Journals / Türk Bilgisayar ve Matematik Eğitimi Dergisi / 2019 / Cilt: 10 - Sayı: 1

The Self-Efficacy Perception Scale for Computational Thinking Skill: Validity and Reliability Study

Bilgi İşlemsel Düşünme Becerisine Yönelik Öz Yeterlik Algısı Ölçeği: Geçerlik ve Güvenirlik Çalışması

Pages
1–29
Publication Date
2019-04-10
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Also, t-tests for the item average means of the bottom and top 27% of the groups were presented significant differences between those groups.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In recent years, developments in the field of computer science, which are in parallel with technology, have led to an increase in the importance of solving problems with the help of computers.
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Key Findings & Data:As a result of the exploratory factor analyzes made, it was seen that the scale includes 39 items with five-factors.
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Conclusion & Impact:Also, t-tests for the item average means of the bottom and top 27% of the groups were presented significant differences between those groups.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:algoritma · programlama · öz-yeterlik

Abstract

In recent years, developments in the field of computer science, which are in parallel with technology, have led to an increase in the importance of solving problems with the help of computers. It is also worth mentioning that this skill, which is defined as computational thinking, has been an issue about how to be taught and evaluated. In this context, the aim of this study is to develop a self-efficacy perception scale for the computational thinking skill. As a result of the exploratory factor analyzes made, it was seen that the scale includes 39 items with five-factors. Additionally, with confirmatory factor analysis which was carried out for confirmation of the model, 3 items were omitted from the scale and the last structure of the form, with 36 items, was presented. The corrected item-total correlations were ranged between 0.632 and 0.386, whereas the Cronbach Alpha coefficients were between 0.762 and 0.930. Also, t-tests for the item average means of the bottom and top 27% of the groups were presented significant differences between those groups.

Özet

Son yıllarda bilgisayar bilimi alanında teknolojiye paralel olarak yaşanan gelişmeler, problemlerin bilgisayarlar yardımı ile çözülmesine verilen önemin artmasına neden olmuştur. Bilgi işlemsel düşünme (computational thinking) olarak tanımlanan bu becerinin kazandırılmasının önemi ile birlikte bu becerinin kazanılıp kazanılmadığının ortaya konması da gündeme gelmiştir. Bu bağlamda çalışmanın amacı bilgi işlemsel düşünme becerisine yönelik öz yeterlik algı ölçeği geliştirmektir. Yapılan açımlayıcı faktör analizleri sonucunda toplam 39 maddeyi içeren ölçeğin beş faktörlü bir yapıdan oluştuğu görülmüştür. Ek olarak, modelin doğrulanması amacıyla gerçekleştirilen doğrulayıcı faktör analizi ile 3 madde ölçekten çıkarılmış ve 36 maddelik son form yapısı ortaya sunulmuştur. Faktörlerin düzeltilmiş madde-toplam puan korelasyon değerlerinin 0.632 ile 0.386 arasında olduğu, Cronbach Alfa katsayılarının ise 0.762 ile 0.930 arasında değiştiği görülmüştür. T-testi sonuçları, üst %27 ile alt %27 grupların madde ortalamaları arasındaki tüm farkların anlamlı olduğunu göstermiştir.

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Cite This Article

Gülbahar, Y., Kert, S. B., Kalelioğlu, F. (2019). The Self-Efficacy Perception Scale for Computational Thinking Skill: Validity and Reliability Study. Türk Bilgisayar ve Matematik Eğitimi Dergisi, Cilt: 10 - Sayı: 1, 1–29. https://ajindex.com/articles/241280

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References (6)

  1. 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. Educational Technology & Society, 19(3), 47–57.
  2. Apostolellis, P., Stewart, M., Frisina, C., & Kafura, D. (2014, June). RaBit escApe: A board game for computational thinking. Paper presented at the Interaction Design and Children Conference, Denmark. 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.
  3. Barr, D., Harrison, J., & Conery, L. (2011). Computational thinking: A digital age skill for everyone. Learning & Leading with Technology, 38(6), 20-23.
  4. Basawapatna, A., Koh, K. H., Repenning, A., Webb, D. C., & Marshall, K. S. (2011, March). Recognizing computational thinking patterns. Paper presented at the 42nd ACM Technical Symposium on Computer Science Education, USA. Basawapatna, A., Repenning, A., Koh, K. H., & Savignano, M. (2014, March). The consume - create spectrum: Balancing convenience and computational thinking in stem learning. Paper presented at the 45th ACM Technical Symposium on Computer Science Education, USA. Basawapatna, A., Repenning, R., & Lewis, C. (2013, March). The simulation creation toolkit: An ınitial exploration ınto making programming accessible while preserving computational thinking. Paper presented at the 44th ACM Technical Symposium on Computer Science Education, USA. Bocconi, S., Chioccariello, A., Dettori, G., Ferrari, A., Engelhardt, K., Kampylis, P., & Punie, Y. (2016). Developing computational thinking in compulsory education. Retrieved August 12, 2018 from http://publications.jrc.ec.europa.eu/repository/bitstream/JRC104188/jrc104188_computhinkreport.pdf.
  5. Bort, H., & Brylow, D. (2013, March). CS4Impact: Measuring computational thinking concepts. Paper presented at the the 44th ACM Technical Symposium on Computer Science Education, USA. Büyüköztürk, S. (2007). Sosyal bilimler için veri analizi el kitabı (8. baskı). Ankara:
  6. Pegem Yayıncılık. Brennan, K., & Resnick, M. (2012, April). Using artifact-based interviews to study the development of computational thinking in interactive media design. Paper presented at the Annual American Educational Research Association Meeting, Vancouver, BC, Canada. CSTA & ISTE (2011). Computational thinking in K–12 education leadership toolkit. Retrieved August 12, 2018 from http://csta.a