Research Article
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Turkish Adaptation of Mathematical Modeling Attitude Scale (MMAS)

Year 2023, Issue: 94, 52 - 65, 24.05.2023
https://doi.org/10.17753/sosekev.1224724

Abstract

In this research, it is aimed to adapt the Mathematical Modeling Attitude Scale developed by Asempapa (2019) into Turkish. The survey model, one of the quantitative research methods, was used in the research, and the sample of the research consists of 88 teachers and 157 teacher candidates determined by appropriate sampling method. Mathematical Modeling Attitude Scale, Mathematical Modeling Self-Efficacy Scale and Innovative Literacy Scale were used as data collection tools in the research. Explanatory and confirmatory factor analyzes were performed to determine the factor structure of MMAS. It has been concluded that the Turkish version of the MMAS with four factors and 23 items is a valid and reliable measurement tool to measure the attitudes of teachers attending mathematics courses towards mathematical modelling. This study can be done using a larger data set and different variables.

References

  • Arseven, A. (2019). Matematik öğretim yöntemleri. Pegem A Akademi.
  • Asempapa, R.S. (2019). Development and initial psychometric properties of the mathematical modeling attitude scale. School Science and Mathematics,119,14-23. https://doi.org/10.1111/ssm.12311
  • Bal, C. G., Ada, S., & Çelik, A. (2012). Bilişim sistemleri başarı modeli ve aile hekimliği bilişim sistemleri. Yönetim ve Ekonomi Dergisi, 9(1), 35-46.
  • Blum, W. (2011). Can modelling be taught and learnt? Some answers from empirical research. In G. Kaiser, W. Blum, R. Borromeo Ferri, & G. Stillman (Eds.), Trends in teaching and learning of mathematical modelling (pp. 15–30). Springer.
  • Blum, W. (2015). Quality teaching of mathematical modelling: What do we know, what can we do? In S. J. Cho (Ed.), Proceedings of the 12th International Congress on Mathematical Education: Intellectual and attitudinal challenges (pp. 73–96). Springer.
  • Blum, W., & Borromeo Ferri, R. (2009). Mathematical modelling: Can it be taught and learnt? Journal of Mathematical Modelling and Application, 1, 45–58.
  • Bryman, A., & Cramer, D. (2001). Quantitative data analysis with SPSS release 10 for Windows: A guide for social scientists. Routledge.
  • Büyüköztürk, Ş. (2002). Faktör analizi: Temel kavramlar ve ölçek geliştirmede kullanımı. Eğitim Yönetimi, 32, 470-483.
  • Büyüköztürk, Ş., Çakmak, E. K., Akgün, Ö.E., Karadeniz, Ş., & Demirel, F. (2010). Bilimsel araştırma yöntemleri (5.baskı). Pegem.
  • Chin, W. W. (1998). Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), 7–16.
  • Consortium for Mathematics and Its Applications [COMAP] and Society for Industrial and Applied Mathematics [SIAM]. (2016). Guidelines for assessment and instruction in mathematical modeling education. Retrieved from http://www.siam.org/reports/gaimme.php
  • Crouch, G. (2007). Modelling destination competitiveness. A survey and analysis of the impact of competitiveness attributes.
  • Çelik, H. C. (2017). Educational research and reviews mathematical modelling research in Turkey: A content analysis study. Educational Research and Reviews, 12(1), 19–27. https://doi.org/10.5897/ERR2016.3077
  • Field, A. (2009). Discovering statistics using SPSS (3rd ed.). Sage.
  • Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and Statistics. Journal of Marketing Research, 18(3), 382–388. https://doi.org/10.1177/002224378101800313
  • Freeze, R., & Raschke, R. L. (2007). An assessment of formative and reflective constructs in IS Research, Proceedings of the 15th European Conference on Information Systems, 1481-1492.
  • Galbraith, P. L., & Clatworthy, N. J. (1990). Beyond standard models meeting the challenge of modelling. Educational Studies in Mathematics, 21(2), 137-163.
  • Gaskin, J., Validity and Realiability, http://statwiki.gaskination.com/index.php?title=CFA#Validity_and_Reliability. Erişim tarihi: 15.11.2022
  • Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage.
  • Hambleton, R. K. (2005). Issues, Designs and Technical Guidelines for Adapting Tests Into Multiple Languages and Cultures. In R. K. Hambleton, P. F. Merenda and C. D. Spielberger (Eds.). Adapting Psychological and Educational Tests for Cross-Cultural Assessment. Lawrence Erlbaum.
  • Karasar, N. (2008). Bilimsel araştırma yöntemi. Nobel.
  • Koyuncu, I., Guzeller, C. O., & Akyuz, D. (2017). The development of a self-efficacy scale for mathematical modeling competencies. International Journal of Assessment Tools in Education, 4, 19-36. https://doi.org/10.21449/ijate.256552
  • Lesh, R. (2012). Research on models & modeling and implications for common core state curriculum standards. In R. Mayes, L. Hatfield, & S. Belbase (Eds.), WISDOMe Monograph: Quantitative reason-ing and mathematical modeling: A driver for STEM integrated edu-cation and teaching in context (Vol. 2, pp. 197–203). University of Wyoming.
  • Liu, C., Marchewka, J. T., Lu, J., & Yu, C. S. (2005). Beyond concern: A privacy-trust-behavioral intention model of electronic commerce. Information and Management, 42, 289-304.
  • Malhotra, N. K., & Dash, S. (2011). Marketing Research an Applied Orientation. Pearson.
  • National Council of Teachers of Mathematics. (2000). Principles and standards for school mathematics. Author.
  • National Council of Teachers of Mathematics. (2014). Principles to actions: Ensuring mathematical success for all. Author
  • Nunnally, J.C. (1978). Psychometric theory. McGraw-Hill.
  • Petter, S., Straub, D., & Rai, A., (2007). Specifying formative constructs in information systems research, MIS Quarterly, 31, 623-656.
  • Pollak, H. O. (2011). What is mathematical modeling? Journal of Mathematics Education at Teachers College, 2, 64-72.
  • Roberts, N., & Thatcher, J. (2009). Conceptualizing and testing formative constructs: Tutorial and annotated example. ACM sigmis database: The database for Advances in Information Systems, 40(3), 9-39.
  • Yenilmez, K., & Yıldız, Ş. (2019). Matematiksel modelleme ile ilgili lisansüstü tezlerin tematik içerik analizi. Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi, 20 (1), 1–22. https://doi.org/10.17494/ogusbd.548180
  • Yılmaz, A., Çelik, A., & Ulukapı, H. (2015). Çalışanların tinsel değerlere ilişkin algılarının iş stresi üzerindeki etkisinde birey-örgüt uyumunun aracılık rolü: Selçuk Üniversitesi Örneği. 23. Ulusal Yönetim ve Organizasyon Kongresi, 14-16 Mayıs 2015.
  • Yüksel, A. (2022). Entelektüel sermayenin yeni kuramsal yaklaşımı: İnovatif okuryazarlık (Tez No. 729939) [Doktora Tezi, Gebze Teknik Üniversitesi]. Yükseköğretim Kurulu Ulusal Tez Merkezi.
Year 2023, Issue: 94, 52 - 65, 24.05.2023
https://doi.org/10.17753/sosekev.1224724

Abstract

References

  • Arseven, A. (2019). Matematik öğretim yöntemleri. Pegem A Akademi.
  • Asempapa, R.S. (2019). Development and initial psychometric properties of the mathematical modeling attitude scale. School Science and Mathematics,119,14-23. https://doi.org/10.1111/ssm.12311
  • Bal, C. G., Ada, S., & Çelik, A. (2012). Bilişim sistemleri başarı modeli ve aile hekimliği bilişim sistemleri. Yönetim ve Ekonomi Dergisi, 9(1), 35-46.
  • Blum, W. (2011). Can modelling be taught and learnt? Some answers from empirical research. In G. Kaiser, W. Blum, R. Borromeo Ferri, & G. Stillman (Eds.), Trends in teaching and learning of mathematical modelling (pp. 15–30). Springer.
  • Blum, W. (2015). Quality teaching of mathematical modelling: What do we know, what can we do? In S. J. Cho (Ed.), Proceedings of the 12th International Congress on Mathematical Education: Intellectual and attitudinal challenges (pp. 73–96). Springer.
  • Blum, W., & Borromeo Ferri, R. (2009). Mathematical modelling: Can it be taught and learnt? Journal of Mathematical Modelling and Application, 1, 45–58.
  • Bryman, A., & Cramer, D. (2001). Quantitative data analysis with SPSS release 10 for Windows: A guide for social scientists. Routledge.
  • Büyüköztürk, Ş. (2002). Faktör analizi: Temel kavramlar ve ölçek geliştirmede kullanımı. Eğitim Yönetimi, 32, 470-483.
  • Büyüköztürk, Ş., Çakmak, E. K., Akgün, Ö.E., Karadeniz, Ş., & Demirel, F. (2010). Bilimsel araştırma yöntemleri (5.baskı). Pegem.
  • Chin, W. W. (1998). Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), 7–16.
  • Consortium for Mathematics and Its Applications [COMAP] and Society for Industrial and Applied Mathematics [SIAM]. (2016). Guidelines for assessment and instruction in mathematical modeling education. Retrieved from http://www.siam.org/reports/gaimme.php
  • Crouch, G. (2007). Modelling destination competitiveness. A survey and analysis of the impact of competitiveness attributes.
  • Çelik, H. C. (2017). Educational research and reviews mathematical modelling research in Turkey: A content analysis study. Educational Research and Reviews, 12(1), 19–27. https://doi.org/10.5897/ERR2016.3077
  • Field, A. (2009). Discovering statistics using SPSS (3rd ed.). Sage.
  • Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and Statistics. Journal of Marketing Research, 18(3), 382–388. https://doi.org/10.1177/002224378101800313
  • Freeze, R., & Raschke, R. L. (2007). An assessment of formative and reflective constructs in IS Research, Proceedings of the 15th European Conference on Information Systems, 1481-1492.
  • Galbraith, P. L., & Clatworthy, N. J. (1990). Beyond standard models meeting the challenge of modelling. Educational Studies in Mathematics, 21(2), 137-163.
  • Gaskin, J., Validity and Realiability, http://statwiki.gaskination.com/index.php?title=CFA#Validity_and_Reliability. Erişim tarihi: 15.11.2022
  • Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage.
  • Hambleton, R. K. (2005). Issues, Designs and Technical Guidelines for Adapting Tests Into Multiple Languages and Cultures. In R. K. Hambleton, P. F. Merenda and C. D. Spielberger (Eds.). Adapting Psychological and Educational Tests for Cross-Cultural Assessment. Lawrence Erlbaum.
  • Karasar, N. (2008). Bilimsel araştırma yöntemi. Nobel.
  • Koyuncu, I., Guzeller, C. O., & Akyuz, D. (2017). The development of a self-efficacy scale for mathematical modeling competencies. International Journal of Assessment Tools in Education, 4, 19-36. https://doi.org/10.21449/ijate.256552
  • Lesh, R. (2012). Research on models & modeling and implications for common core state curriculum standards. In R. Mayes, L. Hatfield, & S. Belbase (Eds.), WISDOMe Monograph: Quantitative reason-ing and mathematical modeling: A driver for STEM integrated edu-cation and teaching in context (Vol. 2, pp. 197–203). University of Wyoming.
  • Liu, C., Marchewka, J. T., Lu, J., & Yu, C. S. (2005). Beyond concern: A privacy-trust-behavioral intention model of electronic commerce. Information and Management, 42, 289-304.
  • Malhotra, N. K., & Dash, S. (2011). Marketing Research an Applied Orientation. Pearson.
  • National Council of Teachers of Mathematics. (2000). Principles and standards for school mathematics. Author.
  • National Council of Teachers of Mathematics. (2014). Principles to actions: Ensuring mathematical success for all. Author
  • Nunnally, J.C. (1978). Psychometric theory. McGraw-Hill.
  • Petter, S., Straub, D., & Rai, A., (2007). Specifying formative constructs in information systems research, MIS Quarterly, 31, 623-656.
  • Pollak, H. O. (2011). What is mathematical modeling? Journal of Mathematics Education at Teachers College, 2, 64-72.
  • Roberts, N., & Thatcher, J. (2009). Conceptualizing and testing formative constructs: Tutorial and annotated example. ACM sigmis database: The database for Advances in Information Systems, 40(3), 9-39.
  • Yenilmez, K., & Yıldız, Ş. (2019). Matematiksel modelleme ile ilgili lisansüstü tezlerin tematik içerik analizi. Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi, 20 (1), 1–22. https://doi.org/10.17494/ogusbd.548180
  • Yılmaz, A., Çelik, A., & Ulukapı, H. (2015). Çalışanların tinsel değerlere ilişkin algılarının iş stresi üzerindeki etkisinde birey-örgüt uyumunun aracılık rolü: Selçuk Üniversitesi Örneği. 23. Ulusal Yönetim ve Organizasyon Kongresi, 14-16 Mayıs 2015.
  • Yüksel, A. (2022). Entelektüel sermayenin yeni kuramsal yaklaşımı: İnovatif okuryazarlık (Tez No. 729939) [Doktora Tezi, Gebze Teknik Üniversitesi]. Yükseköğretim Kurulu Ulusal Tez Merkezi.

MATEMATİKSEL MODELLEME TUTUM ÖLÇEĞİ’NİN (MMTÖ) TÜRKÇE UYARLAMASI

Year 2023, Issue: 94, 52 - 65, 24.05.2023
https://doi.org/10.17753/sosekev.1224724

Abstract

Bu araştırmada Asempapa (2019) tarafından geliştirilen Matematiksel Modelleme Tutum Ölçeği’nin Türkçe’ye uyarlanması amaçlanmaktadır. Araştırmada nicel araştırma yöntemlerinden tarama modeli kullanılmış olup, araştırmanın örneklemini ise uygun örnekleme yöntemiyle belirlenen 88 öğretmen ve 157 öğretmen adayı oluşturmaktadır. Araştırmada veri toplama aracı olarak Matematiksel Modelleme Tutum Ölçeği, Matematiksel Modelleme Özyeterlik Ölçeği ve İnovatif Okuryazarlık Ölçeği kullanılmıştır. MMTÖ’nin faktör yapısını belirleyebilmek amacıyla açımlayıcı ve doğrulayıcı faktör analizleri yapılmıştır. MMTÖ’nin dört faktörlü ve 23 maddelik Türkçe uyarlamasının matematik dersine giren öğretmenlerin matematiksel modellemeye yönelik tutumlarını ölçmek için geçerli ve güvenilir bir ölçme aracı olduğu sonucuna ulaşılmıştır. Bu çalışma daha büyük bir veri seti ve farklı değişkenler kullanılarak yapılabilir.

References

  • Arseven, A. (2019). Matematik öğretim yöntemleri. Pegem A Akademi.
  • Asempapa, R.S. (2019). Development and initial psychometric properties of the mathematical modeling attitude scale. School Science and Mathematics,119,14-23. https://doi.org/10.1111/ssm.12311
  • Bal, C. G., Ada, S., & Çelik, A. (2012). Bilişim sistemleri başarı modeli ve aile hekimliği bilişim sistemleri. Yönetim ve Ekonomi Dergisi, 9(1), 35-46.
  • Blum, W. (2011). Can modelling be taught and learnt? Some answers from empirical research. In G. Kaiser, W. Blum, R. Borromeo Ferri, & G. Stillman (Eds.), Trends in teaching and learning of mathematical modelling (pp. 15–30). Springer.
  • Blum, W. (2015). Quality teaching of mathematical modelling: What do we know, what can we do? In S. J. Cho (Ed.), Proceedings of the 12th International Congress on Mathematical Education: Intellectual and attitudinal challenges (pp. 73–96). Springer.
  • Blum, W., & Borromeo Ferri, R. (2009). Mathematical modelling: Can it be taught and learnt? Journal of Mathematical Modelling and Application, 1, 45–58.
  • Bryman, A., & Cramer, D. (2001). Quantitative data analysis with SPSS release 10 for Windows: A guide for social scientists. Routledge.
  • Büyüköztürk, Ş. (2002). Faktör analizi: Temel kavramlar ve ölçek geliştirmede kullanımı. Eğitim Yönetimi, 32, 470-483.
  • Büyüköztürk, Ş., Çakmak, E. K., Akgün, Ö.E., Karadeniz, Ş., & Demirel, F. (2010). Bilimsel araştırma yöntemleri (5.baskı). Pegem.
  • Chin, W. W. (1998). Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), 7–16.
  • Consortium for Mathematics and Its Applications [COMAP] and Society for Industrial and Applied Mathematics [SIAM]. (2016). Guidelines for assessment and instruction in mathematical modeling education. Retrieved from http://www.siam.org/reports/gaimme.php
  • Crouch, G. (2007). Modelling destination competitiveness. A survey and analysis of the impact of competitiveness attributes.
  • Çelik, H. C. (2017). Educational research and reviews mathematical modelling research in Turkey: A content analysis study. Educational Research and Reviews, 12(1), 19–27. https://doi.org/10.5897/ERR2016.3077
  • Field, A. (2009). Discovering statistics using SPSS (3rd ed.). Sage.
  • Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and Statistics. Journal of Marketing Research, 18(3), 382–388. https://doi.org/10.1177/002224378101800313
  • Freeze, R., & Raschke, R. L. (2007). An assessment of formative and reflective constructs in IS Research, Proceedings of the 15th European Conference on Information Systems, 1481-1492.
  • Galbraith, P. L., & Clatworthy, N. J. (1990). Beyond standard models meeting the challenge of modelling. Educational Studies in Mathematics, 21(2), 137-163.
  • Gaskin, J., Validity and Realiability, http://statwiki.gaskination.com/index.php?title=CFA#Validity_and_Reliability. Erişim tarihi: 15.11.2022
  • Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage.
  • Hambleton, R. K. (2005). Issues, Designs and Technical Guidelines for Adapting Tests Into Multiple Languages and Cultures. In R. K. Hambleton, P. F. Merenda and C. D. Spielberger (Eds.). Adapting Psychological and Educational Tests for Cross-Cultural Assessment. Lawrence Erlbaum.
  • Karasar, N. (2008). Bilimsel araştırma yöntemi. Nobel.
  • Koyuncu, I., Guzeller, C. O., & Akyuz, D. (2017). The development of a self-efficacy scale for mathematical modeling competencies. International Journal of Assessment Tools in Education, 4, 19-36. https://doi.org/10.21449/ijate.256552
  • Lesh, R. (2012). Research on models & modeling and implications for common core state curriculum standards. In R. Mayes, L. Hatfield, & S. Belbase (Eds.), WISDOMe Monograph: Quantitative reason-ing and mathematical modeling: A driver for STEM integrated edu-cation and teaching in context (Vol. 2, pp. 197–203). University of Wyoming.
  • Liu, C., Marchewka, J. T., Lu, J., & Yu, C. S. (2005). Beyond concern: A privacy-trust-behavioral intention model of electronic commerce. Information and Management, 42, 289-304.
  • Malhotra, N. K., & Dash, S. (2011). Marketing Research an Applied Orientation. Pearson.
  • National Council of Teachers of Mathematics. (2000). Principles and standards for school mathematics. Author.
  • National Council of Teachers of Mathematics. (2014). Principles to actions: Ensuring mathematical success for all. Author
  • Nunnally, J.C. (1978). Psychometric theory. McGraw-Hill.
  • Petter, S., Straub, D., & Rai, A., (2007). Specifying formative constructs in information systems research, MIS Quarterly, 31, 623-656.
  • Pollak, H. O. (2011). What is mathematical modeling? Journal of Mathematics Education at Teachers College, 2, 64-72.
  • Roberts, N., & Thatcher, J. (2009). Conceptualizing and testing formative constructs: Tutorial and annotated example. ACM sigmis database: The database for Advances in Information Systems, 40(3), 9-39.
  • Yenilmez, K., & Yıldız, Ş. (2019). Matematiksel modelleme ile ilgili lisansüstü tezlerin tematik içerik analizi. Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi, 20 (1), 1–22. https://doi.org/10.17494/ogusbd.548180
  • Yılmaz, A., Çelik, A., & Ulukapı, H. (2015). Çalışanların tinsel değerlere ilişkin algılarının iş stresi üzerindeki etkisinde birey-örgüt uyumunun aracılık rolü: Selçuk Üniversitesi Örneği. 23. Ulusal Yönetim ve Organizasyon Kongresi, 14-16 Mayıs 2015.
  • Yüksel, A. (2022). Entelektüel sermayenin yeni kuramsal yaklaşımı: İnovatif okuryazarlık (Tez No. 729939) [Doktora Tezi, Gebze Teknik Üniversitesi]. Yükseköğretim Kurulu Ulusal Tez Merkezi.
There are 34 citations in total.

Details

Primary Language Turkish
Journal Section Articles
Authors

Barış Demir 0000-0001-6997-6413

Hülya Sert Çelik 0000-0002-5021-7449

Ayşe Arzu Arı 0000-0002-0907-2663

Gül Kaleli Yılmaz 0000-0002-1946-8901

Publication Date May 24, 2023
Published in Issue Year 2023 Issue: 94

Cite

APA Demir, B., Sert Çelik, H., Arı, A. A., Kaleli Yılmaz, G. (2023). MATEMATİKSEL MODELLEME TUTUM ÖLÇEĞİ’NİN (MMTÖ) TÜRKÇE UYARLAMASI. EKEV Akademi Dergisi(94), 52-65. https://doi.org/10.17753/sosekev.1224724