АУТОР(И): Daniel Doz, Darjo Felda, Mara Cotič
Assessing students’ mathematical knowledge informs students, educators, and parents about students’ mathematical competencies. In Italy, some students receive both written and oral grades in mathematics at the end of the first semester, which are then averaged for a final grade. The possibility of applying fuzzy logic, which has been widely used to deal with uncertain or verbal descriptions, to this process has not yet been explored extensively. In the present contribution, we consider a sample of N = 47 Italian high school students, and analyze two fuzzy combinations of their mathematics grades. Students’ hypothetical grades produced with the center-of-gravity defuzzification method are lower than students’ grades in their report cards, while the mean-of-maxima defuzzification method produced grades that are statistically higher than the students’ original grades. Implications are discussed, leading to suggestions for assessment research.
assessment, defuzzification, fuzzification, fuzzy logic.
- Amelia, N., Abdullah, A. G. & Mulyadi, Y. (2019). Meta-analysis of student performance assessment using fuzzy logic. Indonesian Journal of Science and Technology, 4(1), 74–88.
- Bai, Y. & Wang, D. (2006). Fundamentals of fuzzy logic control-fuzzy sets, fuzzy rules and defuzzifications. In Y. Bai, H. Zhuang & D. Wang (eds.): Advanced fuzzy logic technologies in industrial applications (17–36). London: Springer.
- Bjelica, M. & Rankovic, D. (2010). The Use оf Fuzzy Theory in Grading оf Students in Math. Turkish Online Journal of Distance Education, 11(1), 13–19.
- Close, D. (2009). Fair grades. Teaching Philosophy, 32(4), 361–398.
- CM 94/2011. Retriеved January 9, 2022 from the World Wide Web https:// www.istruzione.it/archivio/web/istruzione/prot6828_11.html.
- DLgs 297/1994. Retriеved January 9, 2022 from the World Wide Web https://archivio. pubblica.istruzione.it/comitato_musica_new/normativa/allegati/dlgs160494.pdf.
- DLgs 62/2017. Retriеved January 9, 2022 from the World Wide Web https://www.gazzettaufficiale.it/eli/id/2017/05/16/17G00070/sg.
- Felda, D. (2018). Preverjanje matematičnega znanja. Journal of Elementary Education, 11(2), 175–188.
- Felda, D. & Cotič, M. (2012). Zakaj poučevati matematiko. Journal of Elementary Education, 5(2/3), 107–120.
- Ivanova, V. & Zlatanov, B. (2019). Implementation of fuzzy functions aimed at fairer grading of students’ tests. Education Sciences, 9(3), 214.
- Kumari, N. A., Rao, D. N. & Reddy, M. S. (2017). Indexing student performance with fuzzy logics evaluation in engineering education. International Journal of Engineering Technology Science and Research, 4(9), 514–522.
- Meenakshi, N. & Pankaj, N. (2015). Application of Fuzzy Logic for Evaluation of Academic Performance of Students of Computer Application Course. IJRASET 2015, 3(X), 260–267.
- Menéndez, I. Y. C., Napa, M. A. C., Moreira, M. L. M. & Zambrano, G. G. V. (2019). The importance of formative assessment in the learning teaching process. International journal of social sciences and humanities, 3(2), 238–249.
- MIUR (2022). Retriеved January 13, 2022 from the World Wide Web https://www.miur.gov.it/scuola-secondaria-di-secondo-grado.
- Namli, N. A. & Şenkal, O. (2018). Using the Fuzzy Logic in Assessing the Programming Performance of Students. International Journal of Assessment Tools in Education, 5(4), 701–712.
- Patterson, C. L., Parrott, A. & Belnap, J. (2020). Strategies for assessing mathematical knowledge for teaching in mathematics content courses. The Mathematics Enthusiast, 17(2), 807–842.
- Petrudi, S. H. J., Pirouz, M. & Pirouz, B. (2013). Application of fuzzy logic for performance evaluation of academic students. 2013 13th Iranian Conference on Fuzzy Systems (1–5). IEEE.
- RD 653/1925. Retriеved January 9, 2022 from the World Wide Web https://www. normattiva.it/uri-res/N2Ls?urn:nir:stato:legge:1925-05-04;653.
- Saliu, S. (2005). Constrained subjective assessment of student learning. Journal of Science Education and Technology, 14(3), 271–284.
- Semerci, Ç. (2004). The Influence of Fuzzy Logic Theory on Studentsʼ Achievement.
- Turkish Online Journal of Educational Technology, 3(2), 56–61.
- Sharma, S. & Obaid, A. J. (2020). Mathematical modelling, analysis and design of fuzzy logic controller for the control of ventilation systems using MATLAB fuzzy logic toolbox. Journal of Interdisciplinary Mathematics, 23(4), 843–849.
- Voskoglou, M. G. (2013). Fuzzy logic as a tool for assessing students’ knowledge and skills. Education sciences, 3(2), 208–221.
- Yadav, R. S., Soni, A. K. & Pal, S. (2014). A study of academic performance evaluation using Fuzzy Logic techniques. 2014 International Conference on Computing for Sustainable Global Development (48–53). IEEE.
- Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353.
- Zhao, X., den Heuvel-Panhuizen, V. & Veldhuis, M. (2018). Chinese primary school mathematics teachers’ assessment profiles: Findings from a large-scale questionnaire survey. International Journal of Science and Mathematics Education, 16(7), 1387–1407.