EVALUATION OF PROSPECTIVE MATH TEACHERS’ ABILITY TO ENTER GRADUATE EDUCATION WITH FUZZY LOGIC ALONG WITH VARIOUS COMPONENTS

Elif Bahadir

Abstract


It seems that getting graduate education has become more important compared to the past. This is the case for teachers and prospective teachers. In order to be admitted for graduate education in Turkey, one must have ALES (Academic personnel and graduate education entrance exam), College GPA (graduation grade point average) and a foreign language score. The road to success is a difficult process for many students to complete when represented by classification of traditional graduation grade point average. Development approaches of student achievement need to have a framework consisting of more in number and a complex success criteria in order to be more effective. Apart from the aforementioned grade data that was mainly determined in the classification that classify whether prospective teachers were suitable for graduate education or not, some other components such as; their emotional data, their level of knowledge on graduate education and how much priority they give to teaching department while doing their university preferences have also become important. The study was shaped in this context and by assessing various components related to the students with fuzzy logic, a more effective prediction and classification was tried to be presented. In the study, considering attitudes of prospective teachers towards graduate education, their genders, their levels of knowledge on graduate education, their university entrance scores, their order of preference, and their levels in undergraduate education, their suitabilities of admission to graduate education was aimed to be determined by fuzzy logic. In our study in which relationships of all above mentioned components with each other were analyzed, survey (scanning) method, of quantitative research methods, was used and the relational scanning model was preferred. In the study, the information of 390 prospective teachers who were studying at the department of primary school mathematics teaching in three different state universities and attending at formation programs but graduated from faculty of arts and sciences mathematics teaching department was used. MATLAB software was used for fuzzy logic analysis. In the research, a fuzzy logic rule base was created and 98 (25.1%) of the analyzed data were decided to be suitable for graduate education program. 29 (7.4%) of these prospective teachers were from the first year, 48 (12.3%) of them were from the fourth year, and 21 (5.3%) of them were from the formation group. The group with the highest percentage of prospective teachers considered to be suitable for graduate education is fourth year undergraduate students with 12.3%. The group with the lowest percentage is formation students with 5.3%. As a result of the analyses conducted by fuzzy logic providing a valid prediction and classification, the reason of fourth year prospective teachers have the highest percentage in the research can be explained as their having higher attitude scores and being more knowledge about graduate education and having higher scores on the university entrance exams than the other participants. In order to ensure prospective teachers to have a higher attitude towards the graduate education, their gaining awareness of research and being informed about graduate education from the first years of college can provide significant benefits. Prospective teachers in different departments may be included in the study. Considering different components related to the prospective teachers and conducting researches using other methods of artificial intelligence such as fuzzy logic, students and educators can be provided an effective prediction and classification opportunities.

 

Article visualizations:

Hit counter

DOI

Keywords


fuzzy logic, graduate education, attitude, classification

Full Text:

PDF

References


Agbuga, B., Xiang, P., & McBride, R. (2012). Students’ attitudes toward an after-school physical activity programme. European Physical Education Review, 1356336X12465511.

Akiyama, T., Tsuboi, H., Description of Route Choice Behaviour by Multi-Stage Fuzzy Reasoning, Paper presented at the Highways to the Next Century Conference, Hong Kong, 1996b.

Al-Aubidy, K. M. (2005). Applying Fuzzy Logic For Learner Modeling And Decision Support In Online Learning Systems. i-Manager's Journal of Educational Technology, 2(3), 76.

Al-Aubidy, K. M., Al-Bader, R. F., & Samadi, A. A. (2005). Simulation and FPGA I mplementation of a simple computer. In The 7th Middle Eastern Simulation Multiconference" MESM2005", Porto (pp. 151-158).

Alabaş, R. (2011). Social studies teachers’ conception of graduate education preferences and its contribution to their professions. Procedia-Social and Behavioural Sciences, 15, 2897-2901. http://dx.doi.org/10.1016/j.sbspro.2011.04.210

Alabaş, R., Kamer, S. T., & Polat, Ü. (2012). Öğretmenlerin Kariyer Gelişimlerinde Lisansüstü Eğitim: Tercih Sebepleri ve Süreçte Karşılaştıkları Sorunlar/Master's Degree Education in The Career Development of Teachers: Reasons of Preference and The Problems That They Face throughout The Process. E-International Journal of Educational Research, 3(4).

Alhas, A. (2006). Lisansüstü eğitim yapmakta olan milli eğitim bakanlığı öğretmenlerinin lisansüstü eğitime bakış açıları. Yayınlanmamış yüksek lisans tezi, Gazi Üniversitesi, Eğitim Bilimleri Enstitüsü, Ankara.

Aloui, A., & Grissa, A. (2015). A New Approach for Flexible Queries Using Fuzzy Ontologies. In Computational Intelligence Applications in Modeling and Control (pp. 315-342). Springer International Publishing.

Altaş İ. H. and Sharaf A. M., A Fuzzy Logic Power Tracking Controller For A Photovoltaic Energy Conversion Scheme, Electric Power Systems Research Journal, Vol.25, No.3, 1992, pp.227-238. [5] İ. Altaş H., A Fuzzy Logic Controlled Tracking System For Moving Targets, 12th IEEE International Symposium on Intelligent Control, ISIC’97, July 16-18, 1997, Istanbul, Turkey, pp. 43-48.

Anastasi, A. & Urbina, S. (1997). Psychological testing. Upper Saddle River, N.J.: Prentice Hall.

Aslan, C. (2010). Türkçe eğitimi programlArinda lisansüstü öğrenim gören öğrencilerin akademik özyeterliklerine ilişkin görüşleri. Mehmet Akif Ersoy Üniversitesi Eğitim Fakültesi Dergisi, 10 (19), 87–115.

Ari, E., Vatansever, F., & Uzun, A. (2009). Student professional orientation using fuzzy logic rules and quality. In 6th Research/Expert Conference With International Participations “Quality 2009 (pp. 04-07).

Balkir, Z. G., Alniacik, U., & Apaydin, E. (2011). Fuzzy logic in legal education.Turkish Online Journal of Distance Education, 12(2).

Barros, B., & Verdejo, M. F. (1999, July). An approach to analyze collaboration when shared structured workspaces are used for carrying out group learning processes. In International Conference on Artificial Intelligence in Education, Le Mans, France.

Başer, N., Narlı, S., & Günhan, B. (2010). Öğretmenlerin Lisansüstü Eğitim Almalarında Yaşanan Sorunlar Ve Çözüm Önerileri. Buca Eğitim Fakültesi Dergisi, (17).

Blouin, D. D., & Moss, A. R. (2015). Graduate Student Teacher Training Still Relevant (and Missing?) 20 Years Later. Teaching Sociology, 43(2), 126-136.

Beyreli, L., & Arı, G. (2005). Türkçe eğitiminde yüksek lisans tezleri ve nitel araştırma tekniklerinin yeri. II. Lisansüstü Eğitim Sempozyumu Bildiri Kitabı, 178-192.

Bertram, C., Mthiyane, N., & Mukeredzi, T. (2013). ‘It will make me a real teacher’: Learning experiences of part time PGCE students in South Africa.International Journal of Educational Development, 33(5), 448-456.

Bunyatova, F. K., & Salamov, G. (2014). New Strategy of the Distance Education. Universal Journal of Educational Research, 2(5), 403-405.

Carlozo, L. (2012). Why college students stop short of a degree? 23 ağustos 2015 tarihinde http://www.reuters.com/article/2012/03/27/us-attn-andreaeducation- dropouts-idUSBRE82Q0Y120120327 adresinden erişildi.

Capaldo, G., & Zollo, G. (2001). Applying fuzzy logic to personnel assessment: a case study.

Omega: The International Journal of Management Science, 29(6), 585–597.

Cuevas, E., Cienfuegos, M., Rojas, R., & Padilla, A. (2015). A Computational Intelligence Optimization Algorithm Based on the Behavior of the Social-Spider. In Computational Intelligence Applications in Modeling and Control (pp. 123-146). Springer International Publishing.

Chang, Y. H., & Yeh, C. H. (2002). A survey analysis of service quality for domestic airlines. European Journal of Operational Research, 139, 166–177.

Chang, D. F., Juan, Y. Y., & Chou, W. C. (2014). Building Better Discipline Strategies for Schools by Fuzzy Logics. International Association for Development of the Information Society.

Chellamani, K. (2014). Operational Efficiency of Interactive E-Learning among Post- Graduation Students in Teacher Education. i-Manager's Journal on School Educational Technology, 10(1), 44.

Chen, L. S., Cheng, C. H., 2005, “Selecting IS Personnel Use Fuzzy GDSS Based on Metric Distance Method”, European Journal of Operational Research, 160, 803- 820.

Chellamani, K. (2014). Operational Efficiency of Interactive E-Learning among Post- Graduation Students in Teacher Education. i-Manager's Journal on School Educational Technology, 10(1), 44.

Chapman, D. W., & Chien, C. L. (2015). Dilemmas of Expansion: The Growth of Graduate Education in Malaysia and Thailand. Higher Education Studies, 5(3), 1.

Chua, S. C., Lim, H. S., Oh, T. H., & Pang, S. Y. (2013). On the possibility of fuzzy method and its mathematical framework in OBE measurements. Knowledge-Based Systems, 37, 305-317.

Cohen, R. J., Swerdlik, M. E., & Phillips, S. M. (1996). Psychological testing and assessment: An introduction to tests and measurement . Mayfield Publishing Co.

Çepni, S. ve Küçük, M. (2002). Fen bilgisi öğretmenlerinin eğitim araştırmalAri hakkındaki düşünceleri. V. Ulusal Fen Bilimleri ve Matematik Eğitimi Kongresi (16–18 Eylül), ODTÜ Kültür ve Kongre Merkezi, Ankara.

Çoklar, A. N. ve Kılıçer, K. (2007). Lisansüstü eğitimde alternatif çözümler: Sanal platformlar. III. Lisansüstü Eğitim Sempozyomu. Eskişehir: Anadolu Üniversitesi Eğitim Bilimleri Enstitüsü, 172–176.

Daniel, M. C., Schumacher, G., Stelter, N., & Riley, C. (2016). Student Perception of Online Learning in ESL Bilingual Teacher Preparation. Universal Journal of Educational Research, 4(3), 561-569.

Demirtaş, Z. (2010). Okul kültürü ile öğrenci başarısı arasındaki ilişki. Eğitim ve Bilim, 35(158).

Dias, S. B., Diniz, J. A., & Hadjileontiadis, L. J. (2014). Dynamic Fuzzy Logic-Based Quality of Interaction within Blended-Learning: The Rare and Contemporary Dance Cases. International Association for Development of the Information Society.

Dogusan, F. (2003). İlköğretim Okulu Yönetici ve Öğretmenlerinin Öğretmenlerin Lisansüstü Öğrenimi Konusundaki Tutumları, Yayınlanmamış yüksek lisans tezi, Kırıkkale Üniversitesi Sosyal Bilimler Enstitüsü. Kırıkkale: Türkiye

Dönmez, A., Aydoğdu, E., Sever, M., Ahmet Aypay (2012). Öğretmen Adaylarının Lisansüstü Eğitime Yönelik Tutumlar, Trakya Üniversitesi Eğitim Fakültesi Dergisi, 2 (1) :9-26

Duan, X., Shan, G., Xu, Y., Li, B., Zhao, X., & Xu, L. (2013, December). Suggestions for graduate curriculum reform. In Proceedings of AASRI Winter International Conference on Engineering and Technology (pp. 28-29).

Dweiri, F. T., & Kablan, M. M. (2006). Using fuzzy decision making for the evaluation of the project management internal efficiency. Decision Support Systems, 42(2), 712- 726.

Erkılıç, T.A. (2007). Öğretmen Adaylarının Lisansüstü Eğitim İstekliliklerini Etkileyen Etmenler (Eskişehir Örneği), GAU Journal of Social &Applied Sciences 3(5) :46-72

Erkuş, A. (2003). Psikometri üzerine yazılar. Ankara: Türk Psikologlar Derneği Yayınları.

Fourali, C. (1997). Using fuzzy logic in educational measurement: the case of portfolio assessment. Evaluation & Research in Education, 11(3), 129–148.

Gravani, M. N., Hadjileontiadou, S. J., Nikolaidou, G. N., & Hadjileontiadis, L. J. (2007). Professional learning: A fuzzy logic-based modeling approach. Learning and Instruction, 17(2), 235-252.

Guzzomi, A. L., Male, S. A., & Miller, K. (2015). Students’ responses to authentic assessment designed to develop commitment to performing at their best. European Journal of Engineering Education, 1-22.

Gökmen, G., Akıncı, T. Ç., Tektaş, M., Onat, N., Koçyiğit, G., & Tektaş, N. (2010). Evaluation of student performance in laboratory applications using fuzzy logic. Procedia-Social and Behavioral Sciences, 2(2), 902-909.

Hadjileontiadou, S. J., & Hadjileontiadis, L. J. (2003). Using ANFIS to efficiently model skills and beliefs in computer-mediated collaboration. InProceedings of the 1st Balkan Conference in Informatics. Thessaloniki: Greece.

Hadjileontiadou, S. J., Nikolaidou, G. N., Hadjileontiadis, L. J., & Balafoutas, G. N. (2004). On enhancing on-line collaboration using fuzzy logic modeling. Journal of Educational Technology & Society, 7(2), 68-81.

Henn V., Fuzzy Route Choice Model for Traffic Assignment, Proceedings of the 9th mini EURO Conference Fuzzy Sets in Traffic and Transportation Systems, Budva, 1997

Herrera, F., Lopez, E., Mendana, C., Rodrıguez, A. M., 2001, “A Linguistic Decision Model for Personnel Management Solved with A Linguistic Biobjective Genetic Algorithm”, Fuzzy Sets and Systems, 118, 47-64.

Hoban, G. F. (2002). Teacher learning for educational change: A systems thinking approach. Buckingham: Open University Press.Hu, Y. C. (2009). Fuzzy multiple- criteria decision making in the determination of critical criteria for assessing service quality of travel websites. Expert Systems with Application, 36, 6439– 6445.

Hwang, G. J., Huang, T. C., & Tseng, J. C. (2004). A group-decision approach for evaluating educational web sites. Computers & Education, 42(1), 65-86.

Humphrey, R., & McCarthy, P. (1999). Recognising difference: providing for graduate students. Studies in Higher Education, 24(3), 371-386.

İbiş, E. (2014). Lisansüstü Eğitimin Sorunları. Journal of Higher Education/Yüksekögretim Dergisi, 4(3).

İpek, H., Şahin, Ç., & Çepni, S. (2007). Fen Bilimleri Eğitiminde Araştırma Yöntemleri Dersi Hakkında Lisansüstü Öğrencilerin Görüşleri. III. Lisansüstü Eğitim Sempozyumu Bildiriler Kitabı, Ekim, 703-708.

John, P. D., & Gravani, M. N. (2005). Evaluating a ‘new’ in-service professional development program in Greece: the experiences of tutors and teachers. Journal of In-service Education, 31(1), 105e129.

Johnson, K. E. (2009). Second language teacher education: A sociocultural perspective. Routledge.

Jones-White, D. R., Radcliffe, P. M., Huesman Jr, R. L., & Kellogg, J. P. (2010). Redefining student success: Applying different multinomial regression techniques for the study of student graduation across institutions of higher education. Research in Higher Education, 51(2), 154-174.

Johnson, G., & Howell, A. (2005). Attitude toward instructional technology following required versus optional WebCT usage. Journal of Technology and Teacher Education, 13(4), 643-654.

Kubow, P. K., & Blosser, A. H. (2016). Teaching Comparative Education: Trends and Issues Informing Practice. In Symposium Books. Symposium Books. PO Box 204, Didcot, Oxford, OX11 9ZQ, UK.

Konokman, G. Y., & Alıcı, D. (2014). An Attitude Scale about Graduate Education: Reliability and Validity Study. International Online Journal of Educational Sciences, 6(1).

Kolasa, Blair J. (1979). İşletmeler için davranış bilimlerine giriş (Çev: Kemal Tosun ve Diğerleri). İÜ İşletme Fakültesi İşletme İktisadi Enstitüsü YayınlAri, İstanbul.

Kazu, İ. Y., & Özdemir, O. (2009). Öğrencilerin bireysel özelliklerinin yapay zeka ile belirlenmesi (Bulanık mantık örneği). In Akademik Bilişim 2009 Konferansı, 11– 13 Şubat 2009 (pp. 457-466). Harran Üniversitesi Şanlıurfa.

Kazancoglu, Y., & Aksoy, M. (2011). A fuzzy logic-based quality function deployment for selection of e-learning provider. TOJET: The Turkish Online Journal of Educational Technology, 10(4).

Kavcic, A., Pedraza-Jiménez, R., Molina-Bulla, H., Valverde-Albacete, F. J., Cid-Sueiro, J., & Navia-Vázquez, A. (2003). Student modeling based on fuzzy inference mechanisms (Vol. 2, pp. 379-383). IEEE.

Kaçalin, M. S. (2008). Türkçe eğitimi lisansüstü çalışmalarında metin incelemeleri. II. Lisansüstü Eğitim Sempozyumu Bildiri Kitabı, 200-208.

Kara, F. (2008). Matematik öğretmenlerinin lisansüstü eğitim deneyimleri ve okul yaşantıl Arina yansımal Ari. Yayınlanmamış yüksek lisans tezi, Karadeniz Teknik Üniversitesi Fen Bilimleri Enstitüsü, Trabzon.

Karakütük, (1999). Lisansüstü öğretimde örgütlenme modelleri ve Türkiye’deki uygulamalar. 6. Ulusal Sosyal Bilimler Kongresi, 17-19 Kasım, Ankara.

Karakütük, K. (2000). Avrupa, Asya ve Amerika’da lisansüstü öğretim reformu. Ankara: Pegem A Yayıncılık.

Karakütük, K. (2002). Öğretim üyesi ve bilim insanı yetiştirme: Lisansüstü öğretimin planlanması. Anı Yayıncılık.

Kan, A. ve Akbaş, A. (2006). Affective factors that influence chemistry achievement (attitude and self efficacy) and the power of these factors to predict chemistry achievement-I. Journal of Turkish Science Education, 3(1): 76-85.

Keser, İ., & Sarıbay, E. (2007). İzmir’deki özel ve devlet üniversitelerindeki öğrencilerin başarılarını etkileyen faktörlerin belirlenmesi ve karşılaştırılması.Muğla Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 18, 39-48.

Kosko, B. (1992). Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence/book and disk. Prentice Hall, Upper Saddle River.

Köksalan, B. İlter, İ. ve Görmez, E. (2010). Sınıf Öğretmeni Adaylarının Sosyo-Kültürel Özellikleri ve Lisansüstü Eğitim İsteklilikleri Üzerine Bir Çalışma (Fırat, Erzincan ve İnönü Üniversitesi Sınıf Öğretmenliği ABD Örneği). Ahi Evran Üniversitesi Eğitim Fakültesi Dergisi, 11 (3): 277-299

Kyriacou, C., Coulthard, M. (2000). Undergraduates’ views of teaching as a career choice. Journal of Education for Teaching, 26(2), 117-126.

Laouafi, A., Mordjaoui, M., & Dib, D. (2015). One-hour ahead electric load forecasting using neuro-fuzzy system in a parallel approach. In Computational Intelligence Applications in Modeling and Control (pp. 95-121). Springer International Publishing.

Lessing, N., & Lessing, A. C. (2004). The supervision of research for dissertations and theses. Acta Commercii, 4(1), 73-87.

Levin, T., Naama, S. ve Zipora, L. (1991). Achievements and attitudinal patterns of boys and girls in science. Journal of Research in Science Teaching, 28 (4): 315-328.

Li, K. K., Lai, L. L., & David, A. K. (2000). Standalone intelligent digital distance relay. Power Systems, IEEE Transactions on, 15(1), 137-142.

Liu, C. C., Pierce, D., & Song, H. (1997). Intelligent system applications to power systems. Computer Applications in Power, IEEE, 10(4), 21-22.

Lo H. and Lam W.S.P., A Modified Multinomial Logit Model of Route Choice for Drivers Using the Transportation Information System, 295-299s., Proceedings of 9th Mini-EURO Conference, 1997.

Lykourentzou, I., Giannoukos, I., Mpardis, G., Nikolopoulos, V., & Loumos, V. (2009). Early and dynamic student achievement prediction in e-learning courses using neural networks. JASIST, 372-380.

McAlpine, L., & Norton, J. (2006). Reframing our approach to doctoral programs: An integrative framework for action and research. Higher Education Research & Development, 25(1), 3-17.

McMahon, S., & Jones, I. (2015). A comparative judgement approach to teacher assessment. Assessment in Education: Principles, Policy & Practice,22(3), 368-389.

Memduhoğlu, H. B., & Tanhan, F. (2009, May). Üniversite öğrencilerinin akademik başarılarını etkileyen örgütsel faktörler ölçeğinin geliştirilmesi. In The First International Congress of Educational Research, 1-3 May, Çanakkale.

Morgan, C. T. (1991). Psikolojiye giriş. 8. Baskı (Çev. Arıcı, H., Aydın, O. vd.), Ankara, Hacettepe Üniversitesi Psikoloji Bölümü Yayınları.

Mullier, D. J. (2000). The application of neural network and fuzzy logic techniques to educational hypermedia (Doctoral dissertation, Leeds Metropolitan University).

Nasr, K. J. (2014). Towards a converged and global set of competencies for graduates of engineering programs in a globalization-governed world. Impact of Globalization On Engineering Education, 15, 15.

Oğuz, A., (2004). Bilgi Çağında Yüksek Öğretim Programları, Milli Eğitim Dergisi, 164.

Oluk, S. ve Çolak, F. (2005). Milli Eğitim Bakanlığına Bağlı Okullarda Öğretmen Olarak Çalışan Lisansüstü Öğrencilerinin Karşılaştıkları Bazı Sorunlar, Buca Eğitim Fakültesi Dergisi, 17:141-144

Oliver, J. S., & Simpson, R. D. (1988). Influences of attitude toward science, achievement motivation, and science self-concept on achievement in science: A longitudinal study. Science Education, 72(2), 143-155.

Ören, F. Ş., Yılmaz, T. ve Güçlü, M. (2012). Öğretmen adaylArinın lisansüstü eğitime yönelik görüşlerinin analizi. Eğitim ve Öğretim AraştırmalAri Dergisi. 1(2), 189- 201.

Prevatt, F., Proctor, B., Best, L., Baker, L., Van Walker, J., & Taylor, N. W. (2011). The positive illusory bias: Does it explain self-evaluations in college students with ADHD?. Journal of attention disorders, 1087054710392538.

Radford, J. & Govier, E. (1991). A Textbook of psychology. London: Sheldon Press.

Ramadi, E., Ramadi, S., & Nasr, K. (2016). Engineering graduates’ skill sets in the MENA region: a gap analysis of industry expectations and satisfaction.European Journal of Engineering Education, 41(1), 34-52.

Ruffell, M., Mason, J., & Allen, B. (1998). Studying attitude to mathematics. Educational Studies in Mathematics, 35(1), 1-18.

Senemoğlu, N., & Özçelik, D. A. (1989). Öğretmen adaylArina “öğretmenlik bilgisi” kazandırma bakımından fen-edebiyat ve eğitim fakültelerinin etkililiği. Çağdaş Eğitim Dergisi, 142, 18-21.

Shekhar, N. C., Venkatasubbaiah, K., & Kandukuria, N. R. (2012). Establishing the overall service quality of engineering education: fuzzy logic approach.European Journal of Engineering Education, 37(6), 575-591.

Smith, M. B. (1968). Attitude change. International encyclopedia of the social sciences, 458- 467.

Smithson, M. J. (1987). Fuzzy set analysis for the behavioral and social sciences (Recent

Research in Psychology). New York: Springer-Verlag.

Sonnert, G., Sadler, P. M., Sadler, S. M., & Bressoud, D. M. (2015). The impact of instructor pedagogy on college calculus students’ attitude toward mathematics. International Journal of Mathematical Education in Science and Technology, 46(3), 370-387.

Sahin, M., & Kisla, T. (2016). An Analysis of University Students' Attitudes towards Personalized Learning Environments. Turkish Online Journal of Educational Technology-TOJET, 15(1), 1-10.

Şaşmaz Ören, F., Yılmaz, T. ve Güçlü, M. (2012). Öğretmen Adaylarının Lisansüstü Eğitime Yönelik Görüşlerinin Analizi, Eğitim ve Öğretim Araştırmaları Dergisi, 1 (2):189-201

Şen, Z. (2004). Mühendislikte Bulanık Mantık ile Modelleme Prensipleri, Su Vakfı Yayınları

Tavşancıl, E. (2006). Tutumların ölçülmesi ve SPSS ile veri analizi. Ankara: Nobel Yayın Dağıtım.

Taylan, O., & Karagözoğlu, B. (2009). An adaptive neuro-fuzzy model for prediction of student’s academic performance. Computers & Industrial Engineering, 57(3), 732- 741.

Tokmak, H. S., Baturay, H. M., & Fadde, P. (2013). Applying the context, input, process, product evaluation model for evaluation, research, and redesign of an online master’s program. The International Review of Research in Open and Distributed Learning, 14(3), 273-293.

Uras, M. ve Kunt, M. (2005). Öğretmen adaylArinın öğretmenlik mesleğinden beklentileri ve beklentilerinin karşılanmasının umma düzeyleri. Pamukkale Üniversitesi Eğitim Fakültesi Dergisi, 19.

Ünal, Ç., & İlter, İ. (2010). Sınıf Öğretmeni AdaylArinın Lisansüstü Eğitime Olan Tutuml Ari (Fırat, Erzincan ve İnönü Üniversitesi Sınıf Öğretmenliği ABD Örneği)/Attitudes of Classroom Teacher Candidates toward Graduate Education. Atatürk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 14(2).

Van Hecke, T. (2011). Fuzzy Expert System to Characterize Students. PRIMUS,21(7), 651-658.

Yasar, M. (2016). High School Students' Attitudes towards Mathematics.Eurasia Journal of Mathematics, Science & Technology Education, 12(4), 931-945.

Yaşar, G., & Ünal, F. T. (2016). Behavior Towards Improving Vocabulary Scale: The Study of Reliability and Validity/Türkçe Dersi Söz Varlığını Geliştirmeye Yönelik Tutum Ölçeği: Bir Geçerlilik ve Güvenirlik Çalışması.Eğitimde Kuram ve Uygulama, 12(5), 1041-1055.

Yaşar, Ş. (2000). Bir meslek olarak öğretmenlik:öğretmenlik mesleğine giriş, (Ed. Ersan Sözer). Anadolu Üniversitesi Açıköğretim Fakültesi YayınlAri No: 700.

Yıldırım, A., Şimşek. H., (2008). Sosyal bilimlerde nitel araştırma yöntemleri. (7. Baskı). Ankara: Seçkin Yayıncılık.

Yıldız, E., Akpınar, E., Aşkar, H., & Ergin, Ö. (2010). Yüksek Lisans Eğitimine Yönelik Öğrenci Görüşleri. Buca Eğitim Fakültesi Dergisi, (17).

Yildiz, O., Bal, A., & Gulsecen, S. (2013). Improved fuzzy modeling to predict the academic performance of distance education students. The International Review of Research in Open and Distributed Learning, 14(5).

Zafra, A., & Ventura, S. (2009). Predicting student grades in learning management systems with multiple instances genetic programming. Educational Data Mining, 307-314.


Refbacks

  • There are currently no refbacks.


Copyright (c) 2018 Elif Bahadir

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2015-2018. European Journal of Education Studies (ISSN 2501 - 1111) is a registered trademark of Open Access Publishing Group. All rights reserved.


This journal is a serial publication uniquely identified by an International Standard Serial Number (ISSN) serial number certificate issued by Romanian National Library (Biblioteca Nationala a Romaniei). All the research works are uniquely identified by a CrossRef DOI digital object identifier supplied by indexing and repository platforms. All authors who send their manuscripts to this journal and whose articles are published on this journal retain full copyright of their articles. All the research works published on this journal are meeting the Open Access Publishing requirements and can be freely accessed, shared, modified, distributed and used in educational, commercial and non-commercial purposes under a Creative Commons Attribution 4.0 International License (CC BY 4.0).