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Matematik Eğitiminde Matematiksel Modelleme Araştırmalarının Bibliyometrik Analizi

Yıl 2025, Cilt: 61 Sayı: 61, 1 - 32

Öz

Birçok alanda olduğu gibi matematik eğitimi alanında da kapsayıcı ve özetleyici derleme çalışmaları bu alanda yapılacak çalışmalar için önemli bir yere sahiptir. Böylelikle araştırmacılar özellikle en çok çalışılan konular ve SSCI ve SCI- Extended indeksli dergilerde yayınlanan çalışmalara tek bir kaynaktan erişerek araştırma süreçlerini daha etkin yönetebilmektedir. Bu çalışmada da 2003-2023 yılları arasında matematiksel modelleme konusunda yapılan nitelikli çalışmaların bibliyometrik haritası sunulmuştur. Web of Science veritabanında taranan araştırma ve derleme çalışmaları belirlenen kriterler çerçevesinde incelenmiş ve 178 dokümana ulaşılmıştır. Sonuçlara göre matematik eğitimindeki matematiksel modelleme çalışmaları giderek artmaktadır. Çalışmaların büyük bir bölümünün araştırma makalesi olduğu tespit edilmiştir. Araştırmanın ortaya koyduğu önemli sonuçlardan biri matematiksel modelleme süreci üzerine yapılan çalışmaların problem kurma çalışmalarına nazaran daha yoğun olmasıdır. Sonuçlar sistematik derlemeler, meta-analizler ve bibliyometrik analizler gibi derleme çalışmalarına ihtiyaç olduğunu göstermektedir. Bununla birlikte araştırma makalelerinde problem kurma çalışmalarına biraz daha yer verilmesi önerilebilir.

Kaynakça

  • Blum, W., & Niss, M. (1991). Applied mathematical problem solving, modelling, applications, and links to other subjects—State, trends and issues in mathematics instruction. Educational Studies in Mathematics, 22(1), 37-68. https://doi.org/10.1007/BF00302716
  • Borromeo Ferri, R. (2018). Learning how to teach mathematical modeling in school and teacher education.Springer.
  • Borromeo Ferri, R., Kaiser, G., & Paquet, M. (2023). Meeting the challenge of heterogeneity through the self-differentiation potential of mathematical modeling problems. In Mathematical Challenges For All (pp. 409-429). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-031-18868-8_22
  • Cevikbas, M., Kaiser, G., & Schukajlow, S. (2022). 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(2), 205-236. https://doi.org/10.1007/s10649-021-10104-6
  • Cevikbas, M., Kaiser, G., & Schukajlow, S. (2024). Trends in mathematics education and insights from a meta-review and bibliometric analysis of review studies. ZDM–Mathematics Education, 1-24. https://doi.org/10.1007/s11858-024-01587-7
  • Cobo, M. J., López‐Herrera, A. G., Herrera‐Viedma, E., & Herrera, F. (2011). Science mapping software tools: Review, analysis, and cooperative study among tools. Journal of the American Society for information Science and Technology, 62(7), 1382-1402. https://doi.org/10.1002/asi.21525
  • *Degrande, T., Van Hoof, J., Verschaffel, L., & Van Dooren, W. (2018). Open word problems: taking the additive or the multiplicative road?. ZDM–Mathematics Education, 50, 91-102. https://doi.org/10.1007/s11858-017-0900-6
  • 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
  • Donthu, N., Reinartz, W., Kumar, S., & Pattnaik, D. (2021). A retrospective review of the first 35 years of the International Journal of Research in Marketing. International Journal of Research in Marketing, 38(1), 232-269. https://doi.org/10.1016/j.ijresmar.2020.10.006
  • English, L. D. (2020). Teaching and learning through mathematical problem posing: Commentary. International Journal of Educational Research, 102, 101451. https://doi.org/10.1016/j.ijer.2019.06.014
  • Hartmann, L. M., Krawitz, J., & Schukajlow, S. (2021). Create your own problem! When given descriptions of real-world situations, do students pose and solve modelling problems?. ZDM–Mathematics Education, 53(4), 919-935. https://doi.org/10.1007/s11858-021-01224-7
  • Kaiser, G., & Schukajlow, S. (2024). Literature reviews in mathematics education and their significance to the field. ZDM–Mathematics Education, 56(1), 1-3. https://doi.org/10.1007/s11858-023-01541-z
  • Kaiser, G., & Sriraman, B. (2006). A global survey of international perspectives on modelling in mathematics education. ZDM–The International Journal on Mathematics Education,, 38, 302-310. https://doi.org/10.1007/BF02652813
  • Krawitz, J., Chang, Y. P., Yang, K. L., & Schukajlow, S. (2022). The role of reading comprehension in mathematical modelling: improving the construction of a real-world model and interest in Germany and Taiwan. Educational Studies in Mathematics, 109(2), 337-359. https://doi.org/10.1007/s10649-021-10058-9
  • Lehrer, R., & English, L. (2018). Introducing children to modeling variability. International handbook of research in statistics education, 229-260. https://doi.org/10.1007/978-3-319-66195-7_7
  • Lesh, R. & Zawojewski, J.S. (2007). Problem solving and modeling. In F. Lester (Ed.), Second handbook of research on mathematics teaching and learning (pp. 763–804). Greenwich, CT: Information Age Publishing.
  • Maaß, K. (2007). Modelling in class: What do we want the students to learn. Mathematical modelling: Education, engineering and economics, 63-78.
  • *Paolucci, C., & Wessels, H. (2017). An examination of preservice teachers’ capacity to create mathematical modeling problems for children. Journal of Teacher Education, 68(3), 330-344. https://doi.org/10.1177/0022487117697636
  • Polya, G. (1944). How to solve it. Garden City, NY: Doubleday.
  • Pritchard, R. D. (1969). Equity theory: A review and critique. Organizational behavior and human performance, 4(2), 176-211. https://doi.org/10.1016/0030-5073(69)90005-1
  • Rellensmann, J., Schukajlow, S., & Leopold, C. (2017). Make a drawing. Effects of strategic knowledge, drawing accuracy, and type of drawing on students’ mathematical modelling performance. Educational Studies in Mathematics, 95, 53-78. https://doi.org/10.1007/s10649-016-9736-1
  • Rellensmann, J., Schukajlow, S., & Leopold, C. (2020). Measuring and investigating strategic knowledge about drawing to solve geometry modelling problems. ZDM–Mathematics Education, 52, 97-110. https://doi.org/10.1007/s11858-019-01085-1
  • Rellensmann, J., Schukajlow, S., Blomberg, J., & Leopold, C. (2023). Does strategic knowledge matter? Effects of strategic knowledge about drawing on students’ modeling competencies in the domain of geometry. Mathematical Thinking and Learning, 25(3), 296-316. https://doi.org/10.1080/10986065.2021.2012741
  • Sahin, S. (2019). Matematik öğretmenlerinin matematiksel modelleme problemi hazırlama becerilerinin incelenmesi [Investigation of mathematical modeling problem posing competencies of mathematics teachers] [Unpublished doctoral dissertation]. Adıyaman University.
  • Sahin, S., Gürbüz, R., & Doğan, M. F. (2023). Investigating Mathematical Modeling Problem Designing Process of Inservice Mathematics Teachers. Cukurova University Faculty of Education Journal, 52(1), 33-70. https://doi.org/10.14812/cuefd.1033080
  • Schukajlow, S., Kaiser, G., & Stillman, G. (2018). Empirical research on teaching and learning of mathematical modelling: A survey on the current state-of-the-art. ZDM–Mathematics Education, 50, 5-18. https://doi.org/10.1007/s11858-018-0933-5
  • Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of business research, 104, 333-339. https://doi.org/10.1016/j.jbusres.2019.07.039
  • Sokolowski, A. (2015). The Effects of Mathematical Modelling on Students' Achievement-Meta-Analysis of Research. IAFOR Journal of Education, 3(1), 93-114.
  • Tosun, C. (2024). Analysis of the last 40 years of science education research via bibliometric methods. Science & Education, 33(2), 451-480. https://doi.org/10.1007/s11191-022-00400-9
  • Van Dooren, W., De Bock, D., Evers, M., & Verschaffel, L. (2009). Students' overuse of proportionality on missing-value problems: How numbers may change solutions. Journal for Research in Mathematics Education, 40(2), 187-211. https://doi.org/10.2307/40539331
  • Van Dooren, W., De Bock, D., Janssens, D., & Verschaffel, L. (2008). The linear imperative: An inventory and conceptual analysis of students' overuse of linearity. Journal for Research in Mathematics Education, 39(3), 311-342. https://doi.org/10.2307/30034972
  • Van Eck, N., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. scientometrics, 84(2), 523-538. https://doi.org/10.1007/s11192-009-0146-3
  • Verma, S., & Gustafsson, A. (2020). Investigating the emerging COVID-19 research trends in the field of business and management: A bibliometric analysis approach. Journal of business research, 118, 253-261. https://doi.org/10.1016/j.jbusres.2020.06.057
  • *Verschaffel, L., Schukajlow, S., Star, J., & Van Dooren, W. (2020). Word problems in mathematics education: A survey. ZDM–Mathematics Education, 52, 1-16. https://doi.org/10.1007/s11858-020-01130-4
  • *Villarreal, M. E., Esteley, C. B., & Smith, S. (2018). Pre-service teachers’ experiences within modelling scenarios enriched by digital technologies. ZDM–Mathematics Education, 50, 327-341. https://doi.org/10.1007/s11858-018-0925-5
  • Yükseköğretim Kurulu (2018a). İlköğretim Matematik Öğretmenliği Lisans Programı, Ankara.
  • Yükseköğretim Kurulu (2018b). Ortaöğretim Matematik Öğretmenliği Lisans Programı, Ankara.

Bibliometric Analysis of Mathematical Modeling Research in Mathematics Education

Yıl 2025, Cilt: 61 Sayı: 61, 1 - 32

Öz

In the field of mathematics education, as in many other fields, comprehensive and summative review studies are an important part of the research that needs to be done in the field. In this way, researchers can manage their research processes with greater efficacy by accessing the most studied topics and studies published in SSCI and SCI-Expanded indexed journals from a single source. This study presents a bibliometric map of qualified studies on mathematical modeling between 2003 and 2023. After searching Web of Science, 178 articles and reviews were identified. According to the results, studies on mathematical modeling in mathematics education have increased over the years. It was found that most of the studies were research articles. One of the key results of the study is that research on the mathematical modeling process is more prevalent than research on problem-posing. The results suggest that there is a need for review studies such as systematic reviews, meta-analyses, and bibliometric analyses. In addition, it can be suggested that problem-posing studies should be included more in research articles.

Kaynakça

  • Blum, W., & Niss, M. (1991). Applied mathematical problem solving, modelling, applications, and links to other subjects—State, trends and issues in mathematics instruction. Educational Studies in Mathematics, 22(1), 37-68. https://doi.org/10.1007/BF00302716
  • Borromeo Ferri, R. (2018). Learning how to teach mathematical modeling in school and teacher education.Springer.
  • Borromeo Ferri, R., Kaiser, G., & Paquet, M. (2023). Meeting the challenge of heterogeneity through the self-differentiation potential of mathematical modeling problems. In Mathematical Challenges For All (pp. 409-429). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-031-18868-8_22
  • Cevikbas, M., Kaiser, G., & Schukajlow, S. (2022). 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(2), 205-236. https://doi.org/10.1007/s10649-021-10104-6
  • Cevikbas, M., Kaiser, G., & Schukajlow, S. (2024). Trends in mathematics education and insights from a meta-review and bibliometric analysis of review studies. ZDM–Mathematics Education, 1-24. https://doi.org/10.1007/s11858-024-01587-7
  • Cobo, M. J., López‐Herrera, A. G., Herrera‐Viedma, E., & Herrera, F. (2011). Science mapping software tools: Review, analysis, and cooperative study among tools. Journal of the American Society for information Science and Technology, 62(7), 1382-1402. https://doi.org/10.1002/asi.21525
  • *Degrande, T., Van Hoof, J., Verschaffel, L., & Van Dooren, W. (2018). Open word problems: taking the additive or the multiplicative road?. ZDM–Mathematics Education, 50, 91-102. https://doi.org/10.1007/s11858-017-0900-6
  • 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
  • Donthu, N., Reinartz, W., Kumar, S., & Pattnaik, D. (2021). A retrospective review of the first 35 years of the International Journal of Research in Marketing. International Journal of Research in Marketing, 38(1), 232-269. https://doi.org/10.1016/j.ijresmar.2020.10.006
  • English, L. D. (2020). Teaching and learning through mathematical problem posing: Commentary. International Journal of Educational Research, 102, 101451. https://doi.org/10.1016/j.ijer.2019.06.014
  • Hartmann, L. M., Krawitz, J., & Schukajlow, S. (2021). Create your own problem! When given descriptions of real-world situations, do students pose and solve modelling problems?. ZDM–Mathematics Education, 53(4), 919-935. https://doi.org/10.1007/s11858-021-01224-7
  • Kaiser, G., & Schukajlow, S. (2024). Literature reviews in mathematics education and their significance to the field. ZDM–Mathematics Education, 56(1), 1-3. https://doi.org/10.1007/s11858-023-01541-z
  • Kaiser, G., & Sriraman, B. (2006). A global survey of international perspectives on modelling in mathematics education. ZDM–The International Journal on Mathematics Education,, 38, 302-310. https://doi.org/10.1007/BF02652813
  • Krawitz, J., Chang, Y. P., Yang, K. L., & Schukajlow, S. (2022). The role of reading comprehension in mathematical modelling: improving the construction of a real-world model and interest in Germany and Taiwan. Educational Studies in Mathematics, 109(2), 337-359. https://doi.org/10.1007/s10649-021-10058-9
  • Lehrer, R., & English, L. (2018). Introducing children to modeling variability. International handbook of research in statistics education, 229-260. https://doi.org/10.1007/978-3-319-66195-7_7
  • Lesh, R. & Zawojewski, J.S. (2007). Problem solving and modeling. In F. Lester (Ed.), Second handbook of research on mathematics teaching and learning (pp. 763–804). Greenwich, CT: Information Age Publishing.
  • Maaß, K. (2007). Modelling in class: What do we want the students to learn. Mathematical modelling: Education, engineering and economics, 63-78.
  • *Paolucci, C., & Wessels, H. (2017). An examination of preservice teachers’ capacity to create mathematical modeling problems for children. Journal of Teacher Education, 68(3), 330-344. https://doi.org/10.1177/0022487117697636
  • Polya, G. (1944). How to solve it. Garden City, NY: Doubleday.
  • Pritchard, R. D. (1969). Equity theory: A review and critique. Organizational behavior and human performance, 4(2), 176-211. https://doi.org/10.1016/0030-5073(69)90005-1
  • Rellensmann, J., Schukajlow, S., & Leopold, C. (2017). Make a drawing. Effects of strategic knowledge, drawing accuracy, and type of drawing on students’ mathematical modelling performance. Educational Studies in Mathematics, 95, 53-78. https://doi.org/10.1007/s10649-016-9736-1
  • Rellensmann, J., Schukajlow, S., & Leopold, C. (2020). Measuring and investigating strategic knowledge about drawing to solve geometry modelling problems. ZDM–Mathematics Education, 52, 97-110. https://doi.org/10.1007/s11858-019-01085-1
  • Rellensmann, J., Schukajlow, S., Blomberg, J., & Leopold, C. (2023). Does strategic knowledge matter? Effects of strategic knowledge about drawing on students’ modeling competencies in the domain of geometry. Mathematical Thinking and Learning, 25(3), 296-316. https://doi.org/10.1080/10986065.2021.2012741
  • Sahin, S. (2019). Matematik öğretmenlerinin matematiksel modelleme problemi hazırlama becerilerinin incelenmesi [Investigation of mathematical modeling problem posing competencies of mathematics teachers] [Unpublished doctoral dissertation]. Adıyaman University.
  • Sahin, S., Gürbüz, R., & Doğan, M. F. (2023). Investigating Mathematical Modeling Problem Designing Process of Inservice Mathematics Teachers. Cukurova University Faculty of Education Journal, 52(1), 33-70. https://doi.org/10.14812/cuefd.1033080
  • Schukajlow, S., Kaiser, G., & Stillman, G. (2018). Empirical research on teaching and learning of mathematical modelling: A survey on the current state-of-the-art. ZDM–Mathematics Education, 50, 5-18. https://doi.org/10.1007/s11858-018-0933-5
  • Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of business research, 104, 333-339. https://doi.org/10.1016/j.jbusres.2019.07.039
  • Sokolowski, A. (2015). The Effects of Mathematical Modelling on Students' Achievement-Meta-Analysis of Research. IAFOR Journal of Education, 3(1), 93-114.
  • Tosun, C. (2024). Analysis of the last 40 years of science education research via bibliometric methods. Science & Education, 33(2), 451-480. https://doi.org/10.1007/s11191-022-00400-9
  • Van Dooren, W., De Bock, D., Evers, M., & Verschaffel, L. (2009). Students' overuse of proportionality on missing-value problems: How numbers may change solutions. Journal for Research in Mathematics Education, 40(2), 187-211. https://doi.org/10.2307/40539331
  • Van Dooren, W., De Bock, D., Janssens, D., & Verschaffel, L. (2008). The linear imperative: An inventory and conceptual analysis of students' overuse of linearity. Journal for Research in Mathematics Education, 39(3), 311-342. https://doi.org/10.2307/30034972
  • Van Eck, N., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. scientometrics, 84(2), 523-538. https://doi.org/10.1007/s11192-009-0146-3
  • Verma, S., & Gustafsson, A. (2020). Investigating the emerging COVID-19 research trends in the field of business and management: A bibliometric analysis approach. Journal of business research, 118, 253-261. https://doi.org/10.1016/j.jbusres.2020.06.057
  • *Verschaffel, L., Schukajlow, S., Star, J., & Van Dooren, W. (2020). Word problems in mathematics education: A survey. ZDM–Mathematics Education, 52, 1-16. https://doi.org/10.1007/s11858-020-01130-4
  • *Villarreal, M. E., Esteley, C. B., & Smith, S. (2018). Pre-service teachers’ experiences within modelling scenarios enriched by digital technologies. ZDM–Mathematics Education, 50, 327-341. https://doi.org/10.1007/s11858-018-0925-5
  • Yükseköğretim Kurulu (2018a). İlköğretim Matematik Öğretmenliği Lisans Programı, Ankara.
  • Yükseköğretim Kurulu (2018b). Ortaöğretim Matematik Öğretmenliği Lisans Programı, Ankara.
Toplam 37 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Matematik Eğitimi
Bölüm Makaleler
Yazarlar

Seda Şahin 0000-0003-3202-8852

Erken Görünüm Tarihi 30 Ocak 2025
Yayımlanma Tarihi
Gönderilme Tarihi 9 Temmuz 2024
Kabul Tarihi 30 Eylül 2024
Yayımlandığı Sayı Yıl 2025 Cilt: 61 Sayı: 61

Kaynak Göster

APA Şahin, S. (2025). Bibliometric Analysis of Mathematical Modeling Research in Mathematics Education. Marmara Üniversitesi Atatürk Eğitim Fakültesi Eğitim Bilimleri Dergisi, 61(61), 1-32. https://doi.org/10.15285/maruaebd.1513165