Aho, A. V. (2012). Computation and computational thinking. The Computer Journal, 55(7), 832-835. https://doi.org/10.1093/comjnl/bxs074
Atmatzidou, S., & Demetriadis, S. (2016). Advancing students’ computational thinking skills through educational robotics: A study on age and gender relevant differences. Robotics and Autonomous Systems, 75, 661-670.
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the academy of marketing science, 16(1), 74-94.
Barr, D., Harrison, J., & Conery, L. (2011). Computational thinking: A digital age skill for everyone. Learning & Leading with Technology, 38(6), 20-23.
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.
Basogain, X., Olabe, M., Olabe, J., Maiz, I., & Castaño, C. (2012). Mathematics Education through Programming Languages. 21st Annual World Congress on Learning Disabilities,
Bell, J., & Bell, T. (2018). Integrating computational thinking with a music education context. Informatics in Education, 17(2), 151-166.
Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological bulletin, 88(3), 588.
Boulden, D. C., Rachmatullah, A., Oliver, K. M., & Wiebe, E. (2021). Measuring in-service teacher self-efficacy for teaching computational thinking: development and validation of the T-STEM CT. Education and Information technologies, 26(4), 4663-4689.
Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (Vol. 154, pp. 136). SAGE Publications.
Bryman, A., & Cramer, D. (2002). Quantitative data analysis with SPSS release 10 for Windows: A guide for social scientists. Routledge.
Bundy, A. (2007). Computational thinking is pervasive. Journal of Scientific and Practical Computing, 1(2), 67-69.
Cattell, R. (2012). The scientific use of factor analysis in behavioral and life sciences. Springer Science & Business Media.
Çokluk, Ö., Şekercioğlu, G., & Büyüköztürk, Ş. (2014). Sosyal bilimler için çok değişkenli istatistik: SPSS ve LISREL uygulamaları. Pegem Akademi.
Durak, H. Y., & Saritepeci, M. (2018). Analysis of the relation between computational thinking skills and various variables with the structural equation model. Computers & Education, 116, 191-202.
Gadanidis, G. (2017). Artificial intelligence, computational thinking, and mathematics education. The International Journal of Information and Learning Technology.
Gefen, D., Straub, D., & Boudreau, M.-C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the association for information systems, 4(1), 7.
Gorsuch, R. L. (1983). Factor analysis. Lawrence Erlbaum.
Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field. Educational researcher, 42(1), 38-43.
Guo, J., Marsh, H. W., Parker, P. D., Morin, A. J., & Yeung, A. S. (2015). Expectancy-value in mathematics, gender and socioeconomic background as predictors of achievement and aspirations: A multi-cohort study. Learning and Individual Differences, 37, 161-168.
Hair, J. F. (2009). Multivariate data analysis.
Hsu, T.-C., Chang, S.-C., & Hung, Y.-T. (2018). How to learn and how to teach computational thinking: Suggestions based on a review of the literature. Computers & Education, 126, 296-310.
ISTE. (2016a). ISTE Standards for Educators. https://www.iste.org/standards/for-educators
ISTE. (2016b). ISTE Standards for Students. http://www.iste.org/docs/Standards-Resources/iste-standards_students-2016_one-sheet_final.pdf?sfvrsn=0.23432948779836327
Kline, R. B. (2016). Principles and practice of structural equation modeling (4 ed.). Guilford publications.
Lai, Y.-H., Chen, S.-Y., Lai, C.-F., Chang, Y.-C., & Su, Y.-S. (2021). Study on enhancing AIoT computational thinking skills by plot image-based VR. Interactive Learning Environments, 29(3), 482-495.
Lee, I., Martin, F., & Apone, K. (2014). Integrating computational thinking across the K--8 curriculum. Acm Inroads, 5(4), 64-71.
Lindberg, R. S., Laine, T. H., & Haaranen, L. (2019). Gamifying programming education in K‐12: A review of programming curricula in seven countries and programming games. British Journal of Educational Technology, 50(4), 1979-1995.
Mohaghegh, D. M., & McCauley, M. (2016). Computational thinking: The skill set of the 21st century. International Journal of Computer Science and Information Technologies, 7(3), 1524-1530.
Özgün, Z., & Saritepeci, M. (2021). Determination of the Factors Affecting Teachers’ Perceptions of Classroom Management Competence in Technology Assisted Courses. Technology, Pedagogy and Education, 30(5), 673-691. https://doi.org/10.1080/1475939X.2021.1956579
Papadakis, S. (2022). Apps to promote computational thinking concepts and coding skills in children of preschool and pre-primary school age. In Research Anthology on Computational Thinking, Programming, and Robotics in the Classroom (pp. 610-630). IGI Global.
Qualls, J. A., & Sherrell, L. B. (2010). Why computational thinking should be integrated into the curriculum. Journal of Computing Sciences in Colleges, 25(5), 66-71.
R Core Team (2020). R: A Language and environment for statistical computing. (Version 4.0) [Computer software]. Retrieved from https://cran.r-project.org. (R packages retrieved from MRAN snapshot 2020-08-24).
Rosseel, Y., et al. (2018). lavaan: Latent Variable Analysis. [R package]. Retrieved from https://cran.r-project.org/package=lavaan.
Rubinstein, A., & Chor, B. (2014). Computational thinking in life science education. PLoS computational biology, 10(11), e1003897.
Sanford, J. F., & Naidu, J. T. (2016). Computational thinking concepts for grade school. Contemporary Issues in Education Research (CIER), 9(1), 23-32.
Saritepeci, M. (2020). Developing Computational Thinking Skills of High School Students: Design-Based Learning Activities and Programming Tasks. Asia-Pacific Education Researcher, 29(1), 35-54. https://doi.org/10.1007/s40299-019-00480-2
Saritepeci, M. (2021). Modelling the Effect of TPACK and Computational Thinking on Classroom Management in Technology Enriched Courses. Technology, Knowledge and Learning, 1-15. https://doi.org/10.1007/s10758-021-09529-y
Sarıtepeci, M., & Durak, H. (2017). Analyzing the Eﬀect of Block and Robotic Coding Activities on Computational Thinking in Programming Education. In G. D. Irina Koleva (Ed.), Educational research and practice. St. Kliment Ohridski University Press.
Shute, V. J., Sun, C., & Asbell-Clarke, J. (2017). Demystifying computational thinking. Educational Research Review, 22, 142-158.
Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (6 ed.). Pearson.
The jamovi project (2021). jamovi. (Version 1.6) [Computer Software]. Retrieved from https://www.jamovi.org.
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(1), 127-147.
Wigfield, A., & Eccles, J. S. (2000). Expectancy–value theory of achievement motivation. Contemporary educational psychology, 25(1), 68-81.
Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35.
Wing, J. M. (2008). Computational thinking and thinking about computing. Philosophical transactions of the royal society of London A: mathematical, physical and engineering sciences, 366(1881), 3717-3725.
Wing, J. M. (2014). Computational thinking benefits society. 40th Anniversary Blog of Social Issues in Computing, 2014, 26.
Wolz, U., Stone, M., Pearson, K., Pulimood, S. M., & Switzer, M. (2011). Computational thinking and expository writing in the middle school. ACM Transactions on Computing Education (TOCE), 11(2), 1-22.
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), 5.
Yıldız-Durak, H., Sarıtepeci, M., & Aksu-Dünya, B. (2021). Examining the Relationship between Computational Thinking, Lifelong Learning Competencies and Personality Traits Using Path Analysis. Bartın University Journal of Faculty of Education, 10(2), 284-294.
Yildiz Durak, H. (2020). The effects of using different tools in programming teaching of secondary school students on engagement, computational thinking and reflective thinking skills for problem solving. Technology, Knowledge and Learning, 25(1), 179-195.
Yildiz Durak, H. (2021). Modeling of relations between K-12 teachers’ TPACK levels and their technology integration self-efficacy, technology literacy levels, attitudes toward technology and usage objectives of social networks. Interactive Learning Environments, 29(7), 1136-1162.
Yildiz Durak, H., Saritepeci, M., & Durak, A. (2021). Modeling of Relationship of Personal and Affective Variables With Computational Thinking and Programming. Technology, Knowledge and Learning, 1-20.
Zhao, L., Liu, X., Wang, C., & Su, Y.-S. (2022). Effect of different mind mapping approaches on primary school students’ computational thinking skills during visual programming learning. Computers & Education, 104445.