Öğretmen Adaylarının Öğretmenlik Uygulaması Derslerinin Değerlendirilmesinde Bulanık Mantık Yönteminin Uygulanması

Abstract

In the fast growing world order, we need to evaluate in detail the results of the education given to the teachers that are trained to be successful and qualified according to the needs of this order. This situation demonstrates the importance and care to the individuals that are trained and their characteristics. Moreover, identifying some common criteria and giving fine-tuned evaluations would be more objective and would overcome the inequalities in the evaluations. The more detailed and fine tuned the evaluations are, the more objective and accurate evaluation results we would obtain. The evaluations of the teacher candidates in the courses such as School Experience, Community Services and Teaching Practicum are usually given according to the perceptions of the instructors. In this study, the evaluation of the Teaching Practicum was modeled with the fuzzy logic method. This method is quite significant considering the fact that it might be used as a model for other similar courses as well

Keywords

• Teaching Practicum, Fuzzy Logic Technique, Evaluation

Öğretmen Adaylarının Öğretmenlik Uygulaması Derslerinin Değerlendirilmesinde Bulanık Mantık Yönteminin Uygulanması

Öz

Hızla gelişen dünya düzeninde, bu düzene uygun başarılı ve nitelikli öğretmenler yetiştirmek amacıyla verilen eğitimlerin sonuçlarının detaylı bir şekilde değerlendirilmesi gerekmektedir. Bu durum, özellikle yetiştirilen bireylere ve onların özelliklerine verilen önemi ve özeni de göstermektedir. Ayrıca, belirlenecek olan ortak kriterlere göre yapılan hassas değerlendirmeler daha objektif olacak ve değerlendirmedeki dengesizlikleri de ortadan kaldıracaktır. Çünkü değerlendirme kriterleri ne kadar ayrıntılı ve hassas olursa, değerlendirme sonucu da o denli doğru ve objektif olur. Öğretmen adaylarının, Okul Deneyimi, Topluma Hizmet Uygulamaları ve Öğretmenlik Uygulaması gibi uygulama derslerinin değerlendirilmesi genellikle dersten sorumlu öğretim elemanının inisiyatifine bağlı olarak değişmektedir. Bu çalışmada, bulanık mantık yöntemiyle “Öğretmenlik Uygulaması” dersinin değerlendirmesi modellenmiş olup, bu model diğer uygulama derslerinin değerlendirilmesi için de bir örnek oluşturması bakımından önem arz etmektedir

Anahtar Kelimeler

• Öğretmenlik Uygulaması, Bulanık Mantık Yöntemi, Değerlendirme

Kaynakça

1. Appleby, J., Samuels, P., & Jones, T. T. (1997). Diagnosis – A knowledgebased diagnostic test of basic mathematical skills. Computers & Education, 28, 113–131.
2. Bai, S. M., & Chen, S. M. (2006a). Automatically constructing grade membership functions for students’ evaluation for fuzzy grading systems. In Proceedings of the 2006 world automation congress, Budapest, Hungary.
3. Bai, S. M., & Chen, S. M. (2006b). A new method for students’ Learning achievement using fuzzy membership functions. In Proceedings of the 11th conference on artificial intelligence, Kaohsiung, Taiwan, Republic of China.
4. Bai, S. M., & Chen, S. M. (2007a). Evaluating students’ learning achievement using fuzzy membership functions and fuzzy rules. Expert Systems with Applications, 34, 339–410.
5. Bai, S. M., & Chen, S. M. (2007b). A new approach for constructing concept maps based on fuzzy rules. In Proceedings of the 20th international conference on industrial, engineering and other applications of applied intelligent systems, Kyoto, Japan (pp. 155–165).
6. Bai, S.-M., & Chen, S.-M. (2008a). Automatically constructing grade membership functions of fuzzy rules for students’ evaluation. Expert Systems with Applications, 35(3), 1408–1414.
7. Bai, S.-M., & Chen, S.-M. (2008b). Evaluating students’ learning achievement using fuzzy membership functions and fuzzy rules. Expert Systems with Applications, 34, 399–410.
8. Baykal, N., Beyan, T.(2004), Bulanık Mantık İlke ve Temelleri, Bıçaklar Kitabevi, Ankara

9. Biswas, R. (1995). An application of fuzzy sets in students’ evaluation. Fuzzy Sets and Systems, 74(2), 187–194.
10. Chang, D. F., & Sun, C. M. (1993). Fuzzy assessment of learning performance of junior high school students. In Proceedings of the 1993 first national symposium on fuzzy theory and applications, Hsinchu, Taiwan, Republic of China (pp. 1–10).
11. Cheng, C. H., & Yang, K. L. (1998). Using fuzzy sets in education grading system. Journal of Chinese Fuzzy Systems Association, 4(2), 81–89.
12. Chen, S.M. & Lee, C.H. (1999). New methods for students’ evaluating using fuzzy sets. Fuzzy Sets and Systems, 104, 2, pp. 209–218.
13. Chiang, T. T., & Lin, C. M. (1994). Application of fuzzy theory to teaching assessment. In Proceedings of the 1994 second national conference on fuzzy theory and applications, Taipei, Taiwan, Republic of China (pp. 92–97).
14. Echauz, J. R., & Vachtsevanos, G. J. (1995). Fuzzy grading system. IEEE Transactions on Education, 38(2), 158–165.
15. Hwang, G. J. (2003). A conceptual map model for developing intelligent tutoring systems. Computers & Education, 40, 217–235.
16. Law, C. K. (1996). Using fuzzy numbers in education grading system. Fuzzy Sets and Systems, 83(3), 311–323.
17. Novak, J. D. (1998). Learning, creating, and using knowledge: Concept maps as facilitative tools in schools and corporations. Lawrence Erlbaum Associates. Popham, W. J. (1999). Classroom assessment: What teachers need to know. Pearson Allyn & Bacon, pp. 222–227.
18. Rasmani, K. A., & Shen, Q. (2006). Data-driven fuzzy rule generation and its application for student academic performance evaluation. Applied Intelligence, 25, 305–319.
19. Saleh, I. ; Kim, S.-I. (2009). A fuzzy system for evaluating students' learning achievement. Expert Systems with Applications, 36, 3, pp. 6236-6243.
20. Sönmez, V (2005). Öğretmenlik Mesleğine Giriş. Ankara:Anı Yayıncılık
21. Sue, P. C., Weng, J. F., Su, J. M., & Tseng, S. S. (2004). A new approach for constructing the concept map. In Proceedings of the 2004 IEEE international conference on advanced learning technologies (pp. 76–80).
22. Weon, S. & Kim, J. (2001). Learning achievement evaluation strategy using fuzzy membership function, Proceedings of the 31st ASEE/IEEE Frontiers in Education Conference, Reno: NV.
23. Wang, H. Y., & Chen, S. M. (2006a). New methods for evaluating the answerscripts of students using fuzzy sets. In Proceedings of the 19th international conference on industrial, engineering & other applications of applied intelligent systems, Annecy, France (pp. 442–451).
24. Wang, H. Y., & Chen, S. M. (2006b). New methods for evaluating students’ answerscripts using fuzzy numbers associated with degrees of confidence. In Proceedings of the 2006 IEEE international conference on fuzzy systems, Vancouver, BC, Canada (pp. 5492–5497).
25. Wang, H.Y. & Chen, S.M. (2008). Evaluating students' answerscripts using fuzzy numbers associated with degrees of confidence. IEEE Transactions on Fuzzy Systems, 16, 2, pp. 403-415.
26. Zadeh, L.A. (1965). Fuzzy sets. Information and Control, 8, pp. 338-3