Abstract

The article aims to present research on the possibilities of using the PROMETHEE II method to optimize the selection of e-learning courses. The first part of the paper presents methodological assumptions concerning multicriteria decision-making methods (MCDM), with particular emphasis on the PROMETHEE II. In the second part, by structuring the problem, it was possible to understand better issues related to the selection of assessment criteria and the alternatives (e-learning courses) to be evaluated. The proposed research concept can be used to analyze other e-learning issues within the framework of specific subjects, such as e-learning system performance or teaching modes. Assuming the best identification and selection of descriptive characteristics and transforming them into real determinants, the PROMETHEE II concept can be used to improve decisions on optimizing problems related to the e-learning courses selection and other educational goals.

Keywords: PROMETHEE II, e-learning, optimization

References

• Bana e Costa, C.A., Vansnick, F.C. (1999). Sur la quantification des jugements de valeur: L'approche MACBETH, Cahiers du LAMSADE, 117. Paris: Université Paris-Dauphine.
• Banayoun, R., Roy, B., Sussman, N. (1966). Manual de référence du programme Electre. Note de synthése et Formation 25. Direction Scientifique SEMA.
• Bedir, N., Özder, E.H., Eren, T. (2016). Course Selection with AHP & PROMETHEE Methods for Post Graduate Students: An Application in Kirikkale University Graduate School of Natural and Applied Sciences. The 3rd International Conference on Industrial Engineering and Applications (ICIEA 2016). DOI: https://doi.org/10.1051/matecconf/20166820004
• Behzadian, M., Kazemzadeh, R., Albadvi, A., Aghdasi, M. (2010). PROMETHEE: A comprehensive literature review on methodologies and applications. European Journal of Operational Research, 200(1), 198-215.
• Boutkhoum, O., Hanine, M., Agouti, T., Tikniouine, A. (2017). A decision-maiking approach based on fuzzy AHP-TOPSIS metodology for selecting appropriate cloud solution to manage big data projects. International Journal of System Assurance Engineering and Management, 8(2), 1237-1253. DOI: https://doi.org/10.1007/s13198-017-0592-x
• Brans, J.P., Vincke, Ph. (1985). Note - A Preference Ranking Organization Method (The PROMETHEÉ Method for Multiple Criteria Decision-Making). Management Science, 31(6), 647-656. https://doi.org/10.1287/mnsc.31.6.647
• Charnes, A., Cooper, W., Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444. DOI: https://doi.org/10.1016/0377-2217(78)90138-8
• Edwards, W., Barron, F.H. (1994). SMARTS and SMARTER: improved simple methods for multiattribute utility measurement. Organizational Behavior and Human Decison Processes, 60(3), 306-325. DOI: https://doi.org/10.1006/obhd.1994.1087
• Jahanshahloo, G.R., Hosseinzadeh Lotfi, F., Izadikhah, M. (2006). Extension of the TOPSIS method for decision-making problems with fuzzy data. Applied Mathematics and Computation 181(2), 1544-1551. DOI: https://doi.org/10.1016/j.amc.2006.02.057
• Murat, S., Kazan, H. i Coskun, S.S. (2015). An Application for Measuring Performance Quality of Schools by Using the PROMETHEE Multi-Criteria Decision Making Method. Procedia - Social and Behavioral Sciences, 195, 729-738. DOI: https://doi.org/10.1016/j.sbspro.2015.06.344
• Roy, B. (1990). Wielokryterialne wspomaganie decyzji. Warszawa: Wydawnictwo Naukowo-Techniczne.
• Saaty, R.W. (2002). Decision Making in Complex Environments: The Analytic Network Process (ANP) for Dependence and Feedback; a manual for the ANP Software SuperDecisions. Creative Decisions Foundation.
• Sianturi, L.T., Karim, A., Utama Siahaan, A.P., Mesran, A., Fadlina, F. (2017). Best Student Selection Using Extended Promethee II Method. International Journal of Recent Trends in Engineering & Research, 3(8), 21-29. DOI: 10.23883/IJRTER.2017.3382.SK4CV
• Triantaphyllou, E. (2000). Multi-Criteria Decision Making Methods: A Comparative Study. Boston: Springer.
• Trzaskalik, T. (red.). (2014). Wielokryterialne wspomaganie decyzji. Metody i zastosowania. Warszawa: PWE.
• Zalewski, W. (2012). Zastosowanie metody TOPSIS do oceny kondycji finansowej spółek dystrybucyjnych energii elektrycznej. Economics and Management 4(4), 138-145.
• Ziemba, P., Piwowarski, M. (2010). Dobór platformy e-learningowej za pomocą metody PROMETHEE GDSS. Metody Informatyki Stosowanej 4(24), 109-124.