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Developing Computational Thinking Skills through Computer Game Programming: A Framework for Middle School Students

Yıl 2024, , 467 - 486, 31.07.2024
https://doi.org/10.31592/aeusbed.1444312

Öz

This study aims to provide educators with a framework for the development and assessment of computational thinking skills through computer game programming. The framework consists of a series of computer game programming activities designed for students at the middle school level. The case study method was employed in the development of the framework. In this context, a literature review, needs analysis, learner analysis, and document analysis were conducted. Based on the literature, in the context of computational thinking skills; decomposition, pattern recognition, abstraction, algorithm design, and debugging were examined as computational thinking skills. Additionally, tinkering, creating, debugging, persevering, and collaborating were considered as problem-solving approaches in computational thinking. As a part of the needs and learner analyses, semi-structured interviews were organized with four teachers with at least five years of experience in the field of information technologies. For the document analysis, a detailed evaluation of the curricula of different countries, guidelines, and reports from national and international organizations was carried out in terms of computational thinking skills. Content analysis was used to analyze the data collected from the documents accessed and the interview forms developed by the researchers. As a result, a framework has been developed that includes learning activities and outcomes for middle school students. This framework has the potential to enhance the computational thinking and computer game programming skills of middle school students, as well as provide guidance on how these activities can be implemented in educational environments.

Kaynakça

  • Angeli, C., Voogt, J., Fluck, A., Webb, M., Cox, M., Malyn-Smith, J., … Zagani, J. (2016). A K-6 computational thinking curriculum framework: Implication for teacher knowledge. Educational Technology & Society, 19(3), 47–57.
  • Australian Curriculum, Assessment and Reporting Authority. (2015). The shape of the Australian curriculum. Australian Government Publishing Service. Canberra. https://docs.acara.edu.au/resources/The_Shape_of_the_Australian_Curriculum_V3.pdf
  • Bai, H., Wang, X., & Zhao, L. (2021). Effects of the problem-oriented learning model on middle school students’ computational thinking skills in a python course. Frontiers in Psychology, 12, 771221.
  • 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.
  • Belmar, H. (2022). Review on the teaching of programming and computational thinking in the world. Frontiers in Computer Science, 4, 997222.
  • Berland, M., & Lee, V. R. (2011). Collaborative strategic board games as a site for distributed computational thinking. International Journal of Game-Based Learning, 1(2), 65–81.
  • Berry, M. (2015). QuickStart Primary Handbook: A CPD toolkit for primary teachers. British Computer Society.
  • Bers, M. U. (2021). From computational thinking to computational doing. In Teaching computational thinking and coding to young children (pp. 1–20). IGI Global.
  • Blikstein, P., Worsley, M., Piech, C., Sahami, M., Cooper, S., & Koller, D. (2014). Programming pluralism: Using learning analytics to detect patterns in the learning of computer programming. Journal of the Learning Sciences, 23(4), 561–599.
  • Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27–40.
  • Bufasi, E., Hoxha, M., Cuka, K., & Vrtagic, S. (2022). Developing student's comprehensive knowledge of physics concepts by using computational thinking activities: Effects of a 6-week intervention. International Journal of Emerging Technologies in Learning, 17(18).
  • Chen, C., Sonnert, G., Sadler, P. M., & Malan, D. J. (2020). Computational thinking and assignment resubmission predict persistence in a computer science MOOC. Journal of Computer Assisted Learning, 36(5), 581–594.
  • CollegeBoard (2015). AP Computer science: Principles. Course planning and pacing guide. https://apcentral.collegeboard.org/media/pdf/ap-comp-sci-principles-cppg-kick.pdf.
  • CollegeBoard (2016). AP Computer science: Principles. Course and exam description. https://secure-media.collegeboard.org/digitalServices/pdf/ap/ap-computer-science-principles-course-and-exam-description.pdf.
  • Computer Science Teacher Association. (2017). CSTA K-12 computer science standards, revised 2017. http://www.csteachers.org/standards.
  • Computing at School. (2012). Computer science: A curriculum for schools. http:// www.computingatschool.org.uk/data/uploads/ComputingCurric.pdf.
  • Computing at School. (2014). Computational thinking. CAS Barefoot. https://www.computingatschool.org.uk/media/kscbloob/computationalthinking.pdf.
  • Csizmadia, A., Curzon, P., Dorling, M., Humphreys, S., Ng, T., Selby, C., … Woollard, J. (2015). Computational thinking. A guide for teachers. Computing at School. Charlote BCS. The Chartered Institute for IT.
  • Csizmadia, A., Standl, B., & Waite, J. (2019). Integrating the constructionist learning theory with computational thinking classroom activities. Informatics in Education, 18(1), 41-67.
  • Curzon, P., Dorling, M., Ng, T., Selby, C., & Woollard, J. (2014). Developing computational thinking in the classroom: A framework. Swindon, GB. Computing at School.
  • Denning, P. J. (2017). Remaining trouble spots with computational thinking. Communications of the ACM, 60(6), 33–39.Department for Education (2013). Computing programmes of study: Key stages 1 and 2. National curriculum in England. https://www.gov.uk/government/publications/national-curriculum-in-england-computing-programmes-of-study.
  • Dorling, M., & Walker, M. (2014). Computing progression pathways with Computational thinking. Computing at School. http://community.computingatschool.org.uk/resources/2324.
  • Finnish National Board of Education (2016). Curriculum in Finland. https://www.dge.mec.pt/sites/default/files/Noticias_Imagens/1_curriculum_in_finland.pdf. Fulop, M. T., Udvaros, J., Guban, A., & Sandor, A. (2022). Development of computational thinking using microcontrollers integrated into OOP (Object-Oriented Programming). Sustainability, 14(12), 7218.
  • Futschek, G. (2006). Algorithmic thinking: The key for understanding computer science. International Conference on Informatics in Secondary Schools-Evolution and Perspectives, (pp. 159–168). Springer.
  • Grover, S., & Pea, R. (2018). Computational Thinking: A competency whose time has come. In S. I, E. Barendsen, & C. Shulte (Eds.), Computer science education: Perspectives on teaching and learning in school (pp. 19-37). Bloomsbury Academic.
  • Herrero-Alvarez, R., Miranda, G., Leon, C., & Segredo, E. (2022). Engaging Primary and Secondary School Students in Computer Science through Computational Thinking Training. IEEE Transactions on Emerging Topics in Computing, 11(1), 56-69.
  • Hunsaker, E. (2018). Understanding computational thinking. Brigham Young University, Provo.
  • International Society for Technology in Education. (2016). ISTE standards for students. ISTE. https://iste.org/standards/students
  • International Society for Technology in Education. (2017). ISTE standards for educators. https://iste.org/standards/educators.
  • Israel, M., Pearson, J. N., Tapia, T., Wherfel, Q. M., & Reese, G. (2015). Supporting all learners in school-wide computational thinking: A cross-case qualitative analysis. Computers & Education, 82(2015), 263–279.
  • Kılıç, S. (2023). Background of the Relationship between Programming and Computational Thinking. In Innovative Digital Practices and Globalization in Higher Education (pp. 203–224). IGI.
  • Kim, C., Belland, B. R., Baabdullah, A., Lee, E., Dinç, E., & Zhang, A. Y. (2021). An ethnomethodological study of abductive reasoning while tinkering. AERA Open, 7.
  • Kim, J., Leftwich, A., & Castner, D. (2024). Beyond teaching computational thinking: Exploring kindergarten teachers’ computational thinking and computer science curriculum design considerations. Education and Information Technologies, 1-37.
  • Kite, V., & Park, S. (2023). What’s computational thinking?: Secondary science teachers’ conceptualizations of computational thinking (CT) and perceived barriers to CT integration. Journal of Science Teacher Education, 34(4), 391-414.
  • Kite, V., & Park, S. (2024). Context matters: Secondary science teachers' integration of process‐based, unplugged computational thinking into science curriculum. Journal of Research in Science Teaching, 61(1), 203-227.
  • Krippendorff, K. (2004). Reliability in content analysis: Some common misconceptions and recommendations. Human Communication Research, 30, 411–433.
  • Kroustalli, C., & Xinogalos, S. (2021). Studying the effects of teaching programming to lower secondary school students with a serious game: A case study with Python and CodeCombat. Education and Information Technologies, 26(5), 6069-6095. Laura-Ochoa, L., & Bedregal-Alpaca, N. (2022). Incorporation of computational thinking practices to enhance learning in a programming course. International Journal of Advanced Computer Science and Applications, 13(2).
  • Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Sage.
  • Liu, Z., Zhi, R., Hicks, A. & Barnes, T., (2017). Understanding problem solving behavior of 6-8 graders in a debugging game. Computer Science Education, 27(1), 1–29.
  • Lockwood, J., & Mooney, A. (2018). Computational thinking in education: Where does it fit? A systematic literary review. International Journal of Computer Sciences and Engineering Systems, 2(1), 41–60.
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  • Mannila, L., Leinonen, T., Bauters, M., & Veermans, M. (2023). Student and teacher co-agency when combining CT with arts and design in a cross-curricular project. Computers and Education Open, 4, 100132.
  • Merriam, S. B. (2009). Qualitative research: A guide to design and implementation (3rd ed.). CA: Jossey-Bass.
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Bilgisayımsal Düşünme Becerilerinin Oyun Programlama Aracılığıyla Geliştirilmesi: Ortaokul Öğrencileri için Bir Çerçeve

Yıl 2024, , 467 - 486, 31.07.2024
https://doi.org/10.31592/aeusbed.1444312

Öz

Bu çalışmanın amacı, bilgisayar oyunu programlama aracılığıyla bilgisayımsal düşünme becerilerinin geliştirilmesi ve değerlendirilmesi için öğretmenlere bir çerçeve sunmaktır. Bu çerçeve, ortaokul düzeyindeki öğrenciler için tasarlanmış bir dizi bilgisayar oyunu programlama etkinliğinden oluşmaktadır. Çerçevenin geliştirme süreci, durum çalışması yöntemiyle biçimlendirilmiştir. Bu doğrultuda alanyazın taraması, ihtiyaç analizi, öğrenen analizi ve doküman incelemesi yapılmıştır. Alanyazından hareketle, bilgisayımsal düşünme becerileri bağlamında; parçalara ayırma, örüntü tanıma, soyutlama, algoritma tasarımı ve hata ayıklama incelenmiştir. Bilgisayımsal düşünmede problem çözme yaklaşımları olarak ise deneyimleme, üretme, hata ayıklama, azimli olma ve işbirliği yapma ele alınmıştır. İhtiyaç ve öğrenen analizleri kapsamında bilişim teknolojileri alanında en az beş yıllık tecrübeye sahip olan dört öğretmen ile yarı yapılandırılmış görüşmeler gerçekleştirilmiştir. Doküman incelemesi için ise farklı ülkelerin öğretim programlarının, ulusal ve uluslararası kuruluşların yönerge ve raporlarının bilgisayımsal düşünme becerileri açısından ayrıntılı bir değerlendirilmesi yapılmıştır. Araştırmacılar tarafından oluşturulan görüşme formları ve ulaşılan dokümanlardan toplanan verilerin çözümlenmesinde içerik analizinden faydalanılmıştır. Sonuç olarak, ortaokul öğrencilerine uygun öğrenme aktiviteleri ve kazanımlar içeren bir çerçeve geliştirilmiştir. Bu çerçevenin, öğrencilerin bilgisayar oyunu programlama ve bilgisayımsal düşünme becerilerinin geliştirilmesine yönelik düzenlenebilecek etkinlikler ve bu etkinliklerin öğretim ortamlarında nasıl uygulanacağı konusunda katkı getirebileceği ileri sürülebilir.

Etik Beyan

Araştırma için etik onay, Hacettepe Üniversitesi Sosyal ve Beşeri Bilimler Araştırma Etik Kurulu’ndan (Onay numarası: 35853172/433-3453) alınmıştır. Ayrıca araştırmaya, verilerin toplandığı ilin Milli Eğitim Müdürlüğü (Sayı: 79137285-605-E.12854266) tarafından uygulama izni verilmiştir.

Destekleyen Kurum

Bu çalışmada, birinci yazara Bilim İnsanı Destekleme Programı, 2211/E Doğrudan Yurt İçi Doktora Bursu ile TÜBİTAK tarafından destek sağlanmıştır (Başvuru No: 1649B031300059).

Teşekkür

Bu çalışma, ikinci yazarın danışmanlığını yürüttüğü birinci yazarın doktora tezinden üretilmiştir.

Kaynakça

  • Angeli, C., Voogt, J., Fluck, A., Webb, M., Cox, M., Malyn-Smith, J., … Zagani, J. (2016). A K-6 computational thinking curriculum framework: Implication for teacher knowledge. Educational Technology & Society, 19(3), 47–57.
  • Australian Curriculum, Assessment and Reporting Authority. (2015). The shape of the Australian curriculum. Australian Government Publishing Service. Canberra. https://docs.acara.edu.au/resources/The_Shape_of_the_Australian_Curriculum_V3.pdf
  • Bai, H., Wang, X., & Zhao, L. (2021). Effects of the problem-oriented learning model on middle school students’ computational thinking skills in a python course. Frontiers in Psychology, 12, 771221.
  • 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.
  • Belmar, H. (2022). Review on the teaching of programming and computational thinking in the world. Frontiers in Computer Science, 4, 997222.
  • Berland, M., & Lee, V. R. (2011). Collaborative strategic board games as a site for distributed computational thinking. International Journal of Game-Based Learning, 1(2), 65–81.
  • Berry, M. (2015). QuickStart Primary Handbook: A CPD toolkit for primary teachers. British Computer Society.
  • Bers, M. U. (2021). From computational thinking to computational doing. In Teaching computational thinking and coding to young children (pp. 1–20). IGI Global.
  • Blikstein, P., Worsley, M., Piech, C., Sahami, M., Cooper, S., & Koller, D. (2014). Programming pluralism: Using learning analytics to detect patterns in the learning of computer programming. Journal of the Learning Sciences, 23(4), 561–599.
  • Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27–40.
  • Bufasi, E., Hoxha, M., Cuka, K., & Vrtagic, S. (2022). Developing student's comprehensive knowledge of physics concepts by using computational thinking activities: Effects of a 6-week intervention. International Journal of Emerging Technologies in Learning, 17(18).
  • Chen, C., Sonnert, G., Sadler, P. M., & Malan, D. J. (2020). Computational thinking and assignment resubmission predict persistence in a computer science MOOC. Journal of Computer Assisted Learning, 36(5), 581–594.
  • CollegeBoard (2015). AP Computer science: Principles. Course planning and pacing guide. https://apcentral.collegeboard.org/media/pdf/ap-comp-sci-principles-cppg-kick.pdf.
  • CollegeBoard (2016). AP Computer science: Principles. Course and exam description. https://secure-media.collegeboard.org/digitalServices/pdf/ap/ap-computer-science-principles-course-and-exam-description.pdf.
  • Computer Science Teacher Association. (2017). CSTA K-12 computer science standards, revised 2017. http://www.csteachers.org/standards.
  • Computing at School. (2012). Computer science: A curriculum for schools. http:// www.computingatschool.org.uk/data/uploads/ComputingCurric.pdf.
  • Computing at School. (2014). Computational thinking. CAS Barefoot. https://www.computingatschool.org.uk/media/kscbloob/computationalthinking.pdf.
  • Csizmadia, A., Curzon, P., Dorling, M., Humphreys, S., Ng, T., Selby, C., … Woollard, J. (2015). Computational thinking. A guide for teachers. Computing at School. Charlote BCS. The Chartered Institute for IT.
  • Csizmadia, A., Standl, B., & Waite, J. (2019). Integrating the constructionist learning theory with computational thinking classroom activities. Informatics in Education, 18(1), 41-67.
  • Curzon, P., Dorling, M., Ng, T., Selby, C., & Woollard, J. (2014). Developing computational thinking in the classroom: A framework. Swindon, GB. Computing at School.
  • Denning, P. J. (2017). Remaining trouble spots with computational thinking. Communications of the ACM, 60(6), 33–39.Department for Education (2013). Computing programmes of study: Key stages 1 and 2. National curriculum in England. https://www.gov.uk/government/publications/national-curriculum-in-england-computing-programmes-of-study.
  • Dorling, M., & Walker, M. (2014). Computing progression pathways with Computational thinking. Computing at School. http://community.computingatschool.org.uk/resources/2324.
  • Finnish National Board of Education (2016). Curriculum in Finland. https://www.dge.mec.pt/sites/default/files/Noticias_Imagens/1_curriculum_in_finland.pdf. Fulop, M. T., Udvaros, J., Guban, A., & Sandor, A. (2022). Development of computational thinking using microcontrollers integrated into OOP (Object-Oriented Programming). Sustainability, 14(12), 7218.
  • Futschek, G. (2006). Algorithmic thinking: The key for understanding computer science. International Conference on Informatics in Secondary Schools-Evolution and Perspectives, (pp. 159–168). Springer.
  • Grover, S., & Pea, R. (2018). Computational Thinking: A competency whose time has come. In S. I, E. Barendsen, & C. Shulte (Eds.), Computer science education: Perspectives on teaching and learning in school (pp. 19-37). Bloomsbury Academic.
  • Herrero-Alvarez, R., Miranda, G., Leon, C., & Segredo, E. (2022). Engaging Primary and Secondary School Students in Computer Science through Computational Thinking Training. IEEE Transactions on Emerging Topics in Computing, 11(1), 56-69.
  • Hunsaker, E. (2018). Understanding computational thinking. Brigham Young University, Provo.
  • International Society for Technology in Education. (2016). ISTE standards for students. ISTE. https://iste.org/standards/students
  • International Society for Technology in Education. (2017). ISTE standards for educators. https://iste.org/standards/educators.
  • Israel, M., Pearson, J. N., Tapia, T., Wherfel, Q. M., & Reese, G. (2015). Supporting all learners in school-wide computational thinking: A cross-case qualitative analysis. Computers & Education, 82(2015), 263–279.
  • Kılıç, S. (2023). Background of the Relationship between Programming and Computational Thinking. In Innovative Digital Practices and Globalization in Higher Education (pp. 203–224). IGI.
  • Kim, C., Belland, B. R., Baabdullah, A., Lee, E., Dinç, E., & Zhang, A. Y. (2021). An ethnomethodological study of abductive reasoning while tinkering. AERA Open, 7.
  • Kim, J., Leftwich, A., & Castner, D. (2024). Beyond teaching computational thinking: Exploring kindergarten teachers’ computational thinking and computer science curriculum design considerations. Education and Information Technologies, 1-37.
  • Kite, V., & Park, S. (2023). What’s computational thinking?: Secondary science teachers’ conceptualizations of computational thinking (CT) and perceived barriers to CT integration. Journal of Science Teacher Education, 34(4), 391-414.
  • Kite, V., & Park, S. (2024). Context matters: Secondary science teachers' integration of process‐based, unplugged computational thinking into science curriculum. Journal of Research in Science Teaching, 61(1), 203-227.
  • Krippendorff, K. (2004). Reliability in content analysis: Some common misconceptions and recommendations. Human Communication Research, 30, 411–433.
  • Kroustalli, C., & Xinogalos, S. (2021). Studying the effects of teaching programming to lower secondary school students with a serious game: A case study with Python and CodeCombat. Education and Information Technologies, 26(5), 6069-6095. Laura-Ochoa, L., & Bedregal-Alpaca, N. (2022). Incorporation of computational thinking practices to enhance learning in a programming course. International Journal of Advanced Computer Science and Applications, 13(2).
  • Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Sage.
  • Liu, Z., Zhi, R., Hicks, A. & Barnes, T., (2017). Understanding problem solving behavior of 6-8 graders in a debugging game. Computer Science Education, 27(1), 1–29.
  • Lockwood, J., & Mooney, A. (2018). Computational thinking in education: Where does it fit? A systematic literary review. International Journal of Computer Sciences and Engineering Systems, 2(1), 41–60.
  • Lodi, M., & Martini, S. (2021). Computational thinking, between Papert and Wing. Science & Education, 30(4), 883–908.
  • Mannila, L., Leinonen, T., Bauters, M., & Veermans, M. (2023). Student and teacher co-agency when combining CT with arts and design in a cross-curricular project. Computers and Education Open, 4, 100132.
  • Merriam, S. B. (2009). Qualitative research: A guide to design and implementation (3rd ed.). CA: Jossey-Bass.
  • Miles, M., & Huberman, A. (1994). Qualitative data analysis: An expanded sourcebook (2nd ed.). Sage.
  • Milli Eğitim Bakanlığı (2018). Bilişim teknolojileri ve yazılım dersi öğretim programı (Ortaokul 5. ve 6. sınıflar). https://mufredat.meb.gov.tr/ProgramDetay.aspx?PID=374.
  • Mouza, C., Pan, Y. C., Yang, H., & Pollock, L. (2020). A multiyear investigation of student computational thinking concepts, practices, and perspectives in an after-school computing program. Journal of Educational Computing Research, 58(5), 1029-1056.
  • New Zealand Ministry of Education (2017). The ministry of education annual report 2017. https://www.education.govt.nz/assets/Documents/Ministry/Publications/Annual-Reports/2017-MOE-Annual-Report-web.pdf.
  • Özmen, B. (2020). Programlama öğretiminde bilgisayımsal düşünme becerilerinin geliştirilmesine yönelik oyun tabanlı bir tasarım modeli önerisi [Yayımlanmamış Doktora Tezi]. Hacettepe Üniversitesi. https://openaccess.hacettepe.edu.tr/xmlui/handle/11655/23259
  • Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas. Basic Books.
  • Patton, M. Q. (2014). Qualitative research and evaluation methods: Integrating theory and practice (4th ed.). Sage.
  • Pelanek, R., & Effenberger, T. (2023). The landscape of computational thinking problems for practice and assessment. ACM Transactions on Computing Education, 23(2), 1–29.
  • Peracaula-Bosch, M., Estebanell-Minguell, M., Couso, D., & González-Martínez, J. (2020). What do pre-service teachers know about computational thinking? Aloma: Revista de Psicologia, Ciències de l’Educació I de l’Esport, 38(1), 75–86.
  • Rich, K. M., Spaepen, E., Strickland, C., & Moran, C. (2019). Synergies and differences in mathematical and computational thinking: Implications for integrated instruction. Interactive Learning Environments, 28(3), 272–283.
  • Searle, K. A., Tofel-Grehl, C., Fischback, L., & Hansen, T. (2023). Affordances and limitations of teachers instructional styles when teaching computer science and computational thinking. Computer Science Education, 33(1), 139-161.
  • Selby, C. C., & Woollard, J. (2013). Computational thinking: The developing definition. University of Southampton.
  • Strauss, A., & Corbin, J. (1998). Basics of qualitative research techniques. Sage. Sun, D., Looi, C. K., Li, Y., Zhu, C., Zhu, C., & Cheng, M. (2024). Block-based versus text-based programming: A comparison of learners’ programming behaviors, computational thinking skills and attitudes toward programming. Educational Technology Research and Development, 72(2).
  • Sun, L., & Liu, J. (2024). Effects of gamified python programming on primary school students’ computational thinking skills: A differential analysis of gender. Journal of Educational Computing Research, 62(3), 846-874.
  • Tang, X., Yin, Y., Lin, Q., Hadad, R., & Zhai, X. (2020). Assessing computational thinking: A systematic review of empirical studies. Computers & Education, 148, 103798.
  • Tsortanidou, X., Daradoumis, T., & Barberá, E. (2023). A K-6 computational thinking curricular framework: Pedagogical implications for teaching practice. Interactive Learning Environments, 31(8), 4903–4923.
  • Tuhkala, A., Wagner, M. L., Iversen, O. S., & Kärkkäinen, T. (2019). Technology comprehension-combining computing, design, and societal reflection as a national subject. International Journal of Child-Computer Interaction, 20, 54–63.
  • Voogt, J., Fisser, P., Good, J., Mishra, P., & Yadav, A. (2015). Computational thinking in compulsory education: Towards an agenda for research and practice. Education and Information Technologies, 20(4), 715–728.
  • Waite, J. L., Curzon, P., Marsh, W., Sentance, S., & Hadwen-Bennett, A. (2018). Abstraction in action: K-5 teachers' uses of levels of abstraction, particularly the design level, in teaching programming. International Journal of Computer Science Education in Schools, 2(1), 14-40.
  • Wahyuni, D. S., Rozimela, Y., Ardi, H., Mukhaiyar, M., & Darmansyah, D. (2022). PROSPER (Project, Sustainability, and Perseverance) learning model in English for computer science. Sustainability, 14(24), 16749.
  • Webb, M., Davis, N., Bell, T., Katz, Y. J., Reynolds, N., Chambers, D. P., … Sysło, M. M. (2017). Computer science in K-12 school curricula of the 21st century: Why, what and when? Education and Information Technologies, 22, 445–468.
  • Weintrop, D., & Wilensky, U. (2019). Transitioning from introductory block-based and text-based environments to professional programming languages in high school computer science classrooms. Computers & Education, 142, 103646.
  • Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35.
  • Wing, J. (2008). Computational thinking and thinking about computing. Philosophical Transactions of the Royal Society A: Mathematical Physical and Engineering Sciences, 366(1881), 3717–3725.
  • Wing, J. M. (2011). Computational thinking - What and why? The Link Magazine, Spring.
  • Wing, J. M. (2017). Computational thinking’s influence on research and education for all. Italian Journal of Educational Technology, 25(2), 7–14.
  • Woollard, J. (2016). CT Driving Computing Curriculum in England. CSTA Voice, 12(1), 4–5.
  • Wu, T. T., Lin, C. J., Wang, S. C., & Huang, Y. M. (2023). Tracking visual programming language-based learning progress for computational thinking education. Sustainability, 15(3), 1983.
  • Yadav, A., Mayfield, C., Zhou, N., Hambrusch, S., & Korb, J. T. (2014). Computational thinking in elementary and secondary teacher education. ACM Transactions on Computing Education, 14(1), 1–16.
  • Yin, R. K. (2014). Case study research: Design and methods (5th ed.). Sage.
Toplam 73 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Öğrenme Psikolojisi
Bölüm Makaleler
Yazarlar

Büşra Özmen Yağız 0000-0003-3761-6215

Yasemin Koçak Usluel 0000-0002-6147-3333

Yayımlanma Tarihi 31 Temmuz 2024
Gönderilme Tarihi 28 Şubat 2024
Kabul Tarihi 30 Temmuz 2024
Yayımlandığı Sayı Yıl 2024

Kaynak Göster

APA Özmen Yağız, B., & Usluel, Y. K. (2024). Bilgisayımsal Düşünme Becerilerinin Oyun Programlama Aracılığıyla Geliştirilmesi: Ortaokul Öğrencileri için Bir Çerçeve. Ahi Evran Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 10(2), 467-486. https://doi.org/10.31592/aeusbed.1444312