Mathematical Modelling: A Retrospective Overview

Tamer Kutluca; Deniz Kaya

doi:10.18009/jcer.1242785

TR EN

Mathematical Modelling: A Retrospective Overview

Öz

This study aims to comprehensively view the scientific articles published on mathematical modelling (MM) before 2023. In this context, analyzed articles published on MM with bibliometric analysis under four main headings; scientific productivity, network analysis, conceptual structure, and thematic map. The Web of Science database was used to analyze 906 articles published by 2039 authors representing 68 countries from 1981 to 2023. According to the study's findings, the articles published on MM differ yearly, but the number of citations is constantly increasing. Erbas, A. K., Schukajlow, S., and Kaiser, G. are the most productive authors. The most productive institutions are Purdue, Australian Catholic, and Hamburg Universities. According to the network analysis, the journals ZDM Mathematics Education and Educational Studies in Mathematics come to the fore. It was determined that the best size reduction obtained in the conceptual analysis constituted approximately 44% of the total variability. According to the findings obtained at the end of the research, made some suggestions.

Anahtar Kelimeler

A retrospective overview, bibliometric analysis, mathematical modelling, Web of Science (WoS)

Mathematical Modelling: A Retrospective Overview

Öz

This study aims to comprehensively view the scientific articles published on mathematical modelling (MM) before 2023. In this context, analyzed articles published on MM with bibliometric analysis under four main headings; scientific productivity, network analysis, conceptual structure, and thematic map. The Web of Science database was used to analyze 906 articles published by 2039 authors representing 68 countries from 1981 to 2023. According to the study's findings, the articles published on MM differ yearly, but the number of citations is constantly increasing. Erbas, A. K., Schukajlow, S., and Kaiser, G. are the most productive authors. The most productive institutions are Purdue, Australian Catholic, and Hamburg Universities. According to the network analysis, the journals ZDM Mathematics Education and Educational Studies in Mathematics come to the fore. It was determined that the best size reduction obtained in the conceptual analysis constituted approximately 44% of the total variability. According to the findings obtained at the end of the research, made some suggestions.

Anahtar Kelimeler

A retrospective overview, bibliometric analysis, mathematical modelling, Web of Science (WoS)

Kaynakça

Akgün, L., Çiltaş, A., Deniz, D., Çiftçi, Z., & Işık, A. (2013). Primary school mathematics teachers’ awareness on mathematical modelling. Adıyaman University Journal of Social Sciences, 12, 1-34. https://doi.org/10.14520/adyusbd.410
Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975.
Aztekin, S., & Şener, Z. T. (2015). The content analysis of mathematical modelling studies in Turkey: A meta-synthesis study, Education and Science, 40(178), 139-161. http://dx.doi.org/10.15390/EB.2015.4125
Bağış, M. (2021). Main analysis techniques used in bibliometric research. In Öztürk, O., & Gürler, G. (Eds.) Bibliometric analysis as a literature review tool (pp. 97-123). Ankara: Nobel Academic Publishing.
Birgin, O., & Öztürk, F. N. (2021). Research trends on mathematical modelling in mathematics education in Turkey (2010-2020): A thematic content analysis. E-International Journal of Educational Research, 12(5), 118-140. https://doi.org/10.19160/e-ijer.937654
Blomhøj, M., & Jensen, T. H. (2003). Developing mathematical modelling competence: Conceptual clarification and educational planning. Teaching Mathematics and Its Applications, 22(3), 123-139. https://doi.org/10.1093/teamat/22.3.123
Blomhøj, M., & Kjeldsen, T. H. (2006). Teaching mathematical modelling through project work. Zentralblatt für Didaktik der Mathematik, 38(2), 163-177. https://doi.org/10.1007/BF02655887
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 (pp. 73-96). New York: Springer Publishing.
Blum, W. (2011). Can modelling be taught and learnt? Some answers from empirical research. In G. Kaiser, W. Blum, F. Borromeo Ferri, & G. Stillman (Eds.), Trends in teaching and learning of mathematical modelling: ICTMA 14 (pp. 15-30). New York: Springer Publishing. https://doi.org/10.1007/978-94-007-0910-2_3
Blum, W., & Borromeo Ferri, R. (2009). Mathematical modeling: Can it be taught and learnt? Journal of Mathematical Modeling and Applications, 1(1), 45-58.

Bora, A., & Ahmed, S. (2019). Mathematical modeling: An important tool for mathematics teaching. International Journal of Research and Analytical Reviews, 6(2), 252-256.
Borromeo-Ferri, R. (2013). Mathematical modelling in European education. Journal of Mathematics Education at Teachers College, 4(2), 18-24. https://doi.org/10.7916/jmetc.v-4i2.624
Bukova-Güzel, E. (Ed.). (2021). Matematik eğitiminde matematiksel modelleme. Araştırmacılar, eğitimciler ve öğrenciler için [Mathematical modeling in mathematics education. For researchers, educators and students] (4th ed.). Ankara: Pegem Academy Publishing.
Bukova-Güzel, E. (2011). An examination of pre-service mathematics teachers’ approaches to construct and solve mathematical modelling problems. Teaching Mathematics and Its Applications, 30(1), 19-36.
Bukova Güzel, E., & Uğurel, I. (2010). The relationship between pre-service mathematics teachers’ academic achievements in calculus and their mathematical modelling approaches. Ondokuz Mayıs University Journal of Education Faculty, 29(1), 69-90.
Cetinkaya, B., Kertil, M., Erbaş, A. K., Korkmaz, H., Alacacı, C., & Cakıroğlu, E. (2016). Preservice teachers’ developing conceptions about the nature and pedagogy of mathematical modeling in the context of a mathematical modeling course. Mathematical Thinking and Learning, 18(4), 287-314. https://doi.org/10.1080/10986065.2016.1219932
Cevikbas, M., Kaiser, G., & Schukajlow, S. (2021). A systematic literature review of the current discussion on mathematical modelling competencies: state-of-the-art developments in conceptualizing, measuring, and fostering. Educational Studies in Mathematics, 109, 205-236. https://doi.org/10.1007/s10649-021-10104-6
Chen, X., Zou, D., Xie, H., & Cheng, G. (2021). Twenty years of personalized language learning: Topic modeling and knowledge mapping. Educational Technology & Society, 24(1), 205-222.
Cheng, B., Wang, M., Mørch, A. I., Chen, N. S., & Spector, J. M. (2014). Research on e-learning in the workplace 2000-2012: A bibliometric analysis of the literature. Educational Research Review, 11, 56-72. https://doi.org/10.1016/j.edurev.2014.01.001
Cirillo, M., Pelesko, J. A., Felton-Koestler, M. D., & Rubel, L. (2016). Perspectives on modeling in school mathematics. In C. R. Hirsch, & A. R. McDuffie (Eds.), Annual perspectives in mathematics education 2016: Mathematical modeling (pp. 1-14). Reston Virginia: National Council of Teachers of Mathematics.
Cobo, M., Lopez-Herrera, A., Herrera-Viedma, E., & Herrera, F. (2011). An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the fuzzy sets theory field. Journal of Informetrics, 5(1), 146–166. https://doi.org/10.1016/j.joi.2010.10.002
Common Core State Standards for Mathematics (CCSS-M) (2010). National governors association center for best practices & council of chief state school officers. Authors.
Common Core Standards Writing Team (CCSWT) (2013). Progressions for the common core state standards in mathematics. Grade 8, high school, functions. Tucson, Institute for Mathematics and Education, University of Arizona.
Çavuş Erdem, Z., & Gürbüz, R. (2018). Examining the 7th grade students’ surface area calculation knowledges and skills in mathematical modelling activities based learning environments. Adıyaman University Journal of Educational Sciences, 8, 86-115. http://doi.org/10.17984/adyuebd.468376
Daher, W. (2021). Middle school students’ motivation in solving modelling activities with technology. EURASIA Journal of Mathematics, Science and Technology Education, 17(9), 1-13. https://doi.org/10.29333/ejmste/11127
De Bakker, F. G. A, Groenewegen, P., & Den Hond, F. (2005). A bibliometric analysis of 30 years of research and theory on corporate social responsibility and corporate social performance. Business & Society, 44(3), 283-317. https://doi.org/10.1177/0007650305278-086
Didis, M. G., Erbas, A. K., Cetinkaya, B., Cakıroğlu, E., & Alacacı, C. (2016). Exploring prospective secondary mathematics teachers’ interpretation of student thinking through analysing students’ work in modelling. Mathematics Education Research Journal, 28, 349-378. https://doi.org/10.1007/s13394-016-0170-6
Dobusch, L., & Kapeller, J. (2012). A guide to paradigmatic self-marginalization: Lessons for post-Keynesian economists. Review of Political Economy, 24(3), 469-487. https://doi.org/10.1080/09538259.2012.701928
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285-296. https://doi.org/10.1016/j.jbusres.2021.04.070
Dost, Ş. (Ed.). (2019). Matematik eğitiminde modelleme etkinlikleri [Modeling activities in mathematics education]. Ankara: Pegem Academy.
Egghe, L. (1987). An exact calculation of Price’s law for the law of Lotka. Scientometrics, 11(1-2), 81-97. https://doi.org/10.1007/BF02016632
English, L. D., Fox, J. L., & Watters, J. J. (2005). Problem posing and solving with mathematical modeling. Teaching Children Mathematics, 12(3), 156-163.
English, L. D., & Watters, J. J. (2004). Mathematical modelling with young children. In M. J. Hoines & A. B Fuglestad (Eds.), Proceedings of the 28th Annual Conference of the International Group for the Psychology of Mathematics Education (pp. 335-342). Bergen, Norway: PME.
Erbas A. K., Kertil, M., Cetinkaya, B., Alacacı, C., Cakıroğlu, E., & Bas, S. (2014). Mathematical modeling in mathematics education: Basic concepts and approaches. Educational Sciences: Theory & Practice, 14(4), 15-21. https://doi.org/10.12738/estp.2014.4.2039
Fang, C., Zhang, J., & Qiu, W. (2017). Online classified advertising: A review and bibliometric analysis. Scientometrics, 113(3), 1481-1511. https://doi.org/10.1007/s11192-017-2524-6
Frejd, P., & Bergsten, C. (2018). Professional modellers’ conceptions of the notion of mathematical modelling: Ideas for education. ZDM-Mathematics Education, 50(1-2), 117-127. https://doi.org/10.1007/s11858-018-0928-2
Gainsburg, J. (2013). Learning to model in engineering. Mathematical Thinking and Learning, 15(4), 259-290. https://doi.org/10.1080/10986065.2013.830947
Galbraith, P. (2012). Models of modelling: Genres, purposes or perspectives. Journal of Mathematical Modeling and Application, 1(5), 3-16.
Glotzl, F., & Aigner, E. (2018). Orthodox core-heterodox periphery? Contrasting citation networks of economics departments in Vienna. Review of Political Economy, 30(2), 210-240. https://doi.org/10.1080/09538259.2018.1449619
Gonzales-Valiente, C. (2019). Redes de citación de revistas iberoamericanas de bibliotecología y ciencia de la información en Scopus. Bibliotecas Anales de Investigación, 19(1), 83-98. https://doi.org/10.6084/m9.figshare.7415375.v1
Gravemeijer, K. (2002). Preamble: From models to modeling. In Gravemeijer, K. P., Lehrer, R., van Oers, H. J., &Verschaffel, L. (Eds.), Symbolizing, modeling and tool use in mathematics education (pp. 7-22). New York: Springer Publishing.
Greefrath, G., Siller, H. S., Vorhölter, K., & Kaiser, G. (2022). Mathematical modelling and discrete mathematics: Opportunities for modern mathematics teaching. ZDM-Mathematics Education, 54(4), 865-879. https://doi.org/10.1007/s11858-022-01339-5
Grzybowska, K., & Awasthi, A. (2020). Literature review on sustainable logistics and sustainable production for industry 4.0. In K., Grzybowska, A., Awasthi, & R., Sawhney (Eds.), Sustainable logistics and production in industry 4.0 new opportunities and challenges (pp. 1-19). New York: Springer Publishing.
Haines, C. R., & Crouch, R. (2010). Remarks on a modeling cycle and interpreting behaviours. In R. Lesh, P. L. Galbraith, C. R. Haines, & A. Hurford (Eds.), Modeling students’ mathematical modeling competencies: ICTMA 13 (pp. 145-154). New York: Springer Publishing. https://doi.org/10.1007/978-1-4419-0561-1
Hıdıroğlu, Ç. N., Tekin-Dede, A., Kula-Ünver, S., & Bukova-Güzel, E. (2017). Mathematics student teachers’ modelling approaches while solving the designed eşme rug problem. EURASIA Journal of Mathematics Science and Technology Education, 13(3), 873-892.
Jiang, Y., Ritchie, B., & Benckendorff, P. (2019). Bibliometric visualisation: An application in tourism crisis and disaster management research. Current Issues in Tourism, 22(16), 1925-1957. https://doi.org/10.1080/13683500.2017.1408574
Jing, S., Qinghua, Z., & Landström, H. (2015). Entrepreneurship across regions: Internationalization and/or contextualization? In Handbook of research on Global competitive advantage through innovation and entrepreneurship (pp. 372-392). Pennsylvania: IGI Global Publishing.
Kandemir, M. A. (2011). Modelleme etkinliklerinin öğrencilerin duyuşsal özelliklerine problem çözme ve teknolojiye ilişkin düşüncelerine etkisinin incelenmesi [Analysis of the effect of modelling activities on students? affective features and thoughts on problem solving and technology] (Unpublished doctoral dissertation). Balıkesir University.
Kaya, D., & Keşan, C. (2022). Mathematical modelling processes of elementary mathematics teacher candidates: An example of waste of water. Van Yüzüncü Yıl University Journal of Education, 19(3), 1068-1097. https://doi.org/10.33711/yyuefd.1177845
Kumar, S., & Jan, J. M. (2014). Research collaboration networks of two OIC nations: Comparative study between Turkey and Malaysia in the field of 'energy fuels', 2009-2011. Scientometrics, 98, 387-414. https://doi.org/10.1007/s11192-013-1059-8
Kaiser, G. (2020). Mathematical modelling and applications in education. In S. Lerman (Ed.), Encyclopedia of mathematics education (pp. 553-561). New York: Springer Publishing.
Kaiser, G. (2017). The teaching and learning of mathematical modelling. In J. Cai (Ed.), Compendium for research in mathematics education (pp. 267-291). Reston Virginia: National Council of Teachers of Mathematics.
Kaiser, G., & Brand, S. (2015). Modelling competencies: Past development and further perspectives. In G. A. Stillman, W. Blum, & M. S. Biembengut (Eds.), Mathematical modelling in education research and practice (pp. 129-149). New York: Springer Publishing.
Kaiser, G., & Sriraman, B. (2006). A global survey of international perspectives on modelling in mathematics education. ZDM-Mathematics Education, 38(3), 302-310.
Kertil, M., Erbas, A. K., & Cetinkaya, B. (2017). Pre-service elementary mathematics teachers’ ways of thinking about rate of change in the context of a modeling activity. Turkish Journal of Computer and Mathematics Education, 8(1), 188-217.
Kim, S. H., & Kim, S. (2010). The effects of mathematical modeling on creative production ability and self-directed learning attitude. Asia Pasific Education Review, 11, 109-120.
Law, J., Bauin, S., Courtial, J., & Wittaker, J. (1988). Policy and the mapping of scientific change: A co-word analysis of research into environmental acidification. Scientometrics, 14(3-4), 251-264. https://doi.org/10.1007/BF02020078 Lesh, R., & Harel, G. (2003). Problem solving, modeling, and local conceptual development. Mathematical Thinking and Learning, 5(2-3), 157–189.
Lesh, R., & Doerr, H. M. (2003). Foundations of a models and modeling perspective on mathematics teaching, learning, and problem solving. In R. Lesh, & H. M. Doerr (Eds.), Beyond constructivism: Models and modeling perspectives on mathematics problem solving, learning, and teaching (pp. 3-33). Mahwah, NJ: Lawrence Erlbaum Associates.
Lesh, R., & Lehrer, R. (2003). Models and modeling perspectives on the development of students and teachers. Mathematical Thinking and Learning, 5(2&3), 109-129.
Liao, H., Tang, M., Li, Z., & Lev, B. (2019). Bibliometric analysis for highly cited papers in operations research and management science from 2008 to 2017 based on essential science indicators. Omega, 88, 223-236. https://doi.org/10.1016/j.omega.2018.11.005
Lingefjärd, T. (2006). Faces of mathematical modeling. ZDM-Mathematics Education, 38(2), 96-112. https://doi.org/10.1007/BF02655884
Lu, X., & Kaiser, G. (2021). Creativity in students’ modelling competencies: Conceptualisation and measurement. Educational Studies in Mathematics, 109, 287-311.
Maaβ, K. (2006). What are modelling competencies? Zentralblatt für Didaktik der Mathematik, 38(2), 113-142. https://doi.org/10.1007/BF02655885
Martínez, M. A., Cobo, M. J., Herrera, M., & Herrera-Viedma, E. (2015). Analyzing the scientific evolution of social work using science mapping. Research on Social Work Practice, 25(2), 257-277. https://doi.org/10.1177/1049731514522101
Michelsen, C. (2006). Functions: a modelling tool in mathematics and science. Zentralblatt für Didaktik der Mathematik, 38(3), 269-280. https://doi.org/10.1007/BF02652810
Ministry of National Education (MoNE) (2018). Matematik dersi öğretim programı (ilkokul ve ortaokul 3, 4, 5, 6, 7 ve 8. sınıflar) [Mathematics lesson curriculum (primary and middle school 3, 4, 5, 6, 7 and 8th grades)]. Ankara: Ministry of National Education.
Mostafa, M. M. (2022). Three decades of interactive learning environments: A retrospective bibliometric network analysis. Interactive Learning Environments. (Press)
Mostafa, M. M. (2020). A knowledge domain visualization review of thirty years of halal food research: Themes, trends and knowledge structure. Trends in Food Science & Technology, 99, 660-677. https://doi.org/10.1016/j.tifs.2020.03.022
National Council of Teachers of Mathematics (NCTM) (2016). Executive summary: principles and standards for school mathematics. Author, Reston, Virgina: NCTM.
National Council of Teachers of Mathematics (NCTM) (2014). Principles to actions: Ensuring mathematical success for all. Author, Reston, Virgina: NCTM.
National Council of Teachers of Mathematics (NCTM) (2000). Principles and standards for school mathematics. Author, Reston, Virgina: NCTM.
Niss, M., & Blum, W. (2020). The learning and teaching of mathematical modelling. London: Routledge Publishing.
Niss, M., & Højgaard, T. (2019). Mathematical competencies revisited. Educational Studies in Mathematics, 102, 9-28. https://doi.org/10.1007/s10649-019-09903-9
Novak, E., Daday, J., & McDaniel, K. (2018). Using a mathematical model of motivation, volition, and performance to examine students’ e-text learning experiences. Education Tech Research Dev, 66, 1189-1209. https://doi.org/10.1007/s11423-018-9599-5
Park, S., Lim, Y., & Park, H. (2015). Comparing Twitter and YouTube networks in information diffusion: The case of the "occupy wall street" movement. Technological Forecasting and Social Change, 95, 208-217. https://doi.org/10.1016/j.techfore.2015.02.003
Pollak, H. O. (2003). A history of the teaching of modelling. In G. Stanic & J. Kilpatrick (Eds.), A history of school mathematics (pp. 647-671). Reston, Virgina: NCTM.
Qian, J., Law, R., & Wei, J. (2019). Knowledge mapping in travel website studies: A scientometric review. Scandinavian Journal of Hospitality and Tourism, 19(2), 192-209.
Schukajlow, S., Kolter, J., & Blum, W. (2015). Scafolding mathematical modelling with a solution plan. ZDM-Mathematics Education, 47(7), 1241-1254.
Sokolowski, A. (2015). The effects of mathematical modelling on students’ achievement-meta-analysis of research. The IAFOR Journal of Education, 3(1), 93-114.
Sriraman, B. (2009). The characteristics of mathematical creativity. ZDM-Mathematics Education, 41(1-2), 13-27. https://10.1007/s11858-008-0114-z
Stillman, G., Kaiser, G., & Lampen, C. E. (Eds.). (2020). Mathematical modelling education and sense-making. New York: Springer Publishing. https://doi.org/10.1007/978-3-030-37673-4
Swetz, F., & Hartzler, J. S. (1991). Mathematical modeling in the secondary school curriculum: A resource guide of classroom exercises. Reston, Virgina: NCTM.
Van Eck N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523-538.
Verbeek, A., Debackere, K., Luwel, M., & Zimmermann, E. (2002). Measuring progress and evolution in science and technology-I: the multiple uses of bibliometric indicators. International Journal of Management Reviews, 4(2), 179-211.
Verschaffel, L., Greer, B., & De Corte, E. (2002). Everyday knowledge and mathematical modeling of school word problems. In K. P. Gravemeijer, R. Lehrer, H. J. van Oers, & L. Verschaffel (Eds.), Symbolizing, modeling and tool use in mathematics education (pp. 171-195). New York: Kluwer Academic Publishers.
Vidgen, R., Henneberg, S., & Naude, P. (2007). What sort of community is the European Conference on Information Systems? A social network analysis 1993-2005. European Journal of Information Systems, 16, 5-19.
Vorhölter, K., Greefrath, G., Borromeo-Ferri, R., Leiß, D., & Schukajlow, S. (2019). Mathematical modelling. In H. N. Jahnke & L. Hefendehl-Hebeker (Eds.), Traditions in German-speaking mathematics education research (pp. 91-114). New York: Springer Publishing. https://doi.org/10.1007/978-3-030-11069-7_4
Web of Science Group (WoSG) (2022). Web of Science Core Collection. Retrieved from https://clarivate.com/ Wessels, H. (2014). Levels of mathematical creativity in model-eliciting activities. Journal of Mathematical Modelling and Application, 1(9), 22-40.
Wetzstein, A., Feisel, E., Hartmann, E., & Benton, W. (2019). Uncovering the supplier selection knowledge structure: A systematic citation network analysis from 1991 to 2017. Journal of Purchasing and Supply Management, 25, 1-16.
Wong, W., Mittas, N., Arvanitou, E., & Li, Y. (2021). A bibliometric assessment of software engineering themes, scholars and institutions (2013-2020). Journal of Systems and Software, 180, 1-10. https://doi.org/10.1016/j.jss.2021.111029
Xu, B., Lu, X., Yang, X., & Bao, J. (2022). Mathematicians’, mathematics educators’, and mathematics teachers’ professional conceptions of the school learning of mathematical modelling in China. ZDM-Mathematics Education, 54(3), 679-691.
Yıldız, Ş., & Yenilmez, K. (2019). Thematic content analysis of graduate theses related to mathematical modelling. Eskişehir Osmangazi University Journal of Social Sciences, 20, 1-22. https://doi.org/10.17494/ogusbd.548180
Ziebek, R. M., & Conner, A. (2006). Beyond motivation: Exploring mathematical modeling as a context for deepening students' understandings of curricular mathematics. Educational Studies in Mathematics, 63(1), 89-112
Zhao, D., & Strotmann, A. (2015). Analysis and visualization of citation networks. Synthesis Lectures on Information Concepts, Retrieval, and Services 7(1), 1-207.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Alan Eğitimleri

Bölüm

Araştırma Makalesi

Yazarlar

Tamer Kutluca
0000-0003-0730-5248
Türkiye

Deniz Kaya ^*
0000-0002-7804-1772
Türkiye

Yayımlanma Tarihi

21 Mart 2023

Gönderilme Tarihi

26 Ocak 2023

Kabul Tarihi

7 Mart 2023

Yayımlandığı Sayı

Yıl 2023 Cilt: 11 Sayı: 21

DOI

https://doi.org/10.18009/jcer.1242785

IZ

https://izlik.org/JA83MN73GD

APA

Kutluca, T., & Kaya, D. (2023). Mathematical Modelling: A Retrospective Overview. Journal of Computer and Education Research, 11(21), 240-274. https://doi.org/10.18009/jcer.1242785

AMA

1.Kutluca T, Kaya D. Mathematical Modelling: A Retrospective Overview. JCER. 2023;11(21):240-274. doi:10.18009/jcer.1242785

Chicago

Kutluca, Tamer, ve Deniz Kaya. 2023. “Mathematical Modelling: A Retrospective Overview”. Journal of Computer and Education Research 11 (21): 240-74. https://doi.org/10.18009/jcer.1242785.

EndNote

Kutluca T, Kaya D (01 Mart 2023) Mathematical Modelling: A Retrospective Overview. Journal of Computer and Education Research 11 21 240–274.

IEEE

[1]T. Kutluca ve D. Kaya, “Mathematical Modelling: A Retrospective Overview”, JCER, c. 11, sy 21, ss. 240–274, Mar. 2023, doi: 10.18009/jcer.1242785.

ISNAD

Kutluca, Tamer - Kaya, Deniz. “Mathematical Modelling: A Retrospective Overview”. Journal of Computer and Education Research 11/21 (01 Mart 2023): 240-274. https://doi.org/10.18009/jcer.1242785.

JAMA

1.Kutluca T, Kaya D. Mathematical Modelling: A Retrospective Overview. JCER. 2023;11:240–274.

MLA

Kutluca, Tamer, ve Deniz Kaya. “Mathematical Modelling: A Retrospective Overview”. Journal of Computer and Education Research, c. 11, sy 21, Mart 2023, ss. 240-74, doi:10.18009/jcer.1242785.

Vancouver

1.Tamer Kutluca, Deniz Kaya. Mathematical Modelling: A Retrospective Overview. JCER. 01 Mart 2023;11(21):240-74. doi:10.18009/jcer.1242785

Cited By

Examining 5th Grade Students' Learning on Surface Area Calculations with Realistic Mathematics Education Approach

International e-Journal of Educational Studies

https://doi.org/10.31458/iejes.1354835

Teacher and Student Opinions on Teaching Four Operations with Integer Numbers in 7th Grade with Counting Stamps

International e-Journal of Educational Studies

https://doi.org/10.31458/iejes.1343835

An Investigation into Secondary School Students' Skills in Using Symbols, Operations, Concepts and Rules in Mathematical Modeling Applications

Sınırsız Eğitim ve Araştırma Dergisi

https://doi.org/10.29250/sead.1508427

Investigation of Middle School Math Teachers’ Pedagogical Preferences towards Using Models in the Context of Different Fraction Schemes

International e-Journal of Educational Studies

https://doi.org/10.31458/iejes.1556591

Mathematical modeling in education: contributions and visibility of an Argentine research group

ZDM – Mathematics Education

https://doi.org/10.1007/s11858-025-01733-9

MATHEMATICAL MODELING OF FACTORS OF EFFICIENCY OF LAND USE OF REGIONS

AUTOMOBILE ROADS AND ROAD CONSTRUCTION

https://doi.org/10.33744/0365-8171-2025-117.1-157-165

Exploring the Mathematical Modeling Skills of Pre-Service Elementary Mathematics Teachers Through an Artificial Intelligence Tool: The Case of ChatGPT

e-Kafkas Eğitim Araştırmaları Dergisi

https://doi.org/10.30900/kafkasegt.1744372

Bu eser Creative Commons Atıf 4.0 Uluslararası Lisansı ile lisanslanmıştır.

Değerli Yazarlar,

JCER dergisi 2018 yılından itibaren yayımlanacak sayılarda yazarlarından ORCID bilgilerini isteyecektir. Bu konuda hassasiyet göstermeniz önemle rica olunur.

Önemli: "Yazar adından yapılan yayın/atıf taramalarında isim benzerlikleri, soyadı değişikliği, Türkçe harf içeren isimler, farklı yazımlar, kurum değişiklikleri gibi durumlar sorun oluşturabilmektedir. Bu nedenle araştırmacıların tanımlayıcı kimlik/numara (ID) edinmeleri önem taşımaktadır. ULAKBİM TR Dizin sistemlerinde tanımlayıcı ID bilgilerine yer verilecektir.

Standardizasyonun sağlanabilmesi ve YÖK ile birlikte yürütülecek ortak çalışmalarda ORCID kullanılacağı için, TR Dizin’de yer alan veya yer almak üzere başvuran dergilerin, yazarlardan ORCID bilgilerini talep etmeleri ve dergide/makalelerde bu bilgiye yer vermeleri tavsiye edilmektedir. ORCID, Open Researcher ve Contributor ID'nin kısaltmasıdır. ORCID, Uluslararası Standart Ad Tanımlayıcı (ISNI) olarak da bilinen ISO Standardı (ISO 27729) ile uyumlu 16 haneli bir numaralı bir URI'dir. http://orcid.org adresinden bireysel ORCID için ücretsiz kayıt oluşturabilirsiniz. "

Mathematical Modelling: A Retrospective Overview

Öz

Anahtar Kelimeler

Mathematical Modelling: A Retrospective Overview

Öz

Anahtar Kelimeler

Kaynakça

Ayrıntılar

Birincil Dil

Konular

Bölüm

Yazarlar

Yayımlanma Tarihi

Gönderilme Tarihi

Kabul Tarihi

Yayımlandığı Sayı

DOI

IZ

Kaynak Göster

Cited By

Examining 5th Grade Students' Learning on Surface Area Calculations with Realistic Mathematics Education Approach

Teacher and Student Opinions on Teaching Four Operations with Integer Numbers in 7th Grade with Counting Stamps

An Investigation into Secondary School Students' Skills in Using Symbols, Operations, Concepts and Rules in Mathematical Modeling Applications

Investigation of Middle School Math Teachers’ Pedagogical Preferences towards Using Models in the Context of Different Fraction Schemes

Mathematical modeling in education: contributions and visibility of an Argentine research group

MATHEMATICAL MODELING OF FACTORS OF EFFICIENCY OF LAND USE OF REGIONS

Exploring the Mathematical Modeling Skills of Pre-Service Elementary Mathematics Teachers Through an Artificial Intelligence Tool: The Case of ChatGPT