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Towards a Comprehensive Decision Framework With Linguistic Neutrosophic Data: GRA-Based Combined Approach to Technology-Enabled General High School Education Quality Evaluation
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Author(s): Jisheng Shi (School of Education, Huanggang Normal University, Huanggang, China)and Yunying He (School of Foreign Languages, Hezhou University, Hezhou, China)
Copyright: 2026
Volume: 17
Issue: 1
Pages: 17
Source title:
International Journal of Information System Modeling and Design (IJISMD)
Editor(s)-in-Chief: Thierry O. C. Edoh (RFW-Universtät Bonn, (RFW University of Bonn), Bonn/Germany & Ecole Supérieure Multinationale des Telecomunications, Dakar/Senegal)
DOI: 10.4018/IJISMD.399502
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Abstract
High school education quality assessment holistically evaluates student development, teaching effectiveness, and curriculum implementation. It integrates academic performance with core competencies like critical thinking. This comprehensive process involves multiple stakeholders to inform school improvement and ensure education aligns with broader developmental goals for every learner. The technology-enabled general high school education quality evaluation is multiple attribute group decision making (MAGDM). In this paper, the 2-tuple linguistic neutrosophic number (2TLNN) grey relational analysis (GRA) method (2TLNN-GRA) is constructed based on GRA and 2-tuple linguistic neutrosophic sets (2TLNSs). The 2TLNN-GRA method is constructed for solving the MAGDM problem. Finally, the numerical example for technology-enabled general high school education quality evaluation is constructed with some comparative analysis.
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