Artificial Intelligence Integration in Mathematics Education: A SWOT-BWM Analysis

Abstract

The rapid advancement of artificial intelligence (AI) and its accessibility to almost everyone necessitate a clear definition of its role in education. The primary step in effectively integrating AI into mathematics education (ME) is formulating instructional strategies that consider its advantages and disadvantages. This study aims to develop strategic recommendations for integrating AI into ME by utilizing SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis and the Best-Worst Method (BWM). A SWOT analysis of studies on the use of AI in mathematics education was conducted, and a group of 19 mathematics education experts evaluated these criteria through a paired comparison method. The data was analyzed through BWM to determine the impact level of the criteria, and a SWOT matrix was created to develop key strategies to optimize the role of AI in ME. Strategic recommendations include leveraging AI for personalized learning, integrating AI-driven teaching models, and ensuring that AI complements rather than replaces teacher-student interactions. The findings emphasize the necessity of AI literacy for both educators and students in mitigating its drawbacks. By providing a structured framework for assessing AI’s impact and proposing actionable strategies for its effective implementation in ME, this study contributes to the ongoing discourse on AI in education.

Keywords

• artificial intelligence
• SWOT analysis
• BWM
• mathematics education

References

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