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Mathematical Modelling: A Retrospective Overview

Year 2023, Volume: 11 Issue: 21, 240 - 274, 21.03.2023
https://doi.org/10.18009/jcer.1242785

Abstract

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.

References

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  • 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.
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Mathematical Modelling: A Retrospective Overview

Year 2023, Volume: 11 Issue: 21, 240 - 274, 21.03.2023
https://doi.org/10.18009/jcer.1242785

Abstract

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.

References

  • 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
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Details

Primary Language English
Subjects Other Fields of Education
Journal Section Research Article
Authors

Tamer Kutluca 0000-0003-0730-5248

Deniz Kaya 0000-0002-7804-1772

Early Pub Date March 14, 2023
Publication Date March 21, 2023
Submission Date January 26, 2023
Acceptance Date March 7, 2023
Published in Issue Year 2023 Volume: 11 Issue: 21

Cite

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

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