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<p>Vocational colleges must practically integrate innovation and entrepreneurship education (IAEE) with skill training, leveraging their strengths to build tailored talent systems. However, current setups remain underdeveloped and uniform—student engagement is low, teaching lacks coherence, competition entries lack feasibility, and even rising participation yields few impactful results. Assessing IAEE quality in vocational education is a complex multiple-attribute decision-making (MADM) challenge. Recent studies have adopted Exponential TODIM (ExpTODIM) and EDAS for MADM, but IAEE evaluations involve inherent uncertainty (e.g., vague feedback on teaching effectiveness or ambiguous judging criteria). Z-numbers address this by pairing numerical values with reliability measures, making them ideal for capturing unclear assessment data. This study introduces an integrated Z-number-based Exponential TODIM-EDAS (ZN-ExpTODIM-EDAS) approach. First, it uses Z-numbers to quantify uncertain IAEE quality indicators (e.g., curriculum relevance, student innovation output). Then, ExpTODIM calculates the dominance degree of each assessment object by considering decision-makers’ risk preferences, while EDAS evaluates alternatives via positive/negative distance from the average solution. The combination mitigates limitations of single methods—ExpTODIM’s sensitivity to risk and EDAS’s reliance on average values. To validate this methodology, a practical case study on IAEE quality assessment in three vocational colleges is presented. It collects data from educators, industry experts, and student projects, applies ZN-ExpTODIM-EDAS to rank IAEE quality, and compares results with traditional ExpTODIM/EDAS. The consistency and accuracy of the integrated method confirm its applicability and effectiveness for IAEE quality evaluation.</p>

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Combined Framework for Fuzzy Multiple-Attribute Decision-Making Under Z-Number Environment and Applications to Quality Evaluation of Innovation and Entrepreneurship Education in Vocational Colleges

  • 期刊论文

  • 发表日期：

    2026年6月15日

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  • Leilei Dong

摘要

Vocational colleges must practically integrate innovation and entrepreneurship education (IAEE) with skill training, leveraging their strengths to build tailored talent systems. However, current setups remain underdeveloped and uniform—student engagement is low, teaching lacks coherence, competition entries lack feasibility, and even rising participation yields few impactful results. Assessing IAEE quality in vocational education is a complex multiple-attribute decision-making (MADM) challenge. Recent studies have adopted Exponential TODIM (ExpTODIM) and EDAS for MADM, but IAEE evaluations involve inherent uncertainty (e.g., vague feedback on teaching effectiveness or ambiguous judging criteria). Z-numbers address this by pairing numerical values with reliability measures, making them ideal for capturing unclear assessment data. This study introduces an integrated Z-number-based Exponential TODIM-EDAS (ZN-ExpTODIM-EDAS) approach. First, it uses Z-numbers to quantify uncertain IAEE quality indicators (e.g., curriculum relevance, student innovation output). Then, ExpTODIM calculates the dominance degree of each assessment object by considering decision-makers’ risk preferences, while EDAS evaluates alternatives via positive/negative distance from the average solution. The combination mitigates limitations of single methods—ExpTODIM’s sensitivity to risk and EDAS’s reliance on average values. To validate this methodology, a practical case study on IAEE quality assessment in three vocational colleges is presented. It collects data from educators, industry experts, and student projects, applies ZN-ExpTODIM-EDAS to rank IAEE quality, and compares results with traditional ExpTODIM/EDAS. The consistency and accuracy of the integrated method confirm its applicability and effectiveness for IAEE quality evaluation.