1
Department of Management, Applied College, Jazan University, Jazan, Kingdom of Saudi Arabia
(abSalamai@jazanu.edu.sa)
Abstract :
Multiple schools’ alternatives are assessed by experts based on a wide range of factors, therefore evaluating school performance may be seen as a multiple criteria decision-making (MCDM) issue. In this research, we developed a MABAC approach for evaluating MCDM education's effectiveness under interval-valued neutrosophic sets, keeping in mind the constraints posed by the assessment setting's complexity and the psychological behaviour of experts. Before everything else, experts' opinions are included in the calculation of criterion weights. Next, a novel assessment framework for assessing academic achievement in schools is developed using the MABAC model. Our research aims to provide educational institutions with the tools they need to operate at peak efficiency. In addition, other schools and allied educational institutions may use the study's findings as a benchmark in their assessments, attempts to improve performance, and formulation of educational policy.
Keywords :
MCDM , Neutrosophic sets , Assessment , educational institutions , MABAC
References :
[1] H.-Y. Wu, J.-K. Chen, I.-S. Chen, and H.-H. Zhuo, “Ranking universities based on performance evaluation by a hybrid MCDM model,” Measurement, vol. 45, no. 5, pp. 856–880, 2012.
[2] N. C. Liu and Y. Cheng, “The academic ranking of world universities,” Higher education in Europe, vol. 30, no. 2, pp. 127–136, 2005.
[3] A. F. J. Van Raan, “Challenges in ranking of universities,” in Invited paper for the First International Conference on World Class Universities, Shanghai Jaio Tong University, Shanghai, 2005, pp. 133–143.
[4] J. Ioannidis et al., “International ranking systems for universities and institutions: a critical appraisal,” BMC medicine, vol. 5, no. 1, pp. 1–9, 2007.
[5] N. C. Liu, “The story of academic ranking of world universities,” International Higher Education, no. 54, 2009.
[6] G. A. Olcay and M. Bulu, “Is measuring the knowledge creation of universities possible?: A review of university rankings,” Technological Forecasting and Social Change, vol. 123, pp. 153–160, 2017.
[7] I. Aguillo, J. Bar-Ilan, M. Levene, and J. Ortega, “Comparing university rankings,” Scientometrics, vol. 85, no. 1, pp. 243–256, 2010.
[8] V. Halloin et al., Ranking universities. Editions de l’Université de Bruxelles, 2009.
[9] S. Marginson, “University rankings and social science,” European journal of education, vol. 49, no. 1, pp. 45–59, 2014.
[10] A. Alinezhad and J. Khalili, “MABAC Method,” in New Methods and Applications in Multiple Attribute Decision Making (MADM), Springer, 2019, pp. 193–198.
[11] R. Sun, J. Hu, J. Zhou, and X. Chen, “A hesitant fuzzy linguistic projection-based MABAC method for patients’ prioritization,” International Journal of Fuzzy Systems, vol. 20, no. 7, pp. 2144–2160, 2018.
[12] M. Zhao, G. Wei, X. Chen, and Y. Wei, “Intuitionistic fuzzy MABAC method based on cumulative prospect theory for multiple attribute group decision making,” International Journal of Intelligent Systems, vol. 36, no. 11, pp. 6337–6359, 2021.
[13] P. G. Altbach, “The globalization of college and university rankings,” Change: The magazine of higher learning, vol. 44, no. 1, pp. 26–31, 2012.
[14] S. Marginson, “Global university rankings: Implications in general and for Australia,” Journal of Higher Education Policy and Management, vol. 29, no. 2, pp. 131–142, 2007.
[15] R. Lukman, D. Krajnc, and P. Glavič, “University ranking using research, educational and environmental indicators,” Journal of cleaner production, vol. 18, no. 7, pp. 619–628, 2010.
[16] J. C. Shin and R. K. Toutkoushian, “The past, present, and future of university rankings,” in University rankings, Springer, 2011, pp. 1–16.
[17] S. Zhang, G. Wei, F. E. Alsaadi, T. Hayat, C. Wei, and Z. Zhang, “MABAC method for multiple attribute group decision making under picture 2-tuple linguistic environment,” Soft Computing, vol. 24, no. 8, pp. 5819–5829, 2020.
[18] H. Zhang, G. Wei, and X. Chen, “CPT-MABAC method for spherical fuzzy multiple attribute group decision making and its application to green supplier selection,” Journal of Intelligent & Fuzzy Systems, no. Preprint, pp. 1–11, 2021.
[19] A. R. Mishra, A. Chandel, and D. Motwani, “Extended MABAC method based on divergence measures for multi-criteria assessment of programming language with interval-valued intuitionistic fuzzy sets,” Granular Computing, vol. 5, no. 1, pp. 97–117, 2020.
[20] X. Peng and Y. Yang, “Pythagorean fuzzy Choquet integral based MABAC method for multiple attribute group decision making,” International Journal of Intelligent Systems, vol. 31, no. 10, pp. 989–1020, 2016.
[21] S. Luo and W. Liang, “Optimization of roadway support schemes with likelihood-based MABAC method,” Applied Soft Computing, vol. 80, pp. 80–92, 2019.
[22] D. Pamučar, I. Petrović, and G. Ćirović, “Modification of the Best–Worst and MABAC methods: A novel approach based on interval-valued fuzzy-rough numbers,” Expert systems with applications, vol. 91, pp. 89–106, 2018.
[23] W. Liang, G. Zhao, H. Wu, and B. Dai, “Risk assessment of rockburst via an extended MABAC method under fuzzy environment,” Tunnelling and Underground Space Technology, vol. 83, pp. 533–544, 2019.
[24] D. Pamučar, Ž. Stević, and E. K. Zavadskas, “Integration of interval rough AHP and interval rough MABAC methods for evaluating university web pages,” Applied soft computing, vol. 67, pp. 141–163, 2018.
[25] H. K. Sharma, R. Jagannath, S. Kar, and O. Prentkovskis, “Multi criteria evaluation framework for prioritizing indian railway stations using modified rough ahp-mabac method,” Transport and Telecommunication, vol. 19, no. 2, p. 113, 2018.
[26] G. Wei, Y. He, F. Lei, J. Wu, C. Wei, and Y. Guo, “Green supplier selection with an uncertain probabilistic linguistic MABAC method,” Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3125–3136, 2020.
[27] J. Gong, Q. Li, L. Yin, and H. Liu, “Undergraduate teaching audit and evaluation using an extended MABAC method under q‐rung orthopair fuzzy environment,” International Journal of Intelligent Systems, vol. 35, no. 12, pp. 1912–1933, 2020.
[28] G. Mester, “Academic Ranking of World Universities 2009/2010,” IPSI Journal, Transactions on Internet Research (TIR), vol. 7, no. 1, pp. 44–47, 2011.
[29] G. Buela-Casal, O. Gutiérrez-Martínez, M. P. Bermúdez-Sánchez, and O. Vadillo-Muñoz, “Comparative study of international academic rankings of universities,” Scientometrics, vol. 71, no. 3, pp. 349–365, 2007.
[30] P. Taylor and R. Braddock, “International university ranking systems and the idea of university excellence,” Journal of Higher Education Policy and Management, vol. 29, no. 3, pp. 245–260, 2007.
[31] S. S. Amsler and C. Bolsmann, “University ranking as social exclusion,” British journal of sociology of education, vol. 33, no. 2, pp. 283–301, 2012.
[32] R. Grewal, J. A. Dearden, and G. L. Llilien, “The university rankings game: Modeling the competition among universities for ranking,” The American Statistician, vol. 62, no. 3, pp. 232–237, 2008.
[33] F. Jia, Y. Liu, and X. Wang, “An extended MABAC method for multi-criteria group decision making based on intuitionistic fuzzy rough numbers,” Expert Systems with Applications, vol. 127, pp. 241–255, 2019.
[34] K. Shen, X. Wang, D. Qiao, and J. Wang, “Extended Z-MABAC method based on regret theory and directed distance for regional circular economy development program selection with Z-information,” IEEE Transactions on Fuzzy Systems, vol. 28, no. 8, pp. 1851–1863, 2019.
[35] G. Wei, C. Wei, J. Wu, and H. Wang, “Supplier selection of medical consumption products with a probabilistic linguistic MABAC method,” International Journal of Environmental Research and Public Health, vol. 16, no. 24, p. 5082, 2019.
[36] S. K. De and I. Beg, “Triangular dense fuzzy Neutrosophic sets,” Neutrosophic Sets and Systems, vol. 13, pp. 24–37, 2016.
[37] A. Chakraborty, S. P. Mondal, A. Ahmadian, N. Senu, S. Alam, and S. Salahshour, “Different forms of triangular neutrosophic numbers, de-neutrosophication techniques, and their applications,” Symmetry, vol. 10, no. 8, p. 327, 2018.
[38] S. A. Edalatpanah, “A direct model for triangular neutrosophic linear programming,” International journal of neutrosophic science, vol. 1, no. 1, pp. 19–28, 2020.
[39] S. K. Das and S. A. Edalatpanah, “A new ranking function of triangular neutrosophic number and its application in integer programming,” International Journal of Neutrosophic Science, vol. 4, no. 2, pp. 82–92, 2020.
[40] M. Mullai and R. Surya, “Neutrosophic inventory backorder problem using triangular neutrosophic numbers,” Neutrosophic Sets and Systems, vol. 31, pp. 148–155, 2020.
[41] M. Abdel-Basset, M. Mohamed, A.-N. Hussien, and A. K. Sangaiah, “A novel group decision-making model based on triangular neutrosophic numbers,” Soft Computing, vol. 22, no. 20, pp. 6629–6643, 2018.
[42] S. A. Edalatpanah, “Data envelopment analysis based on triangular neutrosophic numbers,” CAAI transactions on intelligence technology, vol. 5, no. 2, pp. 94–98, 2020.
| Style | # |
|---|---|
| MLA | Abdullah Ali Salamai. "An Assessment Model for Evaluating MCDM Education's Effectiveness Under Interval-Valued Neutrosophic Sets." Full Length Article, Vol. 1, No. 2, 2021 ,PP. 107-113 (Doi : https://doi.org/10.54216/JNFS.010207) |
| APA | Abdullah Ali Salamai. (2021). An Assessment Model for Evaluating MCDM Education's Effectiveness Under Interval-Valued Neutrosophic Sets. Journal of Full Length Article, 1 ( 2 ), 107-113 (Doi : https://doi.org/10.54216/JNFS.010207) |
| Chicago | Abdullah Ali Salamai. "An Assessment Model for Evaluating MCDM Education's Effectiveness Under Interval-Valued Neutrosophic Sets." Journal of Full Length Article, 1 no. 2 (2021): 107-113 (Doi : https://doi.org/10.54216/JNFS.010207) |
| Harvard | Abdullah Ali Salamai. (2021). An Assessment Model for Evaluating MCDM Education's Effectiveness Under Interval-Valued Neutrosophic Sets. Journal of Full Length Article, 1 ( 2 ), 107-113 (Doi : https://doi.org/10.54216/JNFS.010207) |
| Vancouver | Abdullah Ali Salamai. An Assessment Model for Evaluating MCDM Education's Effectiveness Under Interval-Valued Neutrosophic Sets. Journal of Full Length Article, (2021); 1 ( 2 ): 107-113 (Doi : https://doi.org/10.54216/JNFS.010207) |
| IEEE | Abdullah Ali Salamai, An Assessment Model for Evaluating MCDM Education's Effectiveness Under Interval-Valued Neutrosophic Sets, Journal of Full Length Article, Vol. 1 , No. 2 , (2021) : 107-113 (Doi : https://doi.org/10.54216/JNFS.010207) |