Probabilistic Uncertain Linguistic VIKOR Method for Teaching Reform Plan Evaluation for the Core Course “Big Data Technology and Applications” in the Digital Economy Major

Wenshuai Wu ()
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Wenshuai Wu: Lingnan College, Sun Yat-sen University, Guangzhou 510275, China

Mathematics, 2024, vol. 12, issue 23, 1-18

Abstract: The reform of the teaching plan for the core course “big data technology and applications” in the digital economy major has become a globally recognized challenge. Qualitative data, fuzzy and uncertain information, a complex decision-making environment, and various impact factors create significant difficulties in formulating effective responses to teaching reform plans. Therefore, the objective of this paper is to develop a precision evaluation technology for teaching reform plans in the core course “big data technology and applications”, to address the challenges of uncertainty and fuzziness in complex decision-making environments. In this study, an extended VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) method based on a probabilistic uncertain linguistic term set (PULTS), which is presented for teaching reform plan evaluation. The extended probabilistic uncertain linguistic VIKOR method can effectively and accurately capture the fuzziness and uncertainty of complex decision-making processes. In addition, PULTS is integrated into the VIKOR method to express decision-makers’ fuzzy language preference information in terms of probability. A case study is conducted to verify and test the extended method, and the research results demonstrate that it is highly effective for decision-making regarding teaching reform plans to foster the high-quality development of education, especially in uncertain and fuzzy environments. Furthermore, parameter and comparative analyses verify the effectiveness of the extended method. Finally, the paper outlines directions for future research.

Keywords: teaching reform plan evaluation; probabilistic uncertain linguistic term set; VIKOR; course; digital economy (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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