___

• 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.