Correlation analysis between sub-element of technological thinking disposition and computational thinking of gifted students in South Korea
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Aho, A. V. (2012). Computation and computational thinking. The Computer Journal, 55(7), 832–835. https://doi.org/10.1093/comjnl/bxs074
Araujo, A. L. S. O., Andrade, W. L., Guerrero, D. D. S., & Melo, M. R. A. (2019). How many abilities can we measure in computational thinking? A study on the bebras challenge. In Proceedings of the 50th ACM technological symposium on computer science education (pp. 545–551). https://doi.org/10.1145/3287324.3287405.
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.
BBC. (2018). KS3 computer science: Introduction to computational thinking—Revision 1. Retrieved from www.bbc.com/education/guides/zp92mp3/revision.
Bers, M. U., Flannery, L., Kazakoff, E. R., & Sullivan, A. (2014). Computational thinking and tinkering: Exploration of an early childhood robotics curriculum. Computers & Education, 72, 145–157.
Calcagni, A., Lonati, V., Malchiodi, D., Monga, M., Morpurgo, A. (2017). Promoting computational thinking skills: Would you use this bebras task? In: Dagienė, V., & Hellas, A. (eds), Informatics in Schools: Focus on Learning Programming. ISSEP 2017. Lecture Notes in Computer Science, vol. 10696. Springer, Cham. https://doi.org/10.1007/978-3-319-71483-7_9.
Chalmers, C. (2018). Robotics and computational thinking in primary school. International Journal of Child-Computer Interaction, 17, 93–100.
Chen, G., Shen, J., Barth-Cohen, L., Jiang, S., Huang, X., & Eltoukhy, M. (2017). Assessing elementary students’ computational thinking in everyday reasoning and robotics programming. Computers & Education, 109, 162–175.
Chiazzese, G., Arrigo, M., Chifari, A., Lonati, V., & Tosto, C. (2019). Educational robotics in primary school: Measuring the development of computational thinking skills with the bebras tasks. In Informatics. Multidisciplinary Digital Publishing Institute (Vol. 6, No. 4, p. 43). https://doi.org/10.3390/informatics6040043.
Computer Science Teachers Association (2011). CSTA K-12 Computer Science Standards, Revised 2011. Retrieved from http://scratch.ttu.ee/failid/CSTA_K-12_CSS.pdf.
Dagienė, V., & Sentance, S. (2016). It’s computational thinking! Bebras tasks in the curriculum. In International conference on informatics in schools: Situation, evolution, and perspectives (pp. 28–39). Springer, Cham. https://doi.org/10.1007/978-3-319-46747-4_3.
Denning, P. J. (2009). The profession of IT Beyond computational thinking. Communications of the ACM, 52(6), 28–30.
Furber, S. (2012). Shut down or restart? The way forward for computing in UK Schools. In London, England: The Royal Society. Retrieved from http://royalsociety.org/education/policy/computing-in-schools/report.
Google (2017). Computational Thinking Concepts Guide. Retrieved from http://computationalthinking.pbworks.com/w/file/fetch/108605812/ComputationalThinkingConceptsGuide.pdf.
Gouws, L., Bradshaw, K., & Wentworth, P. (2013). First-year student performance in a test for computational thinking. In Proceedings of the South African institute for computer scientists and information technologists conference. (pp. 271–277).
Halfin, H. H. (1973). Technology: a process approach. West Virginia University. https://www.proquest.com/dissertations-theses/technology-process-approach/docview/302702084/se-2?accountid=15179.
Hill, R. B., & Wicklein, R. C. (1999). A factor analysis of primary mental processes for technological problem-solving. Journal of Industrial Teacher Education, 36(2), 83–100.
International Society for Technology in Education (ISTE). (2011). Retrieved from www.iste.org/computational-thinking.
Jang, J. E. (2018). Comparing two structural correlations among variables affecting computational thinking in elementary schools with and without computer science education programs. In Department of educational technology the graduate school Ewha Womans University.
Key Stage 3. (2017). Introduction to computational thinking. Retrieved from http://www.bbc.co.uk/education/guides/zp92mp3/revision.
Kim, B. S. (2014). Programming education program based on PPS to improve computational thinking ability. In A thesis for a doctorate, Major in Computer Education Faculty of Science Education Graduate School JEJU National University.
Kim, T. H. (2015). STEAM education program based on programming to improve computational thinking ability. In A thesis for a doctorate, major in computer education faculty of science education graduate school JEJU National University.
Korkmaz, Ö., Çakir, R., & Özden, M. Y. (2017). A validity and reliability study of the computational thinking scales (CTS). Computers in Human Behavior, 72, 558–569.
Kwon, H. J.(2005). A model of technological creativity based on the perceptions of technology-related experts. In Department of Industrial Education, Graduate School of Chungnam National University, KOREA
Kwon, D. Y. (2010). Algorithmic brick based tangible robot and hybrid programming environments for enhancing computational thinking. a thesis for a doctorate, Major of Computer Education Faculty of Science Education Graduate School KOREA University.
Lee, E. K. (2009). A robot programming teaching and learning model to enhance computational thinking ability. In Major in Computer Education Graduate School of Korea National University of Education Chung-Buk, KOREA.
Lee, I., Martin, F., Denner, J., Coulter, B., Allan, W., Erickson, J., Malyn-Smith, J., & Werner, L. (2011). Computational thinking for youth in practice. Acm Inroads, 2(1), 32–37. https://doi.org/10.1145/1929887.1929902.
Leonard, J., Buss, A., Gamboa, R., Mitchell, M., Fashola, O. S., Hubert, T., & Almughyirah, S. (2016). Using robotics and game design to enhance children’s self-efficacy, STEM attitudes, and computational thinking skills. Journal of Science Education and Technology, 25, 860–876.
Lockwood, J., & Mooney, A. (2018). Developing a computational thinking test using Bebras problems.
Lonati, V., Malchiodi, D., Monga, M., & Morpurgo, A. (2017). Bebras as a teaching resource: classifying the tasks corpus using computational thinking skills. In Proceedings of the 2017 ACM conference on innovation and technology in computer science education (pp. 366–366). https://doi.org/10.1145/3059009.3072987.
Lye, S. Y., & Koh, J. H. L. (2014). Review on teaching and learning of computational thinking through programming: What is next for K-12? Computers in Human Behavior, 41, 51–61. https://doi.org/10.1016/j.chb.2014.09.012
Mioduser, D. (1998). Framework for the study of the cognitive nature and architecture of technological problem-solving. Journal of Technology Education and Design., 8(2), 167–184. https://doi.org/10.1023/A:1008824125352
MOE (2015). Software Education Guidance. Korean Ministry of Education.
Nam, S. G. (2010). Development of the technological thinking disposition measurement instrument. In Unpublished doctoral dissertations, Chungnam national university.
National Research Council. (2010). Report of a workshop on the scope and nature of computational thinking. National Academy Press, Washington, DC. http://www.nap.edu/openbook.php?record_id=12840.
Noh, J., & Lee, J. (2020). Effects of robotics programming on the computational thinking and creativity of elementary school students. Educational Technology Research and Development, 68, 463–484.
Norris, S. P. (1994). The meaning of critical thinking test performance: The effects of abilities and dispositions on scores. Critical thinking: Current research, theory and practice. Dordrecht, the Netherlands: Kluwer. 22.
Nunnally, J. C. (1978). An overview of psychological measurement. In Clinical diagnosis of mental disorders: A handbook, 97–146.
Papert, S. (1996). An exploration in the space of mathematics education. International Journal of Computers for Mathematical Learning, 1(1), 95–123.
Salomon, G. (1994). To be or not to be (mindful). Paper presented at the Annual Meeting of the American Education Research Association. April 4–8, New Orleans, LA.
Schwab, K. (2016). The fourth industrial revolution. World Economic Forum.
Selby, C. C. (2012). Promoting computational thinking with programming. In Proceedings of the 7th workshop in primary and secondary computing education. https://doi.org/10.1145/2481449.2481466.
Simon, T. R. (1985). Biology and behavior of the endangered Hawaiian dark-rumped petrel. Condor, 87, 229–245.
Song, J. M. (2011). Puzzle Education Based on Computational Thinking Using Scratch. In A thesis for a master, Major in Computer Education Faculty of Science Education Graduate School at KOREA University.
Swaid, S. I. (2015). Bringing computational thinking to STEM education. Procedia Manufacturing, 3, 3657–3662. https://doi.org/10.1016/j.promfg.2015.07.761
Tishman, S., & Andrade, A. (1995). Thinking dispositions: A review of current theories, practices, and issues. ACCTION report #1. Washington, DC. ACCTION.
Wicklein, R. C., & Rojewski, J. W. (1999). Toward a 'Unified Curriculum Framework' for Technology Education. https://scholar.lib.vt.edu/ejournals/JITE/v36n4/wicklein.html.
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 (TOCE), 14(1), 1–16.
Yang, K., Liu, X., & Chen, G. (2020). The influence of robots on students‟ computational thinking: A literature review. International Journal of Information and Education Technology, 10(8), 627–631.
Yu, J. H., & Kim, J. H. (2008). A Conceptual Study on Computational Thinking in Problem-solving Process. The Journal of Creative Informatics & Computing Education, 2(2), 15–24.