Application of Multi-Criteria Decision-Making Models for Assessment of Education Quality in Water Resources Engineering

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 mo...

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Main Authors: Mohammad Kazem Ghorbani, Nasser Talebbeydokhti, Hossein Hamidifar, Mehrshad Samadi, Michael Nones, Fatemeh Rezaeitavabe, Shabnam Heidarifar
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Algorithms
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Online Access:https://www.mdpi.com/1999-4893/18/1/12
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author Mohammad Kazem Ghorbani
Nasser Talebbeydokhti
Hossein Hamidifar
Mehrshad Samadi
Michael Nones
Fatemeh Rezaeitavabe
Shabnam Heidarifar
author_facet Mohammad Kazem Ghorbani
Nasser Talebbeydokhti
Hossein Hamidifar
Mehrshad Samadi
Michael Nones
Fatemeh Rezaeitavabe
Shabnam Heidarifar
author_sort Mohammad Kazem Ghorbani
collection DOAJ
description 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.
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spelling doaj-art-ddcb698458084300b83d2750868992e62025-01-24T13:17:27ZengMDPI AGAlgorithms1999-48932025-01-011811210.3390/a18010012Application of Multi-Criteria Decision-Making Models for Assessment of Education Quality in Water Resources EngineeringMohammad Kazem Ghorbani0Nasser Talebbeydokhti1Hossein Hamidifar2Mehrshad Samadi3Michael Nones4Fatemeh Rezaeitavabe5Shabnam Heidarifar6School of Civil Engineering, Iran University of Science and Technology, Tehran 16846, IranDepartment of Civil and Environmental Engineering, School of Engineering, Shiraz University, Shiraz 71348, IranDepartment of Hydrology and Hydrodynamics, Institute of Geophysics, Polish Academy of Sciences, 01-452 Warsaw, PolandSchool of Civil Engineering, Iran University of Science and Technology, Tehran 16846, IranDepartment of Hydrology and Hydrodynamics, Institute of Geophysics, Polish Academy of Sciences, 01-452 Warsaw, PolandDepartment of Civil and Environmental Engineering, Ohio University, Athens, OH 45701, USADepartment of Civil and Environmental Engineering, School of Engineering, Shiraz University, Shiraz 71348, IranAssessing 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.https://www.mdpi.com/1999-4893/18/1/12multi-criteria decision-makingfuzzy-AHP-TOPSIS methodKlein’s pattern
spellingShingle Mohammad Kazem Ghorbani
Nasser Talebbeydokhti
Hossein Hamidifar
Mehrshad Samadi
Michael Nones
Fatemeh Rezaeitavabe
Shabnam Heidarifar
Application of Multi-Criteria Decision-Making Models for Assessment of Education Quality in Water Resources Engineering
Algorithms
multi-criteria decision-making
fuzzy-AHP-TOPSIS method
Klein’s pattern
title Application of Multi-Criteria Decision-Making Models for Assessment of Education Quality in Water Resources Engineering
title_full Application of Multi-Criteria Decision-Making Models for Assessment of Education Quality in Water Resources Engineering
title_fullStr Application of Multi-Criteria Decision-Making Models for Assessment of Education Quality in Water Resources Engineering
title_full_unstemmed Application of Multi-Criteria Decision-Making Models for Assessment of Education Quality in Water Resources Engineering
title_short Application of Multi-Criteria Decision-Making Models for Assessment of Education Quality in Water Resources Engineering
title_sort application of multi criteria decision making models for assessment of education quality in water resources engineering
topic multi-criteria decision-making
fuzzy-AHP-TOPSIS method
Klein’s pattern
url https://www.mdpi.com/1999-4893/18/1/12
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