Fen Eğitiminde Hesaplamalı Düşünme Çalışmalarının Meta-Analizi: Betimsel İstatistikler*

Bu araştırmanın amacı, fen eğitimi alanında hesaplamalı düşünme üzerine yapılmış çalışmaları bütüncül bir yaklaşımla betimsel olarak incelemektir. Doküman incelemesi yoluyla ulusal ve uluslararası veri tabanları incelenerek dahil edilme ve hariç tutulma kriterlerine uygun olduğu belirlenen birincil araştırmalar, anahtar kelimeler, yayın türü, yıl, yayın dili, araştırma yöntemleri, örneklem özellikleri, konu alanı ve uygulamalar ve veri toplama araçlarının özelliklerine göre değerlendirilmiştir. 32 birincil araştırmadan elde edilen bulgular dokuz alt başlıkta incelenmiştir. Bulgular içinde önemli bir yeri olan anahtar kelimeler verinin doğasına uygun olarak kelime bulutuyla görselleştirilmiştir. Araştırmada hesaplamalı düşünmeyi geliştirmeye yönelik araştırmaların daha çok bilgisayar ve öğretim teknolojileri ve matematik eğitimi alanlarında gerçekleştirildiği tespit edilmiştir. Araştırma sonucunda fen eğitimi alanında yıl, yayın dili, araştırma yöntemleri, örneklem özellikleri, konu alanı ve uygulamalar gibi değişkenlerin odağında gerçekleştirilecek araştırmaların alan yazına katkı sağlayacağı önerilmektedir.

Meta-Analysis of Computational Thinking Studies in Science Education: Descriptive Statistics*

This study aims is to examine the studies on computational thinking in the field of science education descriptive analysis with a holistic approach. Primary studies were determined according to compliance with inclusion and exclusion criteria through document review and national and international database review. The studies included in the scope of the research were evaluated according to the keywords they used, type of publication, year, the language of publication, research methods, sample characteristics, the subject area, and applications covered, and the characteristics of data collection tools used. Findings from 32 primary studies were analyzed under 9 sub-titles. Keywords, which have an important place in the findings, were visualized with word cloud in accordance with the nature of the data. Findings from 32 primary studies were analyzed under 9 sub-titles. Keywords, which have an important place in the findings, were visualized with word cloud in accordance with the nature of the data. According to the determination in the related literature review, researches to develop computational thinking focus on Computer Education and Instructional Technologies, and mathematics. The findings of this research reveal that it is a necessity to use science fields, which are very suitable for developing computational thinking, and to make the necessary changes in the curriculum.

PDF

___

AAAS (1990). American Association for the Advancement of Science. Science for All Americans: Education for a changing future. http://www.project2061.org/publications/sfaa/online/sfaatoc.htm adresinden erişilmiştir.
Aksit, O. (2018). Enhancing Science Learning through Computational Thinking and Modeling in Middle School Classrooms: A Mixed Methods Study. North Carolina State University.
APA. (2020). Publication Manual of The American Psychological Association 7th. Washington DC.
Arthur, J., Bennett, W., & Huffcutt, A. I. (2001). Conducting meta-analysis using SAS. Psychology Press.
Balemen, N. (2016). Proje tabanlı öğrenme yaklaşımının fen eğitimindeki etkililiği: meta analiz çalışması [The effectiveness of the project-based learning approach in science education: meta-analysis study]. (Unpublished Doctoral Dissertation) Gazi University, Ankara.
Basu, S. (2016). Fostering synergistic learning of computational thinking and middle school science in computer-based intelligent learning environments. (Unpublished Dissertation) Vanderbilt University.
Block, J. (1964). The Q-sort method in personality assessment and psychiatric research. The Journal of Nervous and Mental Disease, 136(6), 604-605.
Bocconi, S., Chioccariello, A., Dettori, G., Ferrari, A., & Engelhardt, K. (2016). Developing computational thinking in compulsory education-Implications for policy and practice (No. JRC104188). Joint Research Centre (Seville site).
Çakir, E., & Yaman, S. (2018). Ters Yüz Sınıf Modelinin Öğrencilerin Fen Başarısı ve Bilgisayarca Düşünme Becerileri Üzerine Etkisi [The Effect of Flipped Classroom Model on Students' Science Achievement and Computer Thinking Skills]. Gazi University Journal of Gazi Educational Faculty (GUJGEF), 38(1), 75–99.
Canbazoğlu Bilici, S., Küpeli, M. A., & Guzey, S. S. (2021). Inspired by nature: an engineering design-based biomimicry activity. Science Activities, 58(2), 77-88.
Christensen, D. M. (2020). Learning Biological Evolution Through Computational Thinking (Doctoral dissertation) Temple University.
Clark, D. (2015). Computational and algorithmic thinking, 2011–2015. Canberra, Australia: Australian Mathematics Trust.
Creswell, J. W., & J. D. Creswell. (2018). Research Design Qualitative, Quantitative, and Mixed Methods Approaches. Los Angles/London/ New Delhi/Singapore/Washington DC/ Melbourne: SAGE.
Çukurbaşi, B., & Kiyici, M. (2018). Öğretmen adaylarının elektronik portfolyoya yönelik görüşlerinin incelenmesi: Weebly örneği [Examination of pre-service teachers' views on electronic portfolio: The example of Weebly]. İnönü Üniversitesi Eğitim Fakültesi Dergisi, 19(1), 1-14.
Dagyar, M., & Demirel, M. (2015). Effects of problem-based learning on academic achievement: A meta-analysis study. Egitim ve Bilim, 40(181), 139–174.
Denning, P. J. (2017). Computational thinking in science. American Scientist, 105(1), 13-17.
Ellis, P. D. (2010). The Essential Guide to Effect Sizes. Cambridge University Press.
Evelina, B. C., & Nadia, B. C. (2014). The Q-sort technique used in identifying the level of methodological skills of the prospective teachers. Procedia-Social and Behavioral Sciences, 128, 60-65.
Glass, G. V. (1976). Primary, secondary, and meta-analysis of research. Educational researcher, 5(10), 3-8.
Gülbahar, Y., Çakıroğlu, Ü., Kalelioğlu, F., Delen, İ., Yıldız, B., & Sayın, Z. (2020). Bilgi İşlemsel Düşünme Becerisinin Disiplinlerarası Yaklaşım ile Öğretimi [Teaching Computational Thinking Skills with an Interdisciplinary Approach]. S. Akbıyık ve V. H. Kaya (Ed.). Ankara: MEB ÖYGM.
Gürsakal, N., & Oğuzlar, A. (2015). No Title. Dora Yayıncılık.
Hamutoglu, N. B. (2021). A Road Map for the COVID-19 Pandemic Process to Ensure Quality of Assurance Active Learning Strategies in Online Learning Environments: How to Plan, Implement, Evaluate, and Improve Learning Activities. In Handbook of Research on Emerging Pedagogies for the Future of Education: Trauma-Informed, Care, and Pandemic Pedagogy (ss. 101-126). IGI Global.
Riley, D. D., & Hunt, K. A. (2014). Computational thinking for the modern problem solver. CRC press.
Jaipal-Jamani, K., & Angeli, C. (2017). Effect of robotics on elementary preservice teachers’ self-efficacy, science learning, and computational thinking. Journal of Science Education and Technology, 26(2), 175-192.
Kizilay, E., Yamak, H., & Kavak, N. (2019). Motivation Scale for STEM Fields. Journal of Computer and Education Research, 7(14), 540-557.
Lei, H., Chiu, M. M., Li, F., Wang, X., & Geng, Y. J. (2020). Computational thinking and academic achievement: A meta-analysis among students. Children and Youth Services Review, 118, 105439.
Lipsey, M. W., & Wilson, D. (2001). Practical Meta Analysis Overview. Applied Social Research Methods Series.
MEB. (2018). Fen Bilimleri Dersi Öğretim Programı (İlkokul ve Ortaokul 3, 4, 5, 6, 7 ve 8. Sınıflar) [Science Curriculum (Primary and Secondary Schools 3, 4, 5, 6, 7 and 8th Grades)]. Ankara.
NRC. (2000). National Research Council. Inquiry and the National Science Education Standards: A Guide for Teaching and Learning. Washington: DC: The National Academies Press.
Ortiz, C. J. (2018). An Experimental Comparison of Student Motivation Between Two Computational Thinking-based Stem Activities: Vex-based Automation and Robotics and a Quadcopter Activity (Doctoral dissertation) Utah State University.
Özüdoğru, M. (2018). The effect of flipped learning on pre-service teachers’ achievement and perceptions related to classroom environment. (Unpublished Dissertation) Middle East Technical University.
Rosenthal, R., & DiMatteo, M. R. (2001). Meta-analysis: Recent developments in quantitative methods for literature reviews. Annual review of psychology, 52(1), 59-82.
Sánchez-Meca, J., & Marín-Martínez, F. (2010). Meta-analysis in psychological research. International Journal of Psychological Research, 3(1), 150-162.
Strawhacker, A. L. (2020). Biodesign Education in Early Childhood: A Design-Research Study of the Tangible Crispee Technology and Learning Intervention (Doctoral dissertation) Tufts University.
Ural, G. (2014). İlköğretimde Fen ve Teknoloji Öğretimi Üzerine Türkiye’de Yapılan Araştırmaların Meta Analizi [Meta-Analysis of Researches on Science and Technology Teaching in Primary Education in Turkey] (Unpublished Doctoral Dissertation) Ege University, İzmir.
Uşengül, L., & Bahçeci, F. (2020). The Effect of Lego Wedo 2.0 Education on Academic Achievement and Attitudes and Computational Thinking Skills of Learners toward Science. World Journal of Education, 10(4), 83-93.
Uşengül, L. (2019). Lego Wedo 2.0 eğitiminin öğrenenlerin fen bilimlerine yönelik akademik başarı ve tutumları ile bilgi işlemsel düşünme becerilerine etkisi [The effect of Lego Wedo 2.0 education on learners' academic achievement and attitudes towards science and computational thinking skills] (Unpublished Masters' Thesis). Fırat University, Elazığ.
Üstün, U. (2012). To what extent is problem-based learning effective as compared to traditional teaching in science education? A meta-analysis study. (Unpublished Dissertation) Middle East Technical University.
Weese, J. L. (2017). Bringing computational thinking to K-12 and higher education. (Unpublished Dissertation) Kansas State University.
Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35.
Yilmaz, Ö., & Tuncer, M. (2020). Deneysel bir araştirmada pilot çalişmanin önemi: dale’in yaşanti konisine göre öğretimin akademik başariya etkisi [The importance of a pilot study in an experimental research: the effect of teaching on academic achievement according to dale's life cone]. Electronic Journal of Education Sciences, 9(17), 89-96.