Towards a Comprehensive Decision Framework With Linguistic Neutrosophic Data

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.