A Novel Integrated Picture Fuzzy MACONT Method and Its Application in Teaching Quality Evaluation in Higher Education

Teachers' teaching quality evaluation is an important means of teaching quality management in higher education. It is of great significance to improve teachers' teaching ability and the overall quality of personnel training. This study aims to propose a novel integrated picture fuzzy multi-criteria decision-making method (MCDM) to assess teaching quality in higher education. MCDM is an efficient analytical tool to rank alternatives according to multiple evaluation criteria. As an extension of intuitionistic fuzzy sets, picture fuzzy sets, which include four membership functions, have distinct superiority in addressing neutral and non-participating situations. Hence, the study introduces picture fuzzy sets theory to capture fuzzy evaluation information and integrates it with a grey system theory-based model for objective criteria weighting and an expert grading approach for subjective weighting. Furthermore, the mixed aggregation by comprehensive normalization technique for multi-criteria analysis (MACONT) is extended to sort alternatives in picture fuzzy environments. It is a novel MCDM to get reliable evaluation results with different normalization operations. When using the modified MACONT, picture fuzzy evaluation information is addressed with three types of normalization techniques to reduce deviations. Thereafter, a practical case study of teaching quality evaluation in a higher education institution demonstrates the application and feasibility of the proposed framework. Last, sensitivity and comparison analyses highlight the robustness and flexibility of our approach compared to traditional methods. The results indicate that our method is effective in accurately evaluating teaching quality and can serve as a valuable tool for educational institutions.