Abstract
The paper presents methods of preparing students’ rankings based on the results of final secondary school examination test in mathematics in Poland with the proposal of methods for calculating the levels of the likelihood of learning outcome acquirement. The currently used method is based on the percentage of earned points and does not take into account levels of acquirement of learning outcomes by students. The data used in this article contains results of students who earned the same number of points, so the structure of this uniform group with respect to learning outcomes will be presented. All chosen methods of preparing rankings are based on the experts’ assessment of levels of verification of learning outcomes by items and methods of this assessment fuzzification. According to the applied method, the rankings show some difference.
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References
European Higher Educational Area. www.ehea.info. Accessed 12 July 2016
Rozporządzenie Ministra Edukacji Narodowej z dnia 23 grudnia 2008 r. w sprawie podstawy programowej wychowania przedszkolnego oraz kształcenia ogólnego w poszczególnych typach szkół. http://isap.sejm.gov.pl. Accessed 12 July 2016
Zasady oceniania rozwiązań zadań, Egzamin maturalny w roku 2014/2015, Centralna Komisja Egzaminacyjna. www.cke.edu.pl. Accessed 12 July 2016
Ahmad, B., Kharal, A.: On fuzzy soft sets. Adv. Fuzzy Syst. 2009, 6 p. (2009). Article ID 586507. https://doi.org/10.1155/2009/586507
Baker, F.B.: The Basics of Item Response Theory. ERIC Clearinghouse on Assessment and Evaluation, USA (2001)
Biswas, R.: An application of fuzzy sets in students’ evaluation. Fuzzy Sets Syst. 74, 187–194 (1995)
Csaba, J.Z.: Survey on four fuzzy set theory based student evaluation methods. In: Proceedings of Kecskemét College, Faculty of Technology (GAMF), Kecskemét, HU, vol. XXIII, pp. 121–130 (2008). ISSN: 1587-4400
Dayan, F., Zulqarnain, M., Hassan, N.: A ranking method for students of different socio economic backgrounds based on generalized fuzzy soft sets. Int. J. Sci. Res. (IJSR) 6(9), 2015–2018 (2017)
Dobrosielski, W.T., Szczepański, J., Zarzycki, H.: A proposal for a method of defuzzification based on the golden Ratio—GR. In: Atanassov, K.T., et al. (eds.) Novel Developments in Uncertainty Representation and Processing. AISC, vol. 401, pp. 75–84. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-26211-6_7
Duch, W., Wieczorek, T., Biesiada, J., Blachnik, M.: Comparison of feature ranking methods based on information entropy. In: Proceedings of International Joint Conference on Neural Networks (IJCNN), Budapest 2004, pp. 1415–1420. IEEE Press (2004)
Duch, W., Winiarski T., Biesiada J., Kachel, A.: Feature ranking, selection and discretization. In: Proceedings of Joint International Conference on Artificial Neural Networks (ICANN) and International Conference on Neural Information Processing (ICONIP), Istanbul, pp. 251–254 (2003)
Erdoğan, M., Kaya, İ.: A type-2 fuzzy MCDM method for ranking private universities in İstanbul. In: Proceedings of the World Congress on Engineering, WCE 2014, London, U.K. 2–4 July, vol. 1 (2014)
Hambleton, R.K., Swaminathan, H.: Item Response Theory, Principles and Applications. Springer Science + Business Media, LLC, New York (1991). https://doi.org/10.1007/978-94-017-1988-9
Hameed, I.A., Sorensen, C.G.: Fuzzy systems in education: a more reliable system for student evaluation. In: Azar, A.T. (ed.) Fuzzy systems. InTech, London (2010). http://www.intechopen.com/books/fuzzy-systems/fuzzy-systems-in-education-a-more-reliable-system-for-student-evaluation
Huapaya, C.: Proposal of fuzzy logic-based students´ learning assessment model. In: XVIII Congreso Argentino de Ciencias de la Computación (2012)
Ingoley, S., Bakal, J.W.: Use of fuzzy logic in evaluating students’ learning achievement. Int. J. Adv. Comput. Eng. Commun. Technol. (IJACECT), 1(2), 47–54 (2012)
Majumdar, P., Samanta, S.K.: A generalised fuzzy soft set based student ranking system. Int. J. Adv. Soft Comput. Appl. 3(3) November 2011. www.i-csrs.org
Molodtsov, D.: Soft set theory first results. Comput. Math App. 37, 19–31 (1999)
Mreła, A., Sokolov, O., Katafiasz, T.: Types of fuzzy relations’ composition applied to the validation of learning outcomes at mathematics during final high school examination. In: Mreła, A., Wilkoszewski, P. (eds.): Nauka i technika u progu III tysiąclecia, Wydawnictwo Kujawsko-Pomorskiej Szkoły Wyższej w Bydgoszczy, Bydgoszcz, pp. 119–132 (2015)
Heймaн, Ю.M, Xлeбникoв, B.A.: Bвeдeниe в тeopию мoдeлиpoвaния и пapaмeтpизaции пeдaгoгичecкиx тecтoв. Пpoмeтeй, M. (2000)
Rutkowski, R.: Metody i techniki sztucznej inteligencji. PWN, Warsaw (2009)
Yadav, A.K., Reza, A., Srivastava, S.: A comparative study for ranking the efficiency of washing machines based on fuzzy set theory. Int. J. Innov. Res. Sci., Eng. Technol. 3(4), 11678–11684 (2014)
Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965)
Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning–1. Inf. Sci. 8, 199–249 (1975)
Zeng, W., Li, J.: Fuzzy logic and its application in football team ranking. Sci. World J. 2014, 1–6 (2014). https://doi.org/10.1155/2014/291650. Article ID 291650
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Mreła, A., Sokolov, O. (2018). Rankings of Students Based on Experts’ Assessment and Levels of the Likelihood of Learning Outcome Acquirement. In: Bassiliades, N., et al. Information and Communication Technologies in Education, Research, and Industrial Applications. ICTERI 2017. Communications in Computer and Information Science, vol 826. Springer, Cham. https://doi.org/10.1007/978-3-319-76168-8_4
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