Building a Ranking System for Lecturers Based on Student Evaluations in Teaching a Specific Course: A Case Study at a University in Vietnam
DOI:
https://doi.org/10.23947/2334-8496-2024-12-2-335-350Keywords:
Lecturers ranking, MCDM, PSI, SRP, RAM, PIVAbstract
In the current landscape of higher education, the quality of teaching plays a crucial role in supporting the comprehensive development of students. To ensure the effectiveness of the learning process, evaluating lecturers based on student opinions is an essential means of providing feedback and optimizing the learning experience. This paper focuses on constructing a lecturer ranking system, particularly in the context of a specific course through the evaluation process from students. Four different methods were employed to assess lecturers, including the PSI method, SRP method, RAM method, and PIV method. The evaluation results using these four methods were compared with each other and also with the traditional evaluation approach currently utilized in the educational institution. The achieved results demonstrate that the approach outlined in this paper is highly suitable for determining the rankings of lecturers when teaching individual courses.
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Akmaludin, A., Gernaria E., S., Rinawati, R., Arisawati, E., & Dewi, L., S. (2023). Decision Support for Selection of The Best Teachers Recommendations MCDM-AHP and ARAS Collaborative Methods. Sinkron: Jurnal dan Penelitian Teknik Informatika, 8(4), 2036-2048. https://doi.org/10.33395/sinkron.v8i4.12354 DOI: https://doi.org/10.33395/sinkron.v8i4.12354
Arifin, N., & Saputro, P. H. (2022). Selection Index (PSI) Method in Developing a Student Scholarship Decision Support System. International Journal of Computer and Information System, 3(1), 12-16 DOI: https://doi.org/10.29040/ijcis.v3i1.55
Ayyildiz, E., Murat, M., Imamoglu, G., & Kose, Y. (2023). A novel hybrid MCDM approach to evaluate universities based on student perspective. Scientometrics, 128, 55-86. https://doi.org/10.1007/s11192-022-04534-z DOI: https://doi.org/10.1007/s11192-022-04534-z
Bafail, O., A., Abdulaal, R., M., S., & Kabli, M., R. (2022). AHP-RAPS Approach for Evaluating the Productivity of Engineering Departments at a Public University. Systems, 10(107). https://doi.org/10.3390/systems10040107 DOI: https://doi.org/10.3390/systems10040107
Do, D. T. (2024). Assessing the Impact of Criterion Weights on the Ranking of the Top Ten Universities in Vietnam. Engineering, Technology & Applied Science Research, 14(4), 14899-14903. https://doi.org/10.48084/etasr.7607 DOI: https://doi.org/10.48084/etasr.7607
Do, D., T., Tran, V., D., Duong, V., D., & Nguyen, N., T. (2023). Investigation of the appropriate data normalization method for combination with Preference Selection Index method in MCDM. Operational Research in Engineering Sciences: Theory and Applications, 6(1), 44-64. https://oresta.org/menu-script/index.php/oresta/article/view/329
Dragisa, S., Darjan, K., & Gabrijela, P. (2021). Ranking alternatives using PIPRECIA method: A case of hotels’ website evaluation. Journal of Process Management and New Technologies, 9(3-4), 62-68. https://doi.org/10.5937/jouproman2103062S DOI: https://doi.org/10.5937/jouproman2103062S
Dua, T. V. (2024). PSI-SAW and PSI-MARCOS Hybrid MCDM Methods. Engineering, Technology & Applied Science Research, 14(4), 15963-15968. https://doi.org/10.48084/etasr.7992 DOI: https://doi.org/10.48084/etasr.7992
Dua, T. V., Duc, D. V., Bao, N. C., & Trung, D. D. (2024). Integration of objective weighting methods for criteria and MCDM methods: application in material selection. EUREKA: Physics and Engineering, 2, 131–148. https://doi.org/10.21303/2461-4262.2024.003171 DOI: https://doi.org/10.21303/2461-4262.2024.003171
Ecer, F., & Pamucar, D. (2022). A novel LOPCOW-DOBI multi-criteria sustainability performance assessment methodology: An application in developing country banking sector. Omega, 112, Art. No. 102690. https://doi.org/10.1016/j.omega.2022.102690 DOI: https://doi.org/10.1016/j.omega.2022.102690
Ekinci, Y., Orbay, B.Z., & Karadayi, M. A. (2022). An MCDM-based game-theoretic approach for strategy selection in higher education. Socio-Economic Planning Sciences, 81, 101186. https://doi.org/10.1016/j.seps.2021.101186 DOI: https://doi.org/10.1016/j.seps.2021.101186
Ghorui, N., Ghosh, A., Mondal, S. P., Kumari, S., Jana, S., & Das, A. (2021). Evaluation Of Performancefor School Teacher Recruitment Using MCDM Techniques With Interval Data. Multicultural Education, 7(5), 380-395. https://doi.org/10.5281/zenodo.4837226
Girvan, C. Conneely, C., & Tangney, B. (2016). Extending experiential learning in teacher professional development. Teaching and Teacher Education, 58, 129-139. https://doi.org/10.1016/j.tate.2016.04.009 DOI: https://doi.org/10.1016/j.tate.2016.04.009
Ha, L., D. (2023). Selection of Suitable Data Normalization Method to Combine With the CRADIS Method for Making Multi-Criteria Decision. Applied Engineering Letters, 8(1), 24-35. https://doi.org/10.18485/aeletters.2023.8.1.4 DOI: https://doi.org/10.18485/aeletters.2023.8.1.4
Hoang, X., T. (2023). Multi-objective optimization of turning process by FUCA method. Strojnícky časopis - Journal of Mechanical Engineering, 73(1), 55-66. https://doi.org/10.2478/scjme-2023-0005 DOI: https://doi.org/10.2478/scjme-2023-0005
Kalyan, M., & Pramanik. S. (2019). Multi-criteria Group Decision Making Approach for Teacher Recruitment in Higher Education under Simplified Neutrosophic Environment. Neutrosophic Sets and Systems, 6, 28-34.
Komasi, H., Nemati, A., Hashemkhani Zolfani, S., Williams, N. L., & Bazrafshan, R. (2024). Investigating the effects of COVID-19 on tourism in the G7 countries. Technological and Economic Development of Economy, 30(4), 1064–1086. https://doi.org/10.3846/tede.2024.20821 DOI: https://doi.org/10.3846/tede.2024.20821
Le, H. A., Hoang, X. T., Trieu, Q. H., Pham, D. L., & Le, X. H. (2022). Determining the Best Dressing Parameters for External Cylindrical Grinding Using MABAC Method. Applied scicences, 12(16), 8287. https://doi.org/10.3390/app12168287 DOI: https://doi.org/10.3390/app12168287
Malik, D. A. A., Yusof, Y., & Khalif, K. M. N. K. (2021). A view of MCDM application in education. Journal of Physics: Conference Series, 1988, 012063. https://doi.org/10.1088/1742-6596/1988/1/012063 DOI: https://doi.org/10.1088/1742-6596/1988/1/012063
Maniya, K., & Bhatt, M.G. (2010). A selection of material using a novel type decisionmaking method: Preference selection index method. Materials & Design, 31(4), 1785-1789. https://doi.org/10.1016/j.matdes.2009.11.020 DOI: https://doi.org/10.1016/j.matdes.2009.11.020
Mian, S. H., Nasr, E. A., Moiduddin, K., Saleh, M., Abidi, M. H., & Alkhalefah, H. (2024). Assessment of consolidative multi-criteria decision making (C-MCDM) algorithms for optimal mapping of polymer materials in additive manufacturing: A case study of orthotic application. Heliyon, 10, Art. No. e30867. https://doi.org/10.1016/j.heliyon.2024.e30867 DOI: https://doi.org/10.1016/j.heliyon.2024.e30867
Monalisa, R., & Kusnawi, K. (2017). Decision support system of model teacher selection using PROMETHEE method. International Conference on Innovative and Creative Information Technology (ICITech). https://doi.org/10.1109/INNOCIT.2017.8319147 DOI: https://doi.org/10.1109/INNOCIT.2017.8319147
Mufazzal, S., & Muzakkir, S., (2018). A New Multi-Criterion Decision Making (MCDM) Method Based on Proximity Indexed Value for Minimizing Rank Reversals. Computers & Industrial Engineering, 119, 427-438. https://doi.org/10.1016/j.cie.2018.03.045 DOI: https://doi.org/10.1016/j.cie.2018.03.045
Munna, A. S., & Kalam, M. A. (2021). Teaching and learning process to enhance teaching effectiveness: a literature review. International Journal of Humanities and Innovation (IJHI), 4(1), 1-4. https://doi.org/10.33750/ijhi.v4i1.102 DOI: https://doi.org/10.33750/ijhi.v4i1.102
Nguyen, H. S., Hieu, T. T., Thang, N. M., Tan, H. N., Can, N. T., Thao, P. T., & Bao, N. C. (2024). Selection of Crankshaft Manufacturing Material by the PIV Method. Engineering, Technology & Applied Science Research, 14(4), 14848-14853. https://doi.org/10.48084/etasr.7514 DOI: https://doi.org/10.48084/etasr.7514
Oliver, R. M., & Reschly, D. J. (2007). Effective Classroom Management: Teacher Preparation and Professional Development, National Comprehensive Center for Teacher Quality, Washington, USA.
Sirigiri, P., Hota, H.,S., & Sharma, L., K. (2015). Students Performance Evaluation using MCDM Methods through Customized Software. International Journal of Computer Applications, 130(15), 11-14. https://doi.org/10.5120/ijca2015907171 DOI: https://doi.org/10.5120/ijca2015907171
Sotoudeh-Anvari, A. (2023). Root Assessment Method (RAM): A novel multi-criteria decision making method and its applications in sustainability challenges. Journal of Cleaner Production, 423, Art. No. 138695. https://doi.org/10.1016/j.jclepro.2023.138695 DOI: https://doi.org/10.1016/j.jclepro.2023.138695
Thinh, H. X., & Mai, N. T. (2023). Comparison of two methods in multi-criteria decision-making: application in transmission rod material selection. EUREKA: Physics and Engineering, 6, 59–68. https://doi.org/10.21303/2461-4262.2023.003046 DOI: https://doi.org/10.21303/2461-4262.2023.003046
Thinh, H., X. & Dua, T. V. (2024). Optimal Surface Grinding Regression Model Determination with the SRP Method. Engineering, Technology & Applied Science Research, 14(3), 14713-14718. https://doi.org/10.48084/etasr.7573 DOI: https://doi.org/10.48084/etasr.7573
Toan, P., N., Dang, T., T., & Hong, L., T., T. (2021). E-Learning Platform Assessment and Selection Using Two-Stage Multi-Criteria Decision-Making Approach with Grey Theory: A Case Study in Vietnam. Mathematics, 9(23), Art.No. 3136. https://doi.org/10.3390/math9233136 DOI: https://doi.org/10.3390/math9233136
Trung, D. D., & Tung, N. N. (2022). Applying COCOSO, MABAC, MAIRCA, EAMR, TOPSIS and weight determination methods for multi-criteria decision making in hole turning process. Strojnícky časopis - Journal of Mechanical Engineering, 72(2), 15-40. https://doi.org/10.2478/scjme-2022-0014 DOI: https://doi.org/10.2478/scjme-2022-0014
Trung, D. D., Dudić, B., Duc, D. V., Son, N. H. & Ašonja, A. (2024). Comparison of MCDM methods effectiveness in the selection of plastic injection molding machines. Teknomekanik, 7(1), 1-19. https://doi.org/10.24036/teknomekanik.v7i1.29272 DOI: https://doi.org/10.24036/teknomekanik.v7i1.29272
Trung, D. D., Dudić, B., Dung, H. T., & Truong, N. X. (2024). Innovation in financial health assessment: Applying MCDM techniques to banks in VIETNAM. ECONOMICS - Innovative and Economics Research Journal, 12(2). https://doi.org/10.2478/eoik-2024-0011 DOI: https://doi.org/10.2478/eoik-2024-0011
Trung, D. D., Duc, D. V., Bao, N. C., & Thuy, D. T. T. (2024). Using the root assessment method to choose the optimal solution for mushroom cultivation. Yugoslav Journal of Operations Research. https://doi.org/10.2298/YJOR240115007T DOI: https://doi.org/10.2298/YJOR240115007T
Trung, D. D., Dudić, B., Nguyen, N. T., & Ašonja, A. (2024). Data Normalization for Root Assessment Methodology. International Journal of Industrial Engineering and Management, 15(2), 156-168. https://doi.org/10.24867/IJIEM-2024-2-354 DOI: https://doi.org/10.24867/IJIEM-2024-2-354
Trung, D., D. (2021). A combination method for multi-criteria decision making problem in turning. Manufacturing review, 8, Art. No. 26. https://doi.org/10.1051/mfreview/2021024 DOI: https://doi.org/10.1051/mfreview/2021024
Trung, D., D. (2021). Application of TOPSIS and PIV methods for multi-criteria decision making in hard turning process. Journal of Machine Engineering, 21(4), 57–71. https://doi.org/10.36897/jme/142599 DOI: https://doi.org/10.36897/jme/142599
Trung, D., D. (2022). Expanding Data Normalization Method to CODAS Method for Multi-Criteria Decision Making. Applied Engineering Letters, 7(2), 54-66, https://doi.org/10.18485/aeletters.2022.7.2.2 DOI: https://doi.org/10.18485/aeletters.2022.7.2.2
Trung, D.D, & Thinh, H.X. (2021). A multi-criteria decision-making in turning process using the MAIRCA, EAMR, MARCOS and TOPSIS methods: A comparative study. Advances in Production Engineering & Management, 16(4), 443-456, https://doi.org/10.14743/apem2021.4.412 DOI: https://doi.org/10.14743/apem2021.4.412
Truong, N. X., Ašonja, A., & Trung, D. D. Enhancing Handheld Polishing Machine Selection: An Integrated Approach of MACROS Methods and Weight Determination Techniques. Applied Engineering Letters, 8(3), 2023: 131-138. https://doi.org/10.18485/aeletters.2023.8.3.5 DOI: https://doi.org/10.18485/aeletters.2023.8.3.5
Ulutaş, A., Popovic, G., Radanov, P., Stanujkic, D., & Karabasevic, D. (2021). A new hybrid fuzzy PSI-PIPRECIA-COCOSO MCDM based approach to solving the transportation company selection problem. Technological and Economic Development of Economy, 27(5), 1227–1249. https://doi.org/10.3846/tede.2021.15058 DOI: https://doi.org/10.3846/tede.2021.15058
Ventista, O. M., & Brown, C. (2023). Teachers’ professional learning and its impact on students’ learning outcomes: Findings from a systematic review. Social Sciences & Humanities Open, 8(1), 100565. https://doi.org/10.1016/j.ssaho.2023.100565 DOI: https://doi.org/10.1016/j.ssaho.2023.100565
Zakeri, S., Chatterjee, P., Konstantas, D., & Ecer, F. (2023). A decision analysis model for material selection using simple ranking process. Scientifc Reports, 13, Art. No. 8631. https://doi.org/10.1038/s41598-023-35405-z DOI: https://doi.org/10.1038/s41598-023-35405-z
Zakeri, S., Chatterjee, P., Konstantas, D., & Ecer, F. (2024). A comparative analysis of simple ranking process and faire un Choix Adéquat method. Decision Analytics Journal, 10, Art. No. 100380. https://doi.org/10.1016/j.dajour.2023.100380 DOI: https://doi.org/10.1016/j.dajour.2023.100380
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Copyright (c) 2024 Branislav Dudic, Do Duc Trung
This work is licensed under a Creative Commons Attribution 4.0 International License.
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Accepted 2024-07-30
Published 2024-08-31