Research Article
BibTex RIS Cite

Year 2025, Volume: 15 Issue: 3, 1583 - 1612, 28.09.2025

Nilhan Sümeyra Güler , Zehra Akınç , Hayal Yavuz Mumcu

https://doi.org/10.48146/odusobiad.1612459

Abstract

References

  • Aho, A. V. (2012). Computation and computational thinking. The Computer Journal, 55(7), 832-835. https://doi.org/10.1093/comjnl/bxs074.
  • Aktaş, S. E. (2022). Matematik öğretmeni adaylarının teknoloji destekli matematiksel modelleme sürecindeki bilgi işlemsel düşünmeye ilişkin zihinsel eylemlerinin incelenmesi [Yayınlanmamış yüksek lisans tezi]. Pamukkale Üniversitesi, Denizli.
  • Barcelos, T. S., & Silveira, I. F. (2012). Teaching computational thinking in initial series an analysis of the confluence among mathematics and computer sciences in elementary education and its implications for higher education. In 2012 XXXVIII Conferencia Latinoamericana En Informatica (CLEI) (pp. 1-8). IEEE. https://doi.org/10.1109/CLEI.2012.6427135
  • Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12: What is involved and what is the role of the computer science education community? ACM Inroads, 2(1), 48-54. https://doi.org/10.1145/1929887.1929905
  • Computer Science Teachers Association [CSTA] (2020). Standards for computer science teachers. https://csteachers.org/teacherstandards.
  • Costa, E. J. F., Campos, L. M. R. S., & Guerrero, D. D. S. (2017). Computational thinking in mathematics education: A joint approach to encourage problem-solving ability. In 2017 IEEE Frontiers in Education Conference (FIE) (pp. 1-8). IEEE. https://doi.org/10.1109/FIE.2017.8190655.
  • Curzon, P. (2015). Computational thinking: Searching to speak. http://www.inf.ed.ac.uk/publications/online/1245.pdf.
  • Demir, Ü., & Cevahir, H. (2020). Algoritmik düşünme yeterliliği ile problem çözme becerisi arasındaki ilişkinin incelenmesi: Mesleki ve Teknik Anadolu Lisesi örneği. Kastamonu Eğitim Dergisi, 28(4), 1610-1619. https://doi.org/10.24106/kefdergi.4179.
  • Denning, P. J. (2009). The profession of IT beyond computational thinking. Communications of the ACM, 52(6), 28-30. https://doi.org/10.1145/1516046.1516054
  • Eisenberg, M. (2002). Output devices, computation, and the future of mathematical crafts. International Journal of Computers for Mathematical Learning, 7, 1-44.
  • English, L. (2018). On MTL’s second milestone: Exploring computational thinking and mathematics learning. Mathematical Thinking and Learning, 20(1), 1-2. https://doi.org/10.1080/10986065.2018.1405615
  • Erümit, K. A., Karal, H., Şahin, G., Aksoy, D. A., Aksoy, A., & Benzer, A. İ. (2018). Programlama öğretimi için bir model önerisi: Yedi adımda programlama. Eğitim ve Bilim, 44(197), 155-183.http://dx.doi.org/10.15390/EB.2018.7678.
  • Gadanidis, G., Hughes, J. M., Minniti, L., & White, B. J. G. (2017). Computational thinking, grade 1 students and the binomial theorem. Digital Experiences in Mathematics Education, 3, 77-96. https://doi.org/10.1007/s40751-016-0019-3. Gonzalez, R., Gonzalez, P. & Fernandez, J. (2017). Which cognitive abilities underlie computational thinking? Criterion validity of the Computational Thinking Test. Computers in Human Behavior, 72, 678–691. https://doi.org/10.1016/j.chb.2016.08.047.
  • Gülbahar, Y., Kert, S. B., & Kalelioğlu, F. (2019). Bilgi işlemsel düşünme becerisine yönelik öz yeterlik algısı ölçeği: Geçerlik ve güvenirlik çalışması. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 10(1), 1-29. https://doi.org/10.16949/turkbilmat.385097.
  • Guzdial, M. (1994). Software-realized scaffolding to facilitate programming for science learning. Interactive Learning Environments, 4(1), 1–44. https://doi.org/10.1080/1049482940040101.
  • Hickmott, D., Prieto-Rodriguez, E., & Holmes, K. (2018). A scoping review of studies on computational thinking in K–12 mathematics classrooms. Digital Experiences in Mathematics Education, 4, 48-69. https://doi.org/10.1007/s40751-017-0038-8.
  • International Society for Technology in Education [ISTE] (2016). ISTE standards for students: A practical guide for learning with technology. Washington, DC: Author.
  • Kong, S. C. (2016). A framework of curriculum design for computational thinking development in K-12 education. Journal of Computers in Education, 3(4), 377-394. https://doi.org/10.1007/s40692-016-0076-z.
  • Lu, J. J., & Fletcher, G. H. (2009). Thinking about computational thinking. In Proceedings of the 40th ACM technical symposium on Computer science education (pp. 260-264). Chattanooga, Tenessee, USA.
  • Mannila, L., Dagiene, V., Demo, B., Grgurina, N., Mirolo, C., Rolandsson, L., & Settle, A. (2014). Computational thinking in K-9 education. In Proceedings of the working group reports of the 2014 on innovation & technology in computer science education conference (pp. 1-29). ACM.
  • MEB. (2018a). Bilişim teknolojileri ve yazılım dersi öğretim programı: 5. ve 6. sınıflar. Ankara: MEB.
  • MEB. (2018b). Bilişim teknolojileri ve yazılım dersi öğretim programı: İlkokul 1, 2, 3 ve 4. sınıflar. Ankara: MEB.
  • MEB. (2018c). Matematik dersi öğretim programı (İlkokul ve Ortaokul 1, 2, 3, 4, 5, 6, 7 ve 8. Sınıflar). Ankara: MEB.
  • Miles, M, B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook. (2nd ed). Sage.
  • National Research Council (2011a). Learning science through computer games and simulations. The National Academies Press, Washington, DC. https://ics.uci.edu/~wscacchi/GameLab/Recommended%20Readings/Learning-Science-Games-2011.pdf.
  • National Research Council (2011b). Report of a workshop of pedagogical aspects of computational thinking. The National Academies Press, Washington, DC. https://people.cs.vt.edu/~kafura/CS6604/Papers/NRC-Pegagogy-CT.pdf.
  • Ndlovu, M., Wessels, D., & De Villiers, M. (2011). An instrumental approach to modelling the derivative in Sketchpad. Pythagoras, 32(2), 1-15. https://hdl.handle.net/10520/EJC20946.
  • Niemelä, P., Pears, A., Dagienė, V., & Laanpere, M. (2022). Computational thinking – Forces shaping curriculum and policy in Finland, Sweden and the Baltic countries. In D. Passey, D. Leahy, L. Williams, J. Holvikivi, & M. Ruohonen (Eds.), Digital transformation of education and learning—past, present and future (C. 642, ss. 131-143). Springer International Publishing. https://doi.org/10.1007/978-3-030-97986-7_11.
  • OECD (Organisation for Economic Co-operation and Development) (2022). PISA 2022 assessment and analytical framework. https://doi.org/10.1787/dfe0bf9c-en.
  • Oluk, A. (2017). Öğrencilerin bilgisayarca düşünme becerilerinin mantıksal matematiksel zekâ ve matematik akademik başarıları açısından incelenmesi [Yayınlanmamış yüksek lisans tezi]. Amasya Üniversitesi, Amasya.
  • Papert, S. (1996). An exploration in the space of mathematics educations. International Journal of Computers for Mathematical Learning, 1(1), 138-142.
  • Patan B., (2016). Okul öncesi kodlama öğretim programının geliştirilmesi [Yayınlanmamış yüksek lisans tezi]. Bahçeşehir Üniversitesi, İstanbul.
  • Patton, M. Q. (2014). Nitel araştırma ve değerlendirme yöntemleri (3. baskı) (Çev. Ed. M. Bütün & S. B. Demir). Ankara: Pegem Akademi.
  • Repenning, A., Webb, D., Ioannidou, A. (2010). Scalable game design and the development of a checklist for getting computational thinking into public schools. In Proceedings of the 41st ACM technical symposium on computer science education (pp 265–269). ACM. https://dl.acm.org/doi/10.1145/1734263.1734357.
  • Sengupta, P., Kinnebrew, J. S., Basu, S., Biswas, G., & Clark, D. (2013). Integrating computational thinking with K-12 science education using agent-based computation: A theoretical framework. Education and Information Technologies, 18, 351-380. https://doi.org/10.1007/s10639-012-9240-x.
  • Sneider, C., Stephenson, C., Schafer, B., & Flick, L. (2014). Exploring the science framework and NGSS: Computational thinking in the science classroom. Science Scope, 38(3), 10-15.
  • Temel, B. (2022). Bilgi işlemsel düşünme etkinliklerinin 7. sınıf öğrencilerinin problem çözmeye yönelik beceri ve tutumlarına etkisi [Yayınlanmamış yüksek lisans tezi]. Ordu Üniversitesi, Ordu.
  • Üzümcü, Ö. (2022). İlkokul matematik öğretim programının bilgi işlemsel düşünme boyutlarını içerme durumunun analizi. 10. Uluslararası Eğitim Programları ve Öğretim Kongresi özet bildiri kitapçığı içinde (ss. 833-835). Ankara: Gazi Üniversitesi Yayınları.
  • Üzümcü, Ö., & Bay, E. (2018). Eğitimde yeni 21. yüzyıl becerisi: Bilgi işlemsel düşünme. Uluslararası Türk Kültür Coğrafyasında Sosyal Bilimler Dergisi, 3(2), 1-16.
  • Üzümcü, Ö., & Bay, E. (2021). Bilgisayarsız kodlama eğitiminde bilgi işlemsel düşünme. Ankara: Akademisyen Kitabevi.
  • Van Merrienboer, J. J. (2013). Perspectives on problem solving and instruction. Computers & Education, 64, 153-160. https://doi.org/10.1016/j.compedu.2012.11.025. Voskoglou, M. G., & Buckley, S. (2012). Problem solving and computational thinking in a learning environment. Egyptian Computer Science Journal, 36(4), 28–46. https://doi.org/10.48550/arXiv.1212.0750.
  • Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilenskey, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25, 127-147. https://doi.org/10.1007/s10956-015-9581-5.
  • Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25, 127-147. https://doi.org/10.1007/s10956-015-9581-5.
  • Weiser, M. (1982). Programmers use slices when debugging. Communications of the ACM, 25(7), 446-452. https://doi.org/10.1145/358557.358577.
  • Wilensky, U., & Reisman, K. (2006). Thinking like a wolf, a sheep, or a firefly: Learning biology through constructing and testing computational theories—an embodied modeling approach. Cognition and Instruction, 24(2), 171-209. https://doi.org/10.1207/s1532690xci2402_1.
  • Wilensky, U., Brady, C. E., & Horn, M. S. (2014). Fostering computational literacy in science classrooms. Communications of the ACM, 57(8), 24-28. https://doi.org/10.1145/2633031.
  • Wilson, C., & Guzdial, M. (2010). How to make progress in computing education. Communications of the ACM, 53(5), 35-37. https://doi.org/10.1145/1735223.1735235.
  • Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35. https://doi.org/10.1145/1118178.1118215.
  • Wing, J. M. (2008). Computational thinking and thinking about computing. Philosophical transactions: Mathematical, physical and engineering sciences, 366(1881), 3717-3725. https://doi.org/10.1098/rsta.2008.0118.
  • Wing, J. M. (2011). Research notebook: Computational thinking—What and why. The Link Magazine, 6, 20-23. https://people.cs.vt.edu/~kafura/CS6604/Papers/CT-What-And-Why.pdf.
  • Yadav, A., Hong, H., & Stephenson, C. (2016). Computational thinking for all: Pedagogical approaches to embedding 21st century problem solving in K-12 classrooms. Tech Trends, 60, 565-568. https://doi.org/10.1007/s11528-016-0087-7.
  • Yadav, A., Zhou, N., Mayfield, C., Hambrusch, S., & Korb, J. T. (2011). Introducing computational thinking in education courses. In Proceedings of the 42nd ACM Technical Symposium on Computer Science Education, (pp. 465-470). https://doi.org/10.1145/1953163.1953297.
  • Yıldırım, A., & Şimşek, H. (2021). Sosyal bilimlerde nitel araştırma yöntemleri (12. baskı). Ankara: Seçkin Yayıncılık

Year 2025, Volume: 15 Issue: 3, 1583 - 1612, 28.09.2025

Nilhan Sümeyra Güler , Zehra Akınç , Hayal Yavuz Mumcu

https://doi.org/10.48146/odusobiad.1612459

Abstract

References

  • Aho, A. V. (2012). Computation and computational thinking. The Computer Journal, 55(7), 832-835. https://doi.org/10.1093/comjnl/bxs074.
  • Aktaş, S. E. (2022). Matematik öğretmeni adaylarının teknoloji destekli matematiksel modelleme sürecindeki bilgi işlemsel düşünmeye ilişkin zihinsel eylemlerinin incelenmesi [Yayınlanmamış yüksek lisans tezi]. Pamukkale Üniversitesi, Denizli.
  • Barcelos, T. S., & Silveira, I. F. (2012). Teaching computational thinking in initial series an analysis of the confluence among mathematics and computer sciences in elementary education and its implications for higher education. In 2012 XXXVIII Conferencia Latinoamericana En Informatica (CLEI) (pp. 1-8). IEEE. https://doi.org/10.1109/CLEI.2012.6427135
  • Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12: What is involved and what is the role of the computer science education community? ACM Inroads, 2(1), 48-54. https://doi.org/10.1145/1929887.1929905
  • Computer Science Teachers Association [CSTA] (2020). Standards for computer science teachers. https://csteachers.org/teacherstandards.
  • Costa, E. J. F., Campos, L. M. R. S., & Guerrero, D. D. S. (2017). Computational thinking in mathematics education: A joint approach to encourage problem-solving ability. In 2017 IEEE Frontiers in Education Conference (FIE) (pp. 1-8). IEEE. https://doi.org/10.1109/FIE.2017.8190655.
  • Curzon, P. (2015). Computational thinking: Searching to speak. http://www.inf.ed.ac.uk/publications/online/1245.pdf.
  • Demir, Ü., & Cevahir, H. (2020). Algoritmik düşünme yeterliliği ile problem çözme becerisi arasındaki ilişkinin incelenmesi: Mesleki ve Teknik Anadolu Lisesi örneği. Kastamonu Eğitim Dergisi, 28(4), 1610-1619. https://doi.org/10.24106/kefdergi.4179.
  • Denning, P. J. (2009). The profession of IT beyond computational thinking. Communications of the ACM, 52(6), 28-30. https://doi.org/10.1145/1516046.1516054
  • Eisenberg, M. (2002). Output devices, computation, and the future of mathematical crafts. International Journal of Computers for Mathematical Learning, 7, 1-44.
  • English, L. (2018). On MTL’s second milestone: Exploring computational thinking and mathematics learning. Mathematical Thinking and Learning, 20(1), 1-2. https://doi.org/10.1080/10986065.2018.1405615
  • Erümit, K. A., Karal, H., Şahin, G., Aksoy, D. A., Aksoy, A., & Benzer, A. İ. (2018). Programlama öğretimi için bir model önerisi: Yedi adımda programlama. Eğitim ve Bilim, 44(197), 155-183.http://dx.doi.org/10.15390/EB.2018.7678.
  • Gadanidis, G., Hughes, J. M., Minniti, L., & White, B. J. G. (2017). Computational thinking, grade 1 students and the binomial theorem. Digital Experiences in Mathematics Education, 3, 77-96. https://doi.org/10.1007/s40751-016-0019-3. Gonzalez, R., Gonzalez, P. & Fernandez, J. (2017). Which cognitive abilities underlie computational thinking? Criterion validity of the Computational Thinking Test. Computers in Human Behavior, 72, 678–691. https://doi.org/10.1016/j.chb.2016.08.047.
  • Gülbahar, Y., Kert, S. B., & Kalelioğlu, F. (2019). Bilgi işlemsel düşünme becerisine yönelik öz yeterlik algısı ölçeği: Geçerlik ve güvenirlik çalışması. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 10(1), 1-29. https://doi.org/10.16949/turkbilmat.385097.
  • Guzdial, M. (1994). Software-realized scaffolding to facilitate programming for science learning. Interactive Learning Environments, 4(1), 1–44. https://doi.org/10.1080/1049482940040101.
  • Hickmott, D., Prieto-Rodriguez, E., & Holmes, K. (2018). A scoping review of studies on computational thinking in K–12 mathematics classrooms. Digital Experiences in Mathematics Education, 4, 48-69. https://doi.org/10.1007/s40751-017-0038-8.
  • International Society for Technology in Education [ISTE] (2016). ISTE standards for students: A practical guide for learning with technology. Washington, DC: Author.
  • Kong, S. C. (2016). A framework of curriculum design for computational thinking development in K-12 education. Journal of Computers in Education, 3(4), 377-394. https://doi.org/10.1007/s40692-016-0076-z.
  • Lu, J. J., & Fletcher, G. H. (2009). Thinking about computational thinking. In Proceedings of the 40th ACM technical symposium on Computer science education (pp. 260-264). Chattanooga, Tenessee, USA.
  • Mannila, L., Dagiene, V., Demo, B., Grgurina, N., Mirolo, C., Rolandsson, L., & Settle, A. (2014). Computational thinking in K-9 education. In Proceedings of the working group reports of the 2014 on innovation & technology in computer science education conference (pp. 1-29). ACM.
  • MEB. (2018a). Bilişim teknolojileri ve yazılım dersi öğretim programı: 5. ve 6. sınıflar. Ankara: MEB.
  • MEB. (2018b). Bilişim teknolojileri ve yazılım dersi öğretim programı: İlkokul 1, 2, 3 ve 4. sınıflar. Ankara: MEB.
  • MEB. (2018c). Matematik dersi öğretim programı (İlkokul ve Ortaokul 1, 2, 3, 4, 5, 6, 7 ve 8. Sınıflar). Ankara: MEB.
  • Miles, M, B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook. (2nd ed). Sage.
  • National Research Council (2011a). Learning science through computer games and simulations. The National Academies Press, Washington, DC. https://ics.uci.edu/~wscacchi/GameLab/Recommended%20Readings/Learning-Science-Games-2011.pdf.
  • National Research Council (2011b). Report of a workshop of pedagogical aspects of computational thinking. The National Academies Press, Washington, DC. https://people.cs.vt.edu/~kafura/CS6604/Papers/NRC-Pegagogy-CT.pdf.
  • Ndlovu, M., Wessels, D., & De Villiers, M. (2011). An instrumental approach to modelling the derivative in Sketchpad. Pythagoras, 32(2), 1-15. https://hdl.handle.net/10520/EJC20946.
  • Niemelä, P., Pears, A., Dagienė, V., & Laanpere, M. (2022). Computational thinking – Forces shaping curriculum and policy in Finland, Sweden and the Baltic countries. In D. Passey, D. Leahy, L. Williams, J. Holvikivi, & M. Ruohonen (Eds.), Digital transformation of education and learning—past, present and future (C. 642, ss. 131-143). Springer International Publishing. https://doi.org/10.1007/978-3-030-97986-7_11.
  • OECD (Organisation for Economic Co-operation and Development) (2022). PISA 2022 assessment and analytical framework. https://doi.org/10.1787/dfe0bf9c-en.
  • Oluk, A. (2017). Öğrencilerin bilgisayarca düşünme becerilerinin mantıksal matematiksel zekâ ve matematik akademik başarıları açısından incelenmesi [Yayınlanmamış yüksek lisans tezi]. Amasya Üniversitesi, Amasya.
  • Papert, S. (1996). An exploration in the space of mathematics educations. International Journal of Computers for Mathematical Learning, 1(1), 138-142.
  • Patan B., (2016). Okul öncesi kodlama öğretim programının geliştirilmesi [Yayınlanmamış yüksek lisans tezi]. Bahçeşehir Üniversitesi, İstanbul.
  • Patton, M. Q. (2014). Nitel araştırma ve değerlendirme yöntemleri (3. baskı) (Çev. Ed. M. Bütün & S. B. Demir). Ankara: Pegem Akademi.
  • Repenning, A., Webb, D., Ioannidou, A. (2010). Scalable game design and the development of a checklist for getting computational thinking into public schools. In Proceedings of the 41st ACM technical symposium on computer science education (pp 265–269). ACM. https://dl.acm.org/doi/10.1145/1734263.1734357.
  • Sengupta, P., Kinnebrew, J. S., Basu, S., Biswas, G., & Clark, D. (2013). Integrating computational thinking with K-12 science education using agent-based computation: A theoretical framework. Education and Information Technologies, 18, 351-380. https://doi.org/10.1007/s10639-012-9240-x.
  • Sneider, C., Stephenson, C., Schafer, B., & Flick, L. (2014). Exploring the science framework and NGSS: Computational thinking in the science classroom. Science Scope, 38(3), 10-15.
  • Temel, B. (2022). Bilgi işlemsel düşünme etkinliklerinin 7. sınıf öğrencilerinin problem çözmeye yönelik beceri ve tutumlarına etkisi [Yayınlanmamış yüksek lisans tezi]. Ordu Üniversitesi, Ordu.
  • Üzümcü, Ö. (2022). İlkokul matematik öğretim programının bilgi işlemsel düşünme boyutlarını içerme durumunun analizi. 10. Uluslararası Eğitim Programları ve Öğretim Kongresi özet bildiri kitapçığı içinde (ss. 833-835). Ankara: Gazi Üniversitesi Yayınları.
  • Üzümcü, Ö., & Bay, E. (2018). Eğitimde yeni 21. yüzyıl becerisi: Bilgi işlemsel düşünme. Uluslararası Türk Kültür Coğrafyasında Sosyal Bilimler Dergisi, 3(2), 1-16.
  • Üzümcü, Ö., & Bay, E. (2021). Bilgisayarsız kodlama eğitiminde bilgi işlemsel düşünme. Ankara: Akademisyen Kitabevi.
  • Van Merrienboer, J. J. (2013). Perspectives on problem solving and instruction. Computers & Education, 64, 153-160. https://doi.org/10.1016/j.compedu.2012.11.025. Voskoglou, M. G., & Buckley, S. (2012). Problem solving and computational thinking in a learning environment. Egyptian Computer Science Journal, 36(4), 28–46. https://doi.org/10.48550/arXiv.1212.0750.
  • Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilenskey, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25, 127-147. https://doi.org/10.1007/s10956-015-9581-5.
  • Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25, 127-147. https://doi.org/10.1007/s10956-015-9581-5.
  • Weiser, M. (1982). Programmers use slices when debugging. Communications of the ACM, 25(7), 446-452. https://doi.org/10.1145/358557.358577.
  • Wilensky, U., & Reisman, K. (2006). Thinking like a wolf, a sheep, or a firefly: Learning biology through constructing and testing computational theories—an embodied modeling approach. Cognition and Instruction, 24(2), 171-209. https://doi.org/10.1207/s1532690xci2402_1.
  • Wilensky, U., Brady, C. E., & Horn, M. S. (2014). Fostering computational literacy in science classrooms. Communications of the ACM, 57(8), 24-28. https://doi.org/10.1145/2633031.
  • Wilson, C., & Guzdial, M. (2010). How to make progress in computing education. Communications of the ACM, 53(5), 35-37. https://doi.org/10.1145/1735223.1735235.
  • Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35. https://doi.org/10.1145/1118178.1118215.
  • Wing, J. M. (2008). Computational thinking and thinking about computing. Philosophical transactions: Mathematical, physical and engineering sciences, 366(1881), 3717-3725. https://doi.org/10.1098/rsta.2008.0118.
  • Wing, J. M. (2011). Research notebook: Computational thinking—What and why. The Link Magazine, 6, 20-23. https://people.cs.vt.edu/~kafura/CS6604/Papers/CT-What-And-Why.pdf.
  • Yadav, A., Hong, H., & Stephenson, C. (2016). Computational thinking for all: Pedagogical approaches to embedding 21st century problem solving in K-12 classrooms. Tech Trends, 60, 565-568. https://doi.org/10.1007/s11528-016-0087-7.
  • Yadav, A., Zhou, N., Mayfield, C., Hambrusch, S., & Korb, J. T. (2011). Introducing computational thinking in education courses. In Proceedings of the 42nd ACM Technical Symposium on Computer Science Education, (pp. 465-470). https://doi.org/10.1145/1953163.1953297.
  • Yıldırım, A., & Şimşek, H. (2021). Sosyal bilimlerde nitel araştırma yöntemleri (12. baskı). Ankara: Seçkin Yayıncılık

Year 2025, Volume: 15 Issue: 3, 1583 - 1612, 28.09.2025

Nilhan Sümeyra Güler , Zehra Akınç , Hayal Yavuz Mumcu

https://doi.org/10.48146/odusobiad.1612459

Abstract

References

  • Aho, A. V. (2012). Computation and computational thinking. The Computer Journal, 55(7), 832-835. https://doi.org/10.1093/comjnl/bxs074.
  • Aktaş, S. E. (2022). Matematik öğretmeni adaylarının teknoloji destekli matematiksel modelleme sürecindeki bilgi işlemsel düşünmeye ilişkin zihinsel eylemlerinin incelenmesi [Yayınlanmamış yüksek lisans tezi]. Pamukkale Üniversitesi, Denizli.
  • Barcelos, T. S., & Silveira, I. F. (2012). Teaching computational thinking in initial series an analysis of the confluence among mathematics and computer sciences in elementary education and its implications for higher education. In 2012 XXXVIII Conferencia Latinoamericana En Informatica (CLEI) (pp. 1-8). IEEE. https://doi.org/10.1109/CLEI.2012.6427135
  • Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12: What is involved and what is the role of the computer science education community? ACM Inroads, 2(1), 48-54. https://doi.org/10.1145/1929887.1929905
  • Computer Science Teachers Association [CSTA] (2020). Standards for computer science teachers. https://csteachers.org/teacherstandards.
  • Costa, E. J. F., Campos, L. M. R. S., & Guerrero, D. D. S. (2017). Computational thinking in mathematics education: A joint approach to encourage problem-solving ability. In 2017 IEEE Frontiers in Education Conference (FIE) (pp. 1-8). IEEE. https://doi.org/10.1109/FIE.2017.8190655.
  • Curzon, P. (2015). Computational thinking: Searching to speak. http://www.inf.ed.ac.uk/publications/online/1245.pdf.
  • Demir, Ü., & Cevahir, H. (2020). Algoritmik düşünme yeterliliği ile problem çözme becerisi arasındaki ilişkinin incelenmesi: Mesleki ve Teknik Anadolu Lisesi örneği. Kastamonu Eğitim Dergisi, 28(4), 1610-1619. https://doi.org/10.24106/kefdergi.4179.
  • Denning, P. J. (2009). The profession of IT beyond computational thinking. Communications of the ACM, 52(6), 28-30. https://doi.org/10.1145/1516046.1516054
  • Eisenberg, M. (2002). Output devices, computation, and the future of mathematical crafts. International Journal of Computers for Mathematical Learning, 7, 1-44.
  • English, L. (2018). On MTL’s second milestone: Exploring computational thinking and mathematics learning. Mathematical Thinking and Learning, 20(1), 1-2. https://doi.org/10.1080/10986065.2018.1405615
  • Erümit, K. A., Karal, H., Şahin, G., Aksoy, D. A., Aksoy, A., & Benzer, A. İ. (2018). Programlama öğretimi için bir model önerisi: Yedi adımda programlama. Eğitim ve Bilim, 44(197), 155-183.http://dx.doi.org/10.15390/EB.2018.7678.
  • Gadanidis, G., Hughes, J. M., Minniti, L., & White, B. J. G. (2017). Computational thinking, grade 1 students and the binomial theorem. Digital Experiences in Mathematics Education, 3, 77-96. https://doi.org/10.1007/s40751-016-0019-3. Gonzalez, R., Gonzalez, P. & Fernandez, J. (2017). Which cognitive abilities underlie computational thinking? Criterion validity of the Computational Thinking Test. Computers in Human Behavior, 72, 678–691. https://doi.org/10.1016/j.chb.2016.08.047.
  • Gülbahar, Y., Kert, S. B., & Kalelioğlu, F. (2019). Bilgi işlemsel düşünme becerisine yönelik öz yeterlik algısı ölçeği: Geçerlik ve güvenirlik çalışması. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 10(1), 1-29. https://doi.org/10.16949/turkbilmat.385097.
  • Guzdial, M. (1994). Software-realized scaffolding to facilitate programming for science learning. Interactive Learning Environments, 4(1), 1–44. https://doi.org/10.1080/1049482940040101.
  • Hickmott, D., Prieto-Rodriguez, E., & Holmes, K. (2018). A scoping review of studies on computational thinking in K–12 mathematics classrooms. Digital Experiences in Mathematics Education, 4, 48-69. https://doi.org/10.1007/s40751-017-0038-8.
  • International Society for Technology in Education [ISTE] (2016). ISTE standards for students: A practical guide for learning with technology. Washington, DC: Author.
  • Kong, S. C. (2016). A framework of curriculum design for computational thinking development in K-12 education. Journal of Computers in Education, 3(4), 377-394. https://doi.org/10.1007/s40692-016-0076-z.
  • Lu, J. J., & Fletcher, G. H. (2009). Thinking about computational thinking. In Proceedings of the 40th ACM technical symposium on Computer science education (pp. 260-264). Chattanooga, Tenessee, USA.
  • Mannila, L., Dagiene, V., Demo, B., Grgurina, N., Mirolo, C., Rolandsson, L., & Settle, A. (2014). Computational thinking in K-9 education. In Proceedings of the working group reports of the 2014 on innovation & technology in computer science education conference (pp. 1-29). ACM.
  • MEB. (2018a). Bilişim teknolojileri ve yazılım dersi öğretim programı: 5. ve 6. sınıflar. Ankara: MEB.
  • MEB. (2018b). Bilişim teknolojileri ve yazılım dersi öğretim programı: İlkokul 1, 2, 3 ve 4. sınıflar. Ankara: MEB.
  • MEB. (2018c). Matematik dersi öğretim programı (İlkokul ve Ortaokul 1, 2, 3, 4, 5, 6, 7 ve 8. Sınıflar). Ankara: MEB.
  • Miles, M, B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook. (2nd ed). Sage.
  • National Research Council (2011a). Learning science through computer games and simulations. The National Academies Press, Washington, DC. https://ics.uci.edu/~wscacchi/GameLab/Recommended%20Readings/Learning-Science-Games-2011.pdf.
  • National Research Council (2011b). Report of a workshop of pedagogical aspects of computational thinking. The National Academies Press, Washington, DC. https://people.cs.vt.edu/~kafura/CS6604/Papers/NRC-Pegagogy-CT.pdf.
  • Ndlovu, M., Wessels, D., & De Villiers, M. (2011). An instrumental approach to modelling the derivative in Sketchpad. Pythagoras, 32(2), 1-15. https://hdl.handle.net/10520/EJC20946.
  • Niemelä, P., Pears, A., Dagienė, V., & Laanpere, M. (2022). Computational thinking – Forces shaping curriculum and policy in Finland, Sweden and the Baltic countries. In D. Passey, D. Leahy, L. Williams, J. Holvikivi, & M. Ruohonen (Eds.), Digital transformation of education and learning—past, present and future (C. 642, ss. 131-143). Springer International Publishing. https://doi.org/10.1007/978-3-030-97986-7_11.
  • OECD (Organisation for Economic Co-operation and Development) (2022). PISA 2022 assessment and analytical framework. https://doi.org/10.1787/dfe0bf9c-en.
  • Oluk, A. (2017). Öğrencilerin bilgisayarca düşünme becerilerinin mantıksal matematiksel zekâ ve matematik akademik başarıları açısından incelenmesi [Yayınlanmamış yüksek lisans tezi]. Amasya Üniversitesi, Amasya.
  • Papert, S. (1996). An exploration in the space of mathematics educations. International Journal of Computers for Mathematical Learning, 1(1), 138-142.
  • Patan B., (2016). Okul öncesi kodlama öğretim programının geliştirilmesi [Yayınlanmamış yüksek lisans tezi]. Bahçeşehir Üniversitesi, İstanbul.
  • Patton, M. Q. (2014). Nitel araştırma ve değerlendirme yöntemleri (3. baskı) (Çev. Ed. M. Bütün & S. B. Demir). Ankara: Pegem Akademi.
  • Repenning, A., Webb, D., Ioannidou, A. (2010). Scalable game design and the development of a checklist for getting computational thinking into public schools. In Proceedings of the 41st ACM technical symposium on computer science education (pp 265–269). ACM. https://dl.acm.org/doi/10.1145/1734263.1734357.
  • Sengupta, P., Kinnebrew, J. S., Basu, S., Biswas, G., & Clark, D. (2013). Integrating computational thinking with K-12 science education using agent-based computation: A theoretical framework. Education and Information Technologies, 18, 351-380. https://doi.org/10.1007/s10639-012-9240-x.
  • Sneider, C., Stephenson, C., Schafer, B., & Flick, L. (2014). Exploring the science framework and NGSS: Computational thinking in the science classroom. Science Scope, 38(3), 10-15.
  • Temel, B. (2022). Bilgi işlemsel düşünme etkinliklerinin 7. sınıf öğrencilerinin problem çözmeye yönelik beceri ve tutumlarına etkisi [Yayınlanmamış yüksek lisans tezi]. Ordu Üniversitesi, Ordu.
  • Üzümcü, Ö. (2022). İlkokul matematik öğretim programının bilgi işlemsel düşünme boyutlarını içerme durumunun analizi. 10. Uluslararası Eğitim Programları ve Öğretim Kongresi özet bildiri kitapçığı içinde (ss. 833-835). Ankara: Gazi Üniversitesi Yayınları.
  • Üzümcü, Ö., & Bay, E. (2018). Eğitimde yeni 21. yüzyıl becerisi: Bilgi işlemsel düşünme. Uluslararası Türk Kültür Coğrafyasında Sosyal Bilimler Dergisi, 3(2), 1-16.
  • Üzümcü, Ö., & Bay, E. (2021). Bilgisayarsız kodlama eğitiminde bilgi işlemsel düşünme. Ankara: Akademisyen Kitabevi.
  • Van Merrienboer, J. J. (2013). Perspectives on problem solving and instruction. Computers & Education, 64, 153-160. https://doi.org/10.1016/j.compedu.2012.11.025. Voskoglou, M. G., & Buckley, S. (2012). Problem solving and computational thinking in a learning environment. Egyptian Computer Science Journal, 36(4), 28–46. https://doi.org/10.48550/arXiv.1212.0750.
  • Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilenskey, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25, 127-147. https://doi.org/10.1007/s10956-015-9581-5.
  • Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25, 127-147. https://doi.org/10.1007/s10956-015-9581-5.
  • Weiser, M. (1982). Programmers use slices when debugging. Communications of the ACM, 25(7), 446-452. https://doi.org/10.1145/358557.358577.
  • Wilensky, U., & Reisman, K. (2006). Thinking like a wolf, a sheep, or a firefly: Learning biology through constructing and testing computational theories—an embodied modeling approach. Cognition and Instruction, 24(2), 171-209. https://doi.org/10.1207/s1532690xci2402_1.
  • Wilensky, U., Brady, C. E., & Horn, M. S. (2014). Fostering computational literacy in science classrooms. Communications of the ACM, 57(8), 24-28. https://doi.org/10.1145/2633031.
  • Wilson, C., & Guzdial, M. (2010). How to make progress in computing education. Communications of the ACM, 53(5), 35-37. https://doi.org/10.1145/1735223.1735235.
  • Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35. https://doi.org/10.1145/1118178.1118215.
  • Wing, J. M. (2008). Computational thinking and thinking about computing. Philosophical transactions: Mathematical, physical and engineering sciences, 366(1881), 3717-3725. https://doi.org/10.1098/rsta.2008.0118.
  • Wing, J. M. (2011). Research notebook: Computational thinking—What and why. The Link Magazine, 6, 20-23. https://people.cs.vt.edu/~kafura/CS6604/Papers/CT-What-And-Why.pdf.
  • Yadav, A., Hong, H., & Stephenson, C. (2016). Computational thinking for all: Pedagogical approaches to embedding 21st century problem solving in K-12 classrooms. Tech Trends, 60, 565-568. https://doi.org/10.1007/s11528-016-0087-7.
  • Yadav, A., Zhou, N., Mayfield, C., Hambrusch, S., & Korb, J. T. (2011). Introducing computational thinking in education courses. In Proceedings of the 42nd ACM Technical Symposium on Computer Science Education, (pp. 465-470). https://doi.org/10.1145/1953163.1953297.
  • Yıldırım, A., & Şimşek, H. (2021). Sosyal bilimlerde nitel araştırma yöntemleri (12. baskı). Ankara: Seçkin Yayıncılık

Ortaokul matematik dersi öğretim programının bilgi işlemsel düşünme becerisi bağlamında incelenmesi

Year 2025, Volume: 15 Issue: 3, 1583 - 1612, 28.09.2025

Nilhan Sümeyra Güler , Zehra Akınç , Hayal Yavuz Mumcu

https://doi.org/10.48146/odusobiad.1612459

Abstract

Bu araştırmanın amacı ortaokul matematik dersi öğretim programında yer alan kazanımların, bilgi işlemsel düşünme becerisi bağlamında incelenmesidir. Bunun için öncelikle alan yazın taraması yapılarak bilgi işlemsel düşünme becerisinin göstergeleri oluşturulmuş, daha sonra ise ilgili müfredatta yer alan kazanımlar söz konusu göstergelerle ilişkili olarak incelenmiştir. Doküman analizi yönteminin kullanıldığı araştırmanın veri analizi sürecinde içerik analizi yönteminden yararlanılmıştır. Araştırmadan elde edilen sonuçlara göre, öğretim programında yer alan kazanımların yaklaşık %44’ünün algoritma, %28’inin örüntü-model çıkarma, %21’inin ise soyutlama boyutuyla ilişkili oldukları görülmüştür. Bununla birlikte, sayılar ve işlemler öğrenme alanındaki kazanımların özellikle 'algoritma', cebir ile geometri ve ölçme öğrenme alanlarındaki kazanımların 'örüntü-model oluşturma', veri işleme öğrenme alanındaki kazanımların 'değerlendirme-hata ayıklama', olasılık öğrenme alanındaki kazanımların ise 'soyutlama' ve 'örüntü-model oluşturma' boyutlarıyla güçlü bir ilişki içinde oldukları gözlenmiştir. Farklı sınıf düzeyleri göz önüne alındığında ise, 5 ve 8. sınıf kazanımlarıyla ilişkilendirilen boyutların sırasıyla 'algoritma', 'örüntü-model oluşturma' ve 'soyutlama', 6 ve 7. sınıf kazanımlarıyla ilişkilendirilen boyutların ise 'algoritma', 'örüntü-model oluşturma' ve 'parçalara ayırma' şeklinde sıralandığı sonucuna ulaşılmıştır.

Keywords

Bilgi işlemsel düşünme ortaokul matematik öğretim programı doküman analizi

References

  • Aho, A. V. (2012). Computation and computational thinking. The Computer Journal, 55(7), 832-835. https://doi.org/10.1093/comjnl/bxs074.
  • Aktaş, S. E. (2022). Matematik öğretmeni adaylarının teknoloji destekli matematiksel modelleme sürecindeki bilgi işlemsel düşünmeye ilişkin zihinsel eylemlerinin incelenmesi [Yayınlanmamış yüksek lisans tezi]. Pamukkale Üniversitesi, Denizli.
  • Barcelos, T. S., & Silveira, I. F. (2012). Teaching computational thinking in initial series an analysis of the confluence among mathematics and computer sciences in elementary education and its implications for higher education. In 2012 XXXVIII Conferencia Latinoamericana En Informatica (CLEI) (pp. 1-8). IEEE. https://doi.org/10.1109/CLEI.2012.6427135
  • Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12: What is involved and what is the role of the computer science education community? ACM Inroads, 2(1), 48-54. https://doi.org/10.1145/1929887.1929905
  • Computer Science Teachers Association [CSTA] (2020). Standards for computer science teachers. https://csteachers.org/teacherstandards.
  • Costa, E. J. F., Campos, L. M. R. S., & Guerrero, D. D. S. (2017). Computational thinking in mathematics education: A joint approach to encourage problem-solving ability. In 2017 IEEE Frontiers in Education Conference (FIE) (pp. 1-8). IEEE. https://doi.org/10.1109/FIE.2017.8190655.
  • Curzon, P. (2015). Computational thinking: Searching to speak. http://www.inf.ed.ac.uk/publications/online/1245.pdf.
  • Demir, Ü., & Cevahir, H. (2020). Algoritmik düşünme yeterliliği ile problem çözme becerisi arasındaki ilişkinin incelenmesi: Mesleki ve Teknik Anadolu Lisesi örneği. Kastamonu Eğitim Dergisi, 28(4), 1610-1619. https://doi.org/10.24106/kefdergi.4179.
  • Denning, P. J. (2009). The profession of IT beyond computational thinking. Communications of the ACM, 52(6), 28-30. https://doi.org/10.1145/1516046.1516054
  • Eisenberg, M. (2002). Output devices, computation, and the future of mathematical crafts. International Journal of Computers for Mathematical Learning, 7, 1-44.
  • English, L. (2018). On MTL’s second milestone: Exploring computational thinking and mathematics learning. Mathematical Thinking and Learning, 20(1), 1-2. https://doi.org/10.1080/10986065.2018.1405615
  • Erümit, K. A., Karal, H., Şahin, G., Aksoy, D. A., Aksoy, A., & Benzer, A. İ. (2018). Programlama öğretimi için bir model önerisi: Yedi adımda programlama. Eğitim ve Bilim, 44(197), 155-183.http://dx.doi.org/10.15390/EB.2018.7678.
  • Gadanidis, G., Hughes, J. M., Minniti, L., & White, B. J. G. (2017). Computational thinking, grade 1 students and the binomial theorem. Digital Experiences in Mathematics Education, 3, 77-96. https://doi.org/10.1007/s40751-016-0019-3. Gonzalez, R., Gonzalez, P. & Fernandez, J. (2017). Which cognitive abilities underlie computational thinking? Criterion validity of the Computational Thinking Test. Computers in Human Behavior, 72, 678–691. https://doi.org/10.1016/j.chb.2016.08.047.
  • Gülbahar, Y., Kert, S. B., & Kalelioğlu, F. (2019). Bilgi işlemsel düşünme becerisine yönelik öz yeterlik algısı ölçeği: Geçerlik ve güvenirlik çalışması. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 10(1), 1-29. https://doi.org/10.16949/turkbilmat.385097.
  • Guzdial, M. (1994). Software-realized scaffolding to facilitate programming for science learning. Interactive Learning Environments, 4(1), 1–44. https://doi.org/10.1080/1049482940040101.
  • Hickmott, D., Prieto-Rodriguez, E., & Holmes, K. (2018). A scoping review of studies on computational thinking in K–12 mathematics classrooms. Digital Experiences in Mathematics Education, 4, 48-69. https://doi.org/10.1007/s40751-017-0038-8.
  • International Society for Technology in Education [ISTE] (2016). ISTE standards for students: A practical guide for learning with technology. Washington, DC: Author.
  • Kong, S. C. (2016). A framework of curriculum design for computational thinking development in K-12 education. Journal of Computers in Education, 3(4), 377-394. https://doi.org/10.1007/s40692-016-0076-z.
  • Lu, J. J., & Fletcher, G. H. (2009). Thinking about computational thinking. In Proceedings of the 40th ACM technical symposium on Computer science education (pp. 260-264). Chattanooga, Tenessee, USA.
  • Mannila, L., Dagiene, V., Demo, B., Grgurina, N., Mirolo, C., Rolandsson, L., & Settle, A. (2014). Computational thinking in K-9 education. In Proceedings of the working group reports of the 2014 on innovation & technology in computer science education conference (pp. 1-29). ACM.
  • MEB. (2018a). Bilişim teknolojileri ve yazılım dersi öğretim programı: 5. ve 6. sınıflar. Ankara: MEB.
  • MEB. (2018b). Bilişim teknolojileri ve yazılım dersi öğretim programı: İlkokul 1, 2, 3 ve 4. sınıflar. Ankara: MEB.
  • MEB. (2018c). Matematik dersi öğretim programı (İlkokul ve Ortaokul 1, 2, 3, 4, 5, 6, 7 ve 8. Sınıflar). Ankara: MEB.
  • Miles, M, B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook. (2nd ed). Sage.
  • National Research Council (2011a). Learning science through computer games and simulations. The National Academies Press, Washington, DC. https://ics.uci.edu/~wscacchi/GameLab/Recommended%20Readings/Learning-Science-Games-2011.pdf.
  • National Research Council (2011b). Report of a workshop of pedagogical aspects of computational thinking. The National Academies Press, Washington, DC. https://people.cs.vt.edu/~kafura/CS6604/Papers/NRC-Pegagogy-CT.pdf.
  • Ndlovu, M., Wessels, D., & De Villiers, M. (2011). An instrumental approach to modelling the derivative in Sketchpad. Pythagoras, 32(2), 1-15. https://hdl.handle.net/10520/EJC20946.
  • Niemelä, P., Pears, A., Dagienė, V., & Laanpere, M. (2022). Computational thinking – Forces shaping curriculum and policy in Finland, Sweden and the Baltic countries. In D. Passey, D. Leahy, L. Williams, J. Holvikivi, & M. Ruohonen (Eds.), Digital transformation of education and learning—past, present and future (C. 642, ss. 131-143). Springer International Publishing. https://doi.org/10.1007/978-3-030-97986-7_11.
  • OECD (Organisation for Economic Co-operation and Development) (2022). PISA 2022 assessment and analytical framework. https://doi.org/10.1787/dfe0bf9c-en.
  • Oluk, A. (2017). Öğrencilerin bilgisayarca düşünme becerilerinin mantıksal matematiksel zekâ ve matematik akademik başarıları açısından incelenmesi [Yayınlanmamış yüksek lisans tezi]. Amasya Üniversitesi, Amasya.
  • Papert, S. (1996). An exploration in the space of mathematics educations. International Journal of Computers for Mathematical Learning, 1(1), 138-142.
  • Patan B., (2016). Okul öncesi kodlama öğretim programının geliştirilmesi [Yayınlanmamış yüksek lisans tezi]. Bahçeşehir Üniversitesi, İstanbul.
  • Patton, M. Q. (2014). Nitel araştırma ve değerlendirme yöntemleri (3. baskı) (Çev. Ed. M. Bütün & S. B. Demir). Ankara: Pegem Akademi.
  • Repenning, A., Webb, D., Ioannidou, A. (2010). Scalable game design and the development of a checklist for getting computational thinking into public schools. In Proceedings of the 41st ACM technical symposium on computer science education (pp 265–269). ACM. https://dl.acm.org/doi/10.1145/1734263.1734357.
  • Sengupta, P., Kinnebrew, J. S., Basu, S., Biswas, G., & Clark, D. (2013). Integrating computational thinking with K-12 science education using agent-based computation: A theoretical framework. Education and Information Technologies, 18, 351-380. https://doi.org/10.1007/s10639-012-9240-x.
  • Sneider, C., Stephenson, C., Schafer, B., & Flick, L. (2014). Exploring the science framework and NGSS: Computational thinking in the science classroom. Science Scope, 38(3), 10-15.
  • Temel, B. (2022). Bilgi işlemsel düşünme etkinliklerinin 7. sınıf öğrencilerinin problem çözmeye yönelik beceri ve tutumlarına etkisi [Yayınlanmamış yüksek lisans tezi]. Ordu Üniversitesi, Ordu.
  • Üzümcü, Ö. (2022). İlkokul matematik öğretim programının bilgi işlemsel düşünme boyutlarını içerme durumunun analizi. 10. Uluslararası Eğitim Programları ve Öğretim Kongresi özet bildiri kitapçığı içinde (ss. 833-835). Ankara: Gazi Üniversitesi Yayınları.
  • Üzümcü, Ö., & Bay, E. (2018). Eğitimde yeni 21. yüzyıl becerisi: Bilgi işlemsel düşünme. Uluslararası Türk Kültür Coğrafyasında Sosyal Bilimler Dergisi, 3(2), 1-16.
  • Üzümcü, Ö., & Bay, E. (2021). Bilgisayarsız kodlama eğitiminde bilgi işlemsel düşünme. Ankara: Akademisyen Kitabevi.
  • Van Merrienboer, J. J. (2013). Perspectives on problem solving and instruction. Computers & Education, 64, 153-160. https://doi.org/10.1016/j.compedu.2012.11.025. Voskoglou, M. G., & Buckley, S. (2012). Problem solving and computational thinking in a learning environment. Egyptian Computer Science Journal, 36(4), 28–46. https://doi.org/10.48550/arXiv.1212.0750.
  • Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilenskey, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25, 127-147. https://doi.org/10.1007/s10956-015-9581-5.
  • Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25, 127-147. https://doi.org/10.1007/s10956-015-9581-5.
  • Weiser, M. (1982). Programmers use slices when debugging. Communications of the ACM, 25(7), 446-452. https://doi.org/10.1145/358557.358577.
  • Wilensky, U., & Reisman, K. (2006). Thinking like a wolf, a sheep, or a firefly: Learning biology through constructing and testing computational theories—an embodied modeling approach. Cognition and Instruction, 24(2), 171-209. https://doi.org/10.1207/s1532690xci2402_1.
  • Wilensky, U., Brady, C. E., & Horn, M. S. (2014). Fostering computational literacy in science classrooms. Communications of the ACM, 57(8), 24-28. https://doi.org/10.1145/2633031.
  • Wilson, C., & Guzdial, M. (2010). How to make progress in computing education. Communications of the ACM, 53(5), 35-37. https://doi.org/10.1145/1735223.1735235.
  • Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35. https://doi.org/10.1145/1118178.1118215.
  • Wing, J. M. (2008). Computational thinking and thinking about computing. Philosophical transactions: Mathematical, physical and engineering sciences, 366(1881), 3717-3725. https://doi.org/10.1098/rsta.2008.0118.
  • Wing, J. M. (2011). Research notebook: Computational thinking—What and why. The Link Magazine, 6, 20-23. https://people.cs.vt.edu/~kafura/CS6604/Papers/CT-What-And-Why.pdf.
  • Yadav, A., Hong, H., & Stephenson, C. (2016). Computational thinking for all: Pedagogical approaches to embedding 21st century problem solving in K-12 classrooms. Tech Trends, 60, 565-568. https://doi.org/10.1007/s11528-016-0087-7.
  • Yadav, A., Zhou, N., Mayfield, C., Hambrusch, S., & Korb, J. T. (2011). Introducing computational thinking in education courses. In Proceedings of the 42nd ACM Technical Symposium on Computer Science Education, (pp. 465-470). https://doi.org/10.1145/1953163.1953297.
  • Yıldırım, A., & Şimşek, H. (2021). Sosyal bilimlerde nitel araştırma yöntemleri (12. baskı). Ankara: Seçkin Yayıncılık

Examination of middle school mathematics curriculum in the context of computational thinking skills

Year 2025, Volume: 15 Issue: 3, 1583 - 1612, 28.09.2025

Nilhan Sümeyra Güler , Zehra Akınç , Hayal Yavuz Mumcu

https://doi.org/10.48146/odusobiad.1612459

Abstract

The aim of this research is to examine the acquisitions in the secondary school mathematics curriculum in the context of computational thinking skills. For this purpose, first of all, the indicators of computational thinking skills were created by the literature, and then the acquisitions in the relevant curriculum were examined in relation to the indicators in question. The research, employing the document analysis method, utilized content analysis during the data analysis process. According to the results obtained from the research, it was seen that approximately 44% of the acquisitions in the curriculum were related to the algorithm dimension, 28% with pattern-model extraction, and 21% with abstraction. However, it has been observed that acquisitions in the domain of numbers and operations are particularly associated with the 'algorithm' dimension, acquisitions in algebra and geometry and measurement learning domains are linked with 'pattern-model extraction,' acquisitions in data processing learning domain are related to 'evaluation and debugging,' and achievements in probability learning domain are strongly correlated with the dimensions of 'abstraction' and 'pattern-model extraction’. When considering different grade levels, it has been concluded that dimensions associated with 5th and 8th-grade acquisitions are respectively ranked as 'algorithm,' 'pattern-model extraction,' and 'abstraction,' while dimensions related to 6th and 7th-grade acquisitions are listed as 'algorithm,' 'pattern-model extraction,' and 'decomposition'.

Keywords

Computational thinking Middle school mathematics curriculum Document analysis

References

  • Aho, A. V. (2012). Computation and computational thinking. The Computer Journal, 55(7), 832-835. https://doi.org/10.1093/comjnl/bxs074.
  • Aktaş, S. E. (2022). Matematik öğretmeni adaylarının teknoloji destekli matematiksel modelleme sürecindeki bilgi işlemsel düşünmeye ilişkin zihinsel eylemlerinin incelenmesi [Yayınlanmamış yüksek lisans tezi]. Pamukkale Üniversitesi, Denizli.
  • Barcelos, T. S., & Silveira, I. F. (2012). Teaching computational thinking in initial series an analysis of the confluence among mathematics and computer sciences in elementary education and its implications for higher education. In 2012 XXXVIII Conferencia Latinoamericana En Informatica (CLEI) (pp. 1-8). IEEE. https://doi.org/10.1109/CLEI.2012.6427135
  • Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12: What is involved and what is the role of the computer science education community? ACM Inroads, 2(1), 48-54. https://doi.org/10.1145/1929887.1929905
  • Computer Science Teachers Association [CSTA] (2020). Standards for computer science teachers. https://csteachers.org/teacherstandards.
  • Costa, E. J. F., Campos, L. M. R. S., & Guerrero, D. D. S. (2017). Computational thinking in mathematics education: A joint approach to encourage problem-solving ability. In 2017 IEEE Frontiers in Education Conference (FIE) (pp. 1-8). IEEE. https://doi.org/10.1109/FIE.2017.8190655.
  • Curzon, P. (2015). Computational thinking: Searching to speak. http://www.inf.ed.ac.uk/publications/online/1245.pdf.
  • Demir, Ü., & Cevahir, H. (2020). Algoritmik düşünme yeterliliği ile problem çözme becerisi arasındaki ilişkinin incelenmesi: Mesleki ve Teknik Anadolu Lisesi örneği. Kastamonu Eğitim Dergisi, 28(4), 1610-1619. https://doi.org/10.24106/kefdergi.4179.
  • Denning, P. J. (2009). The profession of IT beyond computational thinking. Communications of the ACM, 52(6), 28-30. https://doi.org/10.1145/1516046.1516054
  • Eisenberg, M. (2002). Output devices, computation, and the future of mathematical crafts. International Journal of Computers for Mathematical Learning, 7, 1-44.
  • English, L. (2018). On MTL’s second milestone: Exploring computational thinking and mathematics learning. Mathematical Thinking and Learning, 20(1), 1-2. https://doi.org/10.1080/10986065.2018.1405615
  • Erümit, K. A., Karal, H., Şahin, G., Aksoy, D. A., Aksoy, A., & Benzer, A. İ. (2018). Programlama öğretimi için bir model önerisi: Yedi adımda programlama. Eğitim ve Bilim, 44(197), 155-183.http://dx.doi.org/10.15390/EB.2018.7678.
  • Gadanidis, G., Hughes, J. M., Minniti, L., & White, B. J. G. (2017). Computational thinking, grade 1 students and the binomial theorem. Digital Experiences in Mathematics Education, 3, 77-96. https://doi.org/10.1007/s40751-016-0019-3. Gonzalez, R., Gonzalez, P. & Fernandez, J. (2017). Which cognitive abilities underlie computational thinking? Criterion validity of the Computational Thinking Test. Computers in Human Behavior, 72, 678–691. https://doi.org/10.1016/j.chb.2016.08.047.
  • Gülbahar, Y., Kert, S. B., & Kalelioğlu, F. (2019). Bilgi işlemsel düşünme becerisine yönelik öz yeterlik algısı ölçeği: Geçerlik ve güvenirlik çalışması. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 10(1), 1-29. https://doi.org/10.16949/turkbilmat.385097.
  • Guzdial, M. (1994). Software-realized scaffolding to facilitate programming for science learning. Interactive Learning Environments, 4(1), 1–44. https://doi.org/10.1080/1049482940040101.
  • Hickmott, D., Prieto-Rodriguez, E., & Holmes, K. (2018). A scoping review of studies on computational thinking in K–12 mathematics classrooms. Digital Experiences in Mathematics Education, 4, 48-69. https://doi.org/10.1007/s40751-017-0038-8.
  • International Society for Technology in Education [ISTE] (2016). ISTE standards for students: A practical guide for learning with technology. Washington, DC: Author.
  • Kong, S. C. (2016). A framework of curriculum design for computational thinking development in K-12 education. Journal of Computers in Education, 3(4), 377-394. https://doi.org/10.1007/s40692-016-0076-z.
  • Lu, J. J., & Fletcher, G. H. (2009). Thinking about computational thinking. In Proceedings of the 40th ACM technical symposium on Computer science education (pp. 260-264). Chattanooga, Tenessee, USA.
  • Mannila, L., Dagiene, V., Demo, B., Grgurina, N., Mirolo, C., Rolandsson, L., & Settle, A. (2014). Computational thinking in K-9 education. In Proceedings of the working group reports of the 2014 on innovation & technology in computer science education conference (pp. 1-29). ACM.
  • MEB. (2018a). Bilişim teknolojileri ve yazılım dersi öğretim programı: 5. ve 6. sınıflar. Ankara: MEB.
  • MEB. (2018b). Bilişim teknolojileri ve yazılım dersi öğretim programı: İlkokul 1, 2, 3 ve 4. sınıflar. Ankara: MEB.
  • MEB. (2018c). Matematik dersi öğretim programı (İlkokul ve Ortaokul 1, 2, 3, 4, 5, 6, 7 ve 8. Sınıflar). Ankara: MEB.
  • Miles, M, B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook. (2nd ed). Sage.
  • National Research Council (2011a). Learning science through computer games and simulations. The National Academies Press, Washington, DC. https://ics.uci.edu/~wscacchi/GameLab/Recommended%20Readings/Learning-Science-Games-2011.pdf.
  • National Research Council (2011b). Report of a workshop of pedagogical aspects of computational thinking. The National Academies Press, Washington, DC. https://people.cs.vt.edu/~kafura/CS6604/Papers/NRC-Pegagogy-CT.pdf.
  • Ndlovu, M., Wessels, D., & De Villiers, M. (2011). An instrumental approach to modelling the derivative in Sketchpad. Pythagoras, 32(2), 1-15. https://hdl.handle.net/10520/EJC20946.
  • Niemelä, P., Pears, A., Dagienė, V., & Laanpere, M. (2022). Computational thinking – Forces shaping curriculum and policy in Finland, Sweden and the Baltic countries. In D. Passey, D. Leahy, L. Williams, J. Holvikivi, & M. Ruohonen (Eds.), Digital transformation of education and learning—past, present and future (C. 642, ss. 131-143). Springer International Publishing. https://doi.org/10.1007/978-3-030-97986-7_11.
  • OECD (Organisation for Economic Co-operation and Development) (2022). PISA 2022 assessment and analytical framework. https://doi.org/10.1787/dfe0bf9c-en.
  • Oluk, A. (2017). Öğrencilerin bilgisayarca düşünme becerilerinin mantıksal matematiksel zekâ ve matematik akademik başarıları açısından incelenmesi [Yayınlanmamış yüksek lisans tezi]. Amasya Üniversitesi, Amasya.
  • Papert, S. (1996). An exploration in the space of mathematics educations. International Journal of Computers for Mathematical Learning, 1(1), 138-142.
  • Patan B., (2016). Okul öncesi kodlama öğretim programının geliştirilmesi [Yayınlanmamış yüksek lisans tezi]. Bahçeşehir Üniversitesi, İstanbul.
  • Patton, M. Q. (2014). Nitel araştırma ve değerlendirme yöntemleri (3. baskı) (Çev. Ed. M. Bütün & S. B. Demir). Ankara: Pegem Akademi.
  • Repenning, A., Webb, D., Ioannidou, A. (2010). Scalable game design and the development of a checklist for getting computational thinking into public schools. In Proceedings of the 41st ACM technical symposium on computer science education (pp 265–269). ACM. https://dl.acm.org/doi/10.1145/1734263.1734357.
  • Sengupta, P., Kinnebrew, J. S., Basu, S., Biswas, G., & Clark, D. (2013). Integrating computational thinking with K-12 science education using agent-based computation: A theoretical framework. Education and Information Technologies, 18, 351-380. https://doi.org/10.1007/s10639-012-9240-x.
  • Sneider, C., Stephenson, C., Schafer, B., & Flick, L. (2014). Exploring the science framework and NGSS: Computational thinking in the science classroom. Science Scope, 38(3), 10-15.
  • Temel, B. (2022). Bilgi işlemsel düşünme etkinliklerinin 7. sınıf öğrencilerinin problem çözmeye yönelik beceri ve tutumlarına etkisi [Yayınlanmamış yüksek lisans tezi]. Ordu Üniversitesi, Ordu.
  • Üzümcü, Ö. (2022). İlkokul matematik öğretim programının bilgi işlemsel düşünme boyutlarını içerme durumunun analizi. 10. Uluslararası Eğitim Programları ve Öğretim Kongresi özet bildiri kitapçığı içinde (ss. 833-835). Ankara: Gazi Üniversitesi Yayınları.
  • Üzümcü, Ö., & Bay, E. (2018). Eğitimde yeni 21. yüzyıl becerisi: Bilgi işlemsel düşünme. Uluslararası Türk Kültür Coğrafyasında Sosyal Bilimler Dergisi, 3(2), 1-16.
  • Üzümcü, Ö., & Bay, E. (2021). Bilgisayarsız kodlama eğitiminde bilgi işlemsel düşünme. Ankara: Akademisyen Kitabevi.
  • Van Merrienboer, J. J. (2013). Perspectives on problem solving and instruction. Computers & Education, 64, 153-160. https://doi.org/10.1016/j.compedu.2012.11.025. Voskoglou, M. G., & Buckley, S. (2012). Problem solving and computational thinking in a learning environment. Egyptian Computer Science Journal, 36(4), 28–46. https://doi.org/10.48550/arXiv.1212.0750.
  • Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilenskey, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25, 127-147. https://doi.org/10.1007/s10956-015-9581-5.
  • Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25, 127-147. https://doi.org/10.1007/s10956-015-9581-5.
  • Weiser, M. (1982). Programmers use slices when debugging. Communications of the ACM, 25(7), 446-452. https://doi.org/10.1145/358557.358577.
  • Wilensky, U., & Reisman, K. (2006). Thinking like a wolf, a sheep, or a firefly: Learning biology through constructing and testing computational theories—an embodied modeling approach. Cognition and Instruction, 24(2), 171-209. https://doi.org/10.1207/s1532690xci2402_1.
  • Wilensky, U., Brady, C. E., & Horn, M. S. (2014). Fostering computational literacy in science classrooms. Communications of the ACM, 57(8), 24-28. https://doi.org/10.1145/2633031.
  • Wilson, C., & Guzdial, M. (2010). How to make progress in computing education. Communications of the ACM, 53(5), 35-37. https://doi.org/10.1145/1735223.1735235.
  • Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35. https://doi.org/10.1145/1118178.1118215.
  • Wing, J. M. (2008). Computational thinking and thinking about computing. Philosophical transactions: Mathematical, physical and engineering sciences, 366(1881), 3717-3725. https://doi.org/10.1098/rsta.2008.0118.
  • Wing, J. M. (2011). Research notebook: Computational thinking—What and why. The Link Magazine, 6, 20-23. https://people.cs.vt.edu/~kafura/CS6604/Papers/CT-What-And-Why.pdf.
  • Yadav, A., Hong, H., & Stephenson, C. (2016). Computational thinking for all: Pedagogical approaches to embedding 21st century problem solving in K-12 classrooms. Tech Trends, 60, 565-568. https://doi.org/10.1007/s11528-016-0087-7.
  • Yadav, A., Zhou, N., Mayfield, C., Hambrusch, S., & Korb, J. T. (2011). Introducing computational thinking in education courses. In Proceedings of the 42nd ACM Technical Symposium on Computer Science Education, (pp. 465-470). https://doi.org/10.1145/1953163.1953297.
  • Yıldırım, A., & Şimşek, H. (2021). Sosyal bilimlerde nitel araştırma yöntemleri (12. baskı). Ankara: Seçkin Yayıncılık
There are 53 citations in total.

Details

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

Nilhan Sümeyra Güler 0009-0003-6108-7496

Zehra Akınç 0009-0002-2461-7278

Hayal Yavuz Mumcu 0000-0002-6720-509X

Publication Date September 28, 2025
Submission Date January 3, 2025
Acceptance Date July 7, 2025
Published in Issue Year 2025 Volume: 15 Issue: 3

Cite

APA Güler, N. S., Akınç, Z., & Yavuz Mumcu, H. (2025). Examination of middle school mathematics curriculum in the context of computational thinking skills. Ordu Üniversitesi Sosyal Bilimler Enstitüsü Sosyal Bilimler Araştırmaları Dergisi, 15(3), 1583-1612. https://doi.org/10.48146/odusobiad.1612459
 Download Cover Image

With the wish to be enlightened by the light of knowledge…
ODÜSOBİAD