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<p>The evaluation of higher education reform effectiveness assesses whether policy changes have improved teaching quality, research output, and graduate employability. Successful reforms enhance innovation, equity, and global rankings, while failures may lead to resource mismanagement or declining standards. Stakeholder feedback from students, teachers, and employers is crucial. Quantitative metrics (graduation rates, research citations) and qualitative analysis (pedagogical innovation, industry relevance) are combined for a comprehensive review. Challenges include balancing academic freedom with standardization and ensuring sustainable funding. Ultimately, effective reforms should align education with societal needs and technological advancements. The evaluation of higher education reform effectiveness is fundamentally a multi-attribute decision-making problem that requires processing substantial uncertain and ambiguous information. To address this challenge, this study innovatively proposes an integrated evaluation method based on Double-Valued Neutrosophic Number Logarithmic Distance (DVNNLD). At the methodological level, this research achieves three significant breakthroughs: First, it creatively combines the CRITIC (Criteria Importance Through Intercriteria Correlation) objective weighting method with an improved CoCoSo method (Combined Compromise Solution) decision-making approach to construct the DVNN-CoCoSo evaluation model. This model effectively captures the fuzziness and uncertainty characteristics in expert judgments through double-valued neutrosophic numbers. Second, it introduces logarithmic distance measures to handle nonlinear relationships among evaluation indicators, significantly enhancing the model's capability to process complex educational data. Finally, the method's applicability in higher education reform evaluation is validated through practical case studies. The study reveals that compared to traditional evaluation methods, the DVNN-CoCoSo model demonstrates three major advantages: (1) more accurate reflection of the multidimensional characteristics of educational reforms; (2) stronger analytical capability for uncertain information; and (3) more discriminative and interpretable evaluation results. Two noteworthy limitations were also identified during the research: the model's relatively high computational complexity and its stringent requirements for data quality. Through theoretical innovation and empirical validation, this study provides a new methodological tool for evaluating higher education reform effectiveness. The research outcomes not only enrich educational evaluation theory but also offer scientific foundations for policymakers to formulate reform plans. Future research could further optimize algorithm efficiency and expand the model's application to other educational assessment scenarios.</p>

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Advanced CoCoSo technique based on logarithmic distance for double-valued neutrosophic multiple-attribute decision-making: applications to higher education reform effectiveness evaluation

  • 期刊论文

  • 发表日期：

    2026年3月17日

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  • Min Sun,
  • Li Che,
  • Lin Li

摘要

The evaluation of higher education reform effectiveness assesses whether policy changes have improved teaching quality, research output, and graduate employability. Successful reforms enhance innovation, equity, and global rankings, while failures may lead to resource mismanagement or declining standards. Stakeholder feedback from students, teachers, and employers is crucial. Quantitative metrics (graduation rates, research citations) and qualitative analysis (pedagogical innovation, industry relevance) are combined for a comprehensive review. Challenges include balancing academic freedom with standardization and ensuring sustainable funding. Ultimately, effective reforms should align education with societal needs and technological advancements. The evaluation of higher education reform effectiveness is fundamentally a multi-attribute decision-making problem that requires processing substantial uncertain and ambiguous information. To address this challenge, this study innovatively proposes an integrated evaluation method based on Double-Valued Neutrosophic Number Logarithmic Distance (DVNNLD). At the methodological level, this research achieves three significant breakthroughs: First, it creatively combines the CRITIC (Criteria Importance Through Intercriteria Correlation) objective weighting method with an improved CoCoSo method (Combined Compromise Solution) decision-making approach to construct the DVNN-CoCoSo evaluation model. This model effectively captures the fuzziness and uncertainty characteristics in expert judgments through double-valued neutrosophic numbers. Second, it introduces logarithmic distance measures to handle nonlinear relationships among evaluation indicators, significantly enhancing the model's capability to process complex educational data. Finally, the method's applicability in higher education reform evaluation is validated through practical case studies. The study reveals that compared to traditional evaluation methods, the DVNN-CoCoSo model demonstrates three major advantages: (1) more accurate reflection of the multidimensional characteristics of educational reforms; (2) stronger analytical capability for uncertain information; and (3) more discriminative and interpretable evaluation results. Two noteworthy limitations were also identified during the research: the model's relatively high computational complexity and its stringent requirements for data quality. Through theoretical innovation and empirical validation, this study provides a new methodological tool for evaluating higher education reform effectiveness. The research outcomes not only enrich educational evaluation theory but also offer scientific foundations for policymakers to formulate reform plans. Future research could further optimize algorithm efficiency and expand the model's application to other educational assessment scenarios.