supported environments enabled more personalised instruction and timely feedback. However, unequal access to devices, unreliable internet connectivity, and limited school resources emerged as major constraints on effective implementation.</p> Implications <p>The findings provide empirical evidence to guide technology-enhanced mathematics education in resource-constrained contexts. They highlight the need for policies and school-level strategies that promote equitable access to AI tools, teacher professional development, and curriculum alignment so that AI is integrated as a pedagogical resource. These insights are relevant to educators, policymakers, and curriculum developers seeking to harness AI’s potential to meaningfully improve mathematics teaching and learning.</p>

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Artificial intelligence impacts learners’ mathematics interest performance and perception

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月17日

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  • Peter Yeribatuah,
  • Francis Ohene Boateng

摘要

Purpose

This study examines how artificial intelligence (AI) tools influence learners’ interest, performance, and perceptions in mathematics and identifies contextual factors shaping their impact in Ghanaian classrooms.

Method

A cross-sectional survey design was employed, utilizing a structured questionnaire to assess learners’ interest, performance, perceptions of mathematics, and AI use. Quantitative data were analysed with Structural Equation Modeling in AMOS (v.23) to estimate the effects of AI on outcome variables.

Findings

AI use showed statistically significant positive effects on learners’ interest (β = 0.644, p < 0.01), academic performance (β = 0.416, p < 0.01), and perceptions of learning mathematics (β = 0.587, p < 0.01). AI-supported environments enabled more personalised instruction and timely feedback. However, unequal access to devices, unreliable internet connectivity, and limited school resources emerged as major constraints on effective implementation.

Implications

The findings provide empirical evidence to guide technology-enhanced mathematics education in resource-constrained contexts. They highlight the need for policies and school-level strategies that promote equitable access to AI tools, teacher professional development, and curriculum alignment so that AI is integrated as a pedagogical resource. These insights are relevant to educators, policymakers, and curriculum developers seeking to harness AI’s potential to meaningfully improve mathematics teaching and learning.