Application of Multi-Criteria Decision-Making Models for Assessment of Education Quality in Water Resources Engineering - Mohammad Kazem Ghorbani; Nasser Talebbeydokhti; Hossein Hamidifar; Mehrshad Samadi; Michael Nones; Fatemeh Rezaeitavabe; Shabnam Heidarifar (Algorithms)
Assessing and improving the quality of education in universities can play a prominent role in developing countries. This study aims to demonstrate an extensive methodology with a related algorithm for assessing the quality of education in Water Resource Engineering (WRE) based on Klein’s learning model and using the hybrid fuzzy-AHP-TOPSIS (FAT) method. Four out of the top ten universities in Iran, including Iran University of Science and Technology (IUST), Amirkabir University of Technology (AUT), Shiraz University (SU), and Khajeh Nasir al-Din Toosi University of Technology (KUT), are considered as case studies. First, participants answered questions based on Klein’s model so that the weight coefficients according to the fuzzy-AHP technique were extracted. Second, these coefficients were transferred to the TOPSIS environment, where the previously prioritized criteria were utilized to select the ideal solution. Finally, the relative closeness of universities (CC) as a performance evaluation criterion in the form of CC(IUST) = 0.54, CC(AUT) = 0.49, CC(SU) = 0.45, and CC(KUT) = 0.39 was obtained. The sensitivity analysis was performed based on the number and type of Klein’s qualitative criteria on the model, and Fourier series expansion curves were used to better compare the results of the proposed algorithm. The presented algorithm in this research can be a good basis for education assessment models in universities.