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<p>Traditional evaluation methods struggle to handle the ambiguity and dynamism inherent in the quality of children’s art education, thereby limiting its scientific rigor and practical applicability. To address these limitations, we propose an improved Fuzzy Analytic Hierarchy Process (FAHP) model for dynamic and systematic evaluation, overcoming the static and fragmented nature of traditional approaches. We established an evaluation system comprising 5 first-level and 15&#xa0;s-level indicators by integrating LR-type (Left-Right) triangular fuzzy numbers, a three-point scale method, and a dynamic weight mechanism, the evaluation system consisting of 5 first-level indexes and 15&#xa0;s-level indexes is established. Empirical evidence shows that the correlation coefficient between the model and expert consensus reaches 0.92, demonstrating high cross-cultural stability (standard deviation of 0.03). In addition, the deviation rate is only 5.1% when data is missing, and compared to the baseline level, it has increased by 38.5%. This study provides a standardized tool for global art education quality evaluation that combines precision, efficiency, and robustness.</p>

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Analysis of the influencing factors of children’s art education quality based on fuzzy analytic hierarchy process

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月18日

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  • Zhiqiang Zhang

摘要

Traditional evaluation methods struggle to handle the ambiguity and dynamism inherent in the quality of children’s art education, thereby limiting its scientific rigor and practical applicability. To address these limitations, we propose an improved Fuzzy Analytic Hierarchy Process (FAHP) model for dynamic and systematic evaluation, overcoming the static and fragmented nature of traditional approaches. We established an evaluation system comprising 5 first-level and 15 s-level indicators by integrating LR-type (Left-Right) triangular fuzzy numbers, a three-point scale method, and a dynamic weight mechanism, the evaluation system consisting of 5 first-level indexes and 15 s-level indexes is established. Empirical evidence shows that the correlation coefficient between the model and expert consensus reaches 0.92, demonstrating high cross-cultural stability (standard deviation of 0.03). In addition, the deviation rate is only 5.1% when data is missing, and compared to the baseline level, it has increased by 38.5%. This study provides a standardized tool for global art education quality evaluation that combines precision, efficiency, and robustness.