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Year 2025, Volume: 14 Issue: 4, 1178 - 1192, 30.10.2025
https://doi.org/10.14686/buefad.1689128

Abstract

References

  • Aho, A. V. (2012). Computation and computational thinking. The Computer Journal, 55(7), 832–835.
  • Angeli, C., Voogt, J., Fluck, A., Webb, M., Cox, M., Malyn-Smith, J., & Zagami, J. (2016). A K-6 computational thinking curriculum framework: Implications for teacher knowledge. Journal of Educational Technology & Society, 19(3), 47-57.
  • Aranda, G., & Ferguson, R. (2018). Supporting computational thinking through programming in K–12 education: A review of the evidence. British Journal of Educational Technology, 49(6), 989–1000. https://doi.org/10.1111/bjet.12664
  • Ausiku, M. M., & Matthee, M. C. (2023). A framework for teaching computational thinking in primary schools: A Namibian case study. The African Journal of Information Systems, 15(3), 175-206.
  • Avşar, M. (2023). Okul öncesi öğretmenlerinin bilgi-işlemsel düşünme becerilerinin desteklenmesi: Tasarım temelli hizmet içi eğitimin etkisi [Doktora tezi, Hacettepe Üniversitesi, Eğitim Bilimleri Enstitüsü]. Yükseköğretim Kurulu Ulusal Tez Merkezi. Tez No: 792662.
  • Aytaç, A. (2021). A study of teachers’ self-efficacy beliefs, motivation to teach, and curriculum fidelity: A path analysis model. International Journal of Contemporary Educational Research, 8(4), 130-143. https://doi.org/10.33200/ijcer.898186
  • Aytaç, A. 2021. “A Study of Teachers' Self-Efficacy Beliefs, Motivation toTeach, and Curriculum Fidelity: A Path Analysis Model.” InternationalJournal of Contemporary Educational Research 8, no. 4: 130–143. https://doi.org/10.33200/ijcer.898186
  • Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37(2), 122–147. https://doi.org/10.1037/0003-066X.37.2.122
  • Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman and Company.
  • 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.
  • Bean, N., Weese, J., Feldhaus, C., & Krause, J. (2015). Infusing computational thinking into the middle school curriculum. Journal of Computing Sciences in Colleges, 30(5), 87–92.
  • Beecher, K. (2017). Computational Thinking. A beginner’s guide to problem solving and programming. BCS Learning & Development.
  • Bers, M. U. (2018). Coding and computational thinking in early childhood: The impact of ScratchJr in Europe. European Journal of STEM Education, 3(3), 08. https://doi.org/10.20897/ejsteme/3868
  • Bers, M. U. (2020). Coding as a Playground: Programming and Computational Thinking in the Early Childhood Classroom. Routledge.
  • Bers, M. U., Flannery, L., Kazakoff, E. R., & Sullivan, A. (2014). Computational thinking and tinkering: Exploration of an early childhood robotics curriculum. Computers and Education 72, 145–157.
  • Bocconi, S., Chioccariello, A., Dettori, G., & Engelhardt, K. (2016). Developing computational thinking in compulsory education – Implications for policy and practice. European Commission Joint Research Centre. https://doi.org/10.2791/792158
  • Brown, T. A. (2015). Confirmatory factor analysis for applied research (2nd ed.). The Guilford Press.
  • Bryman, A., & Cramer, D. (2002). Quantitative data analysis with SPSS release 10 for Windows: A guide for social scientists. Routledge.
  • Büyüköztürk, Ş. (2017). Sosyal bilimler için veri analizi el kitabı: İstatistik, araştırma deseni, SPSS uygulamaları ve yorum (23. Baskı). Ankara: Pegem Akademi Yayıncılık.
  • Cabrera, L., Byrne, V., Jass Ketelhut, D., Coenraad, M., Killen, H., & Plane, J. (2021). Measuring teacher self-efficacy for integrating computational thinking in science (T-SelECTS). Educational Innovations and Emerging Technologies, 1(1), 3-14.
  • Çelik, H. E., & Yılmaz, V. (2016). LISREL 9.1 ile yapısal eşitlik modellemesi: Temel kavramlar-uygulamalar-programlama (3. Baskı). Anı Yayıncılık.
  • Çetin, İ., & Toluk Uçar, Z. (2017). Bilgi-işlemsel düşünme tanımı ve kapsamı. In Y. Gülbahar (Ed.), Bilgi-işlemsel düşünmeden programlamaya (ss. 41–74). Pegem Akademi Yayıncılık.
  • Comrey, A. L., & Lee, H. B. (1992). A first course in factor analysis (2nd Ed.). Lawrence Erlbaum Associates, Inc., 216.
  • Crocker, L., & Algina, J. (1986). Introduction to classical and modern test theory. Holt, Rinehart and Winston.
  • Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1–4. https://doi.org/10.11648/j.ajtas.20160501.11
  • Fang, Z. (1996). A review of research on teacher beliefs and practices. Educational Researcher, 38(1), 47–65. https://doi.org/10.3102/0013189X038001047
  • Geisinger, K. F. (1994). Cross-cultural normative assessment: Translation and adaptation issues influencing the normative interpretation of assessment instruments. Psychological Assessment, 6(4), 304–312. https://doi.org/10.1037/1040-3590.6.4.304
  • George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference (4th ed.). Boston: Allyn & Bacon.
  • Gonzalez, M. R. (2015). Computational thinking test: Design guidelines and content validation. In Proceedings of EDULEARN15 Conference (2436-2444). Barcelona, Spain.
  • Göncü, A., Çetin, İ., & Top, E. (2018). Öğretmen adaylarının kodlama eğitimine yönelik görüşleri: Bir durum çalışması. Mehmet Akif Ersoy Üniversitesi Eğitim Fakültesi Dergisi, (48), 85-110.
  • Gretter, S., & Yadav, A. (2016). Computational thinking and media & information literacy: An integrated approach to teaching twenty-first century skills. TechTrends, 60(5), 510-516.
  • Grover, S., & Pea, R. (2013). Computational thinking in K-12: A review of the state of the field. Educational Researcher, 42(1), 38–43.
  • Gülbahar, Y., Kert, S. B., & Kalelioğlu, F. (2018). Bilgi İşlemsel Düşünme Becerisine Yönelik Öz Yeterlik Algısı Ölçeği (BİDBÖA): Geçerlik ve güvenirlik çalışması. Türk Bilgisayar ve Matematik Eğitimi Dergisi. Advance online publication. https://doi.org/10.16949/turkbilmat.385097
  • Hambleton, R. K., Merenda, P. F., & Spielberger, C. D. (Eds.). (2005). Adapting educational and psychological tests for cross-cultural assessment. Psychology Press.
  • Hooper, D., Coughlan, J. İ., & Mullen, M. R. (2008). Structural equation modelling: Guidelines for determining model fit. Electronic Journal of Business Research Methods, 6(1), 53–60.
  • Hu, C. (2011). Computational thinking: what it might mean and what we might do about it. In Proceedings of the 16th Annual Joint Conference on Innovation and Technology in Computer Science Education (pp. 223-227).
  • Institute for Advancing Computing Education. (2019). Teacher beliefs about coding and computational thinking (TBaCCT). https://csedresearch.org/resources/evaluation-instruments/tool/?id=210
  • Kalelioğlu, F. (2018). Bilgisayarsız bilgisayar bilimi (B3) öğretimi. Y. Gülbahar (Ed.). In Bilgi-işlemsel düşünmeden programlamaya (s. 183-204). Ankara: Pegem Akademi Yayıncılık
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Preschool Teachers' Coding and Computational Thinking Skills: A Scale Adaptation Study

Year 2025, Volume: 14 Issue: 4, 1178 - 1192, 30.10.2025
https://doi.org/10.14686/buefad.1689128

Abstract

This study aimed to adapt the “Teacher Beliefs about Coding and Computational Thinking Scale (TBCCTS)” developed by Rich, Larsen, and Mason, which measures preschool perspectives on computational thinking and coding, into Turkish and preschool education and to analyse the psychometric properties of the scale. The study group of the research include of 201 preschool teachers. Various data analyses were conducted about the measurement tool's validity and reliability. Based on Confirmatory Factor Analysis findings regarding construct validity, it was determined that one of the goodness of fit indices was acceptable and the other four values showed excellent fit. It was seen that the 4-dimensional structure of the 33 items of the original scale was confirmed within the scope of this research. In this context, the adapted scale consists of 4 dimensions and 33 items. Factor values ranged between 0.35-0.92. As a result of the reliability analysis of the scale, it was found that the Cronbach alpha coefficient was 0.91 and the sub-dimensions ranged between 0.87-0.94. The study found that the scale was a viable and reliable way to measure preschool teachers' perceptions of computational thinking and coding.

References

  • Aho, A. V. (2012). Computation and computational thinking. The Computer Journal, 55(7), 832–835.
  • Angeli, C., Voogt, J., Fluck, A., Webb, M., Cox, M., Malyn-Smith, J., & Zagami, J. (2016). A K-6 computational thinking curriculum framework: Implications for teacher knowledge. Journal of Educational Technology & Society, 19(3), 47-57.
  • Aranda, G., & Ferguson, R. (2018). Supporting computational thinking through programming in K–12 education: A review of the evidence. British Journal of Educational Technology, 49(6), 989–1000. https://doi.org/10.1111/bjet.12664
  • Ausiku, M. M., & Matthee, M. C. (2023). A framework for teaching computational thinking in primary schools: A Namibian case study. The African Journal of Information Systems, 15(3), 175-206.
  • Avşar, M. (2023). Okul öncesi öğretmenlerinin bilgi-işlemsel düşünme becerilerinin desteklenmesi: Tasarım temelli hizmet içi eğitimin etkisi [Doktora tezi, Hacettepe Üniversitesi, Eğitim Bilimleri Enstitüsü]. Yükseköğretim Kurulu Ulusal Tez Merkezi. Tez No: 792662.
  • Aytaç, A. (2021). A study of teachers’ self-efficacy beliefs, motivation to teach, and curriculum fidelity: A path analysis model. International Journal of Contemporary Educational Research, 8(4), 130-143. https://doi.org/10.33200/ijcer.898186
  • Aytaç, A. 2021. “A Study of Teachers' Self-Efficacy Beliefs, Motivation toTeach, and Curriculum Fidelity: A Path Analysis Model.” InternationalJournal of Contemporary Educational Research 8, no. 4: 130–143. https://doi.org/10.33200/ijcer.898186
  • Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37(2), 122–147. https://doi.org/10.1037/0003-066X.37.2.122
  • Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman and Company.
  • 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.
  • Bean, N., Weese, J., Feldhaus, C., & Krause, J. (2015). Infusing computational thinking into the middle school curriculum. Journal of Computing Sciences in Colleges, 30(5), 87–92.
  • Beecher, K. (2017). Computational Thinking. A beginner’s guide to problem solving and programming. BCS Learning & Development.
  • Bers, M. U. (2018). Coding and computational thinking in early childhood: The impact of ScratchJr in Europe. European Journal of STEM Education, 3(3), 08. https://doi.org/10.20897/ejsteme/3868
  • Bers, M. U. (2020). Coding as a Playground: Programming and Computational Thinking in the Early Childhood Classroom. Routledge.
  • Bers, M. U., Flannery, L., Kazakoff, E. R., & Sullivan, A. (2014). Computational thinking and tinkering: Exploration of an early childhood robotics curriculum. Computers and Education 72, 145–157.
  • Bocconi, S., Chioccariello, A., Dettori, G., & Engelhardt, K. (2016). Developing computational thinking in compulsory education – Implications for policy and practice. European Commission Joint Research Centre. https://doi.org/10.2791/792158
  • Brown, T. A. (2015). Confirmatory factor analysis for applied research (2nd ed.). The Guilford Press.
  • Bryman, A., & Cramer, D. (2002). Quantitative data analysis with SPSS release 10 for Windows: A guide for social scientists. Routledge.
  • Büyüköztürk, Ş. (2017). Sosyal bilimler için veri analizi el kitabı: İstatistik, araştırma deseni, SPSS uygulamaları ve yorum (23. Baskı). Ankara: Pegem Akademi Yayıncılık.
  • Cabrera, L., Byrne, V., Jass Ketelhut, D., Coenraad, M., Killen, H., & Plane, J. (2021). Measuring teacher self-efficacy for integrating computational thinking in science (T-SelECTS). Educational Innovations and Emerging Technologies, 1(1), 3-14.
  • Çelik, H. E., & Yılmaz, V. (2016). LISREL 9.1 ile yapısal eşitlik modellemesi: Temel kavramlar-uygulamalar-programlama (3. Baskı). Anı Yayıncılık.
  • Çetin, İ., & Toluk Uçar, Z. (2017). Bilgi-işlemsel düşünme tanımı ve kapsamı. In Y. Gülbahar (Ed.), Bilgi-işlemsel düşünmeden programlamaya (ss. 41–74). Pegem Akademi Yayıncılık.
  • Comrey, A. L., & Lee, H. B. (1992). A first course in factor analysis (2nd Ed.). Lawrence Erlbaum Associates, Inc., 216.
  • Crocker, L., & Algina, J. (1986). Introduction to classical and modern test theory. Holt, Rinehart and Winston.
  • Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1–4. https://doi.org/10.11648/j.ajtas.20160501.11
  • Fang, Z. (1996). A review of research on teacher beliefs and practices. Educational Researcher, 38(1), 47–65. https://doi.org/10.3102/0013189X038001047
  • Geisinger, K. F. (1994). Cross-cultural normative assessment: Translation and adaptation issues influencing the normative interpretation of assessment instruments. Psychological Assessment, 6(4), 304–312. https://doi.org/10.1037/1040-3590.6.4.304
  • George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference (4th ed.). Boston: Allyn & Bacon.
  • Gonzalez, M. R. (2015). Computational thinking test: Design guidelines and content validation. In Proceedings of EDULEARN15 Conference (2436-2444). Barcelona, Spain.
  • Göncü, A., Çetin, İ., & Top, E. (2018). Öğretmen adaylarının kodlama eğitimine yönelik görüşleri: Bir durum çalışması. Mehmet Akif Ersoy Üniversitesi Eğitim Fakültesi Dergisi, (48), 85-110.
  • Gretter, S., & Yadav, A. (2016). Computational thinking and media & information literacy: An integrated approach to teaching twenty-first century skills. TechTrends, 60(5), 510-516.
  • Grover, S., & Pea, R. (2013). Computational thinking in K-12: A review of the state of the field. Educational Researcher, 42(1), 38–43.
  • Gülbahar, Y., Kert, S. B., & Kalelioğlu, F. (2018). Bilgi İşlemsel Düşünme Becerisine Yönelik Öz Yeterlik Algısı Ölçeği (BİDBÖA): Geçerlik ve güvenirlik çalışması. Türk Bilgisayar ve Matematik Eğitimi Dergisi. Advance online publication. https://doi.org/10.16949/turkbilmat.385097
  • Hambleton, R. K., Merenda, P. F., & Spielberger, C. D. (Eds.). (2005). Adapting educational and psychological tests for cross-cultural assessment. Psychology Press.
  • Hooper, D., Coughlan, J. İ., & Mullen, M. R. (2008). Structural equation modelling: Guidelines for determining model fit. Electronic Journal of Business Research Methods, 6(1), 53–60.
  • Hu, C. (2011). Computational thinking: what it might mean and what we might do about it. In Proceedings of the 16th Annual Joint Conference on Innovation and Technology in Computer Science Education (pp. 223-227).
  • Institute for Advancing Computing Education. (2019). Teacher beliefs about coding and computational thinking (TBaCCT). https://csedresearch.org/resources/evaluation-instruments/tool/?id=210
  • Kalelioğlu, F. (2018). Bilgisayarsız bilgisayar bilimi (B3) öğretimi. Y. Gülbahar (Ed.). In Bilgi-işlemsel düşünmeden programlamaya (s. 183-204). Ankara: Pegem Akademi Yayıncılık
  • Kalelioğlu, F., Gülbahar, Y., & Kukul, V. (2016). A framework for computational thinking based on a systematic research review. Baltic Journal of Modern Computing, 4(3), 583-596.
  • Karaman, U., & Büyükalan Filiz, S. (2019). Kodlama eğitimine yönelik tutum ölçeği’nin (KEYTÖ) geliştirilmesi. Gelecek Vizyonlar Dergisi, 3(2), 36-47.
  • Kesici, T., & Kocabaş, Z. (2006). Bilgisayar 2 Ders Kitabı. Ankara: Milli Eğitim Bakanlığı Yayınları.
  • Khanlari, A. (2016). Teachers’ perceptions of the benefits and the challenges of integrating educational robots into primary/elementary curricula. European Journal of Engineering Education, 41(3), 320-330.
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There are 82 citations in total.

Details

Primary Language English
Subjects Cross-Cultural Scale Adaptation
Journal Section Research Article
Authors

Merve Avşar 0000-0002-1435-8383

Mine Canan Durmuşoğlu 0000-0001-6777-9117

Submission Date May 2, 2025
Acceptance Date September 9, 2025
Publication Date October 30, 2025
Published in Issue Year 2025 Volume: 14 Issue: 4

Cite

APA Avşar, M., & Durmuşoğlu, M. C. (2025). Preschool Teachers’ Coding and Computational Thinking Skills: A Scale Adaptation Study. Bartın University Journal of Faculty of Education, 14(4), 1178-1192. https://doi.org/10.14686/buefad.1689128

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