Trajectories of Developing Computational Thinking Competencies: Case Portraits of Korean Gifted Girls

Atmatzidou, S., & Demetriadis, S. (2016). Advancing students’ computational thinking skills through educational robotics: A study on age and gender relevant differences. Robotics & Autonomous Systems,75, 661–670. Baker, D., & Leary, R. (2003). Letting girls speak out about science. Journal of Research in Science Teaching,40(1), 176–200. Banerjee, M., Schenke, K., Lam, A., & Eccles, J. S. (2018). The roles of teachers, classroom experiences, and finding balance: A qualitative perspective on the experiences and expectations of females within STEM and non-STEM careers. International Journal of Gender, Science & Technology,10(2), 287–307. 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. Barron, B. (2004). Learning ecologies for technological fluency: Gender and experience differences. Journal of Educational Computing Research,31(1), 1–36. Barron, B. (2006). Interest and self-sustained learning as catalysts of development: A learning ecology perspective. Human Development,49(4), 193–224. Barron, B., Martin, C. K., & Roberts, E. (2007). Sparking self-sustained learning: Report on a design experiment to build technological fluency and bridge divides. International Journal of Technology & Design Education,17(1), 75–105. Baytak, A., & Land, S. M. (2011). An investigation of the artifacts and process of constructing computers games about environmental science in a fifth grade classroom. Educational Technology Research & Development,59(6), 765–782. Boston, J. S., & Cimpian, A. (2018). How do we encourage gifted girls to pursue and succeed in science and engineering? Gifted Child Today,41(4), 196–207. Brennan, K., & Resnick, M. (2012). New frameworks for studying and assessing the development of computational thinking. Paper presented at the 2012 annual meeting of the American Educational Research Association, Vancouver, Canada. Burke, Q., O'Byrne, W. I., & Kafai, Y. B. (2016). Computational participation: Understanding coding as an extension of literacy instruction. Journal of Adolescent & Adult Literacy,59(4), 371–375. Cai, Z., Fan, X., & Du, J. (2017). Gender and attitudes toward technology use: A meta-analysis. Computers & Education,105, 1–13. Callahan, C. M., Sowa, C. J., May, K. M., Tomchin, E. M., Plucker, J. A., Cunningham, C. M., & Taylor, W. (2004). The social and emotional development of gifted students [RM04188]. Retrieved March 31, 2019 from https://files.eric.ed.gov/fulltext/ED505462.pdf. Chenitz, W. C., & Swanson, J. M. (1986). From practice to grounded theory: Qualitative research in nursing. Bergen County, NJ: Prentice Hall. Craig, A. (2006). Young girls ICT: Into computing too, Retrieved March 3, 2019 from https://hdl.handle.net/10536/DRO/DU:30010444. Cross, S., & Markus, H. (1991). Possible selves across the life span. Human Development,34(4), 230–255. Cross, T. L., Speirs Neumeister, K. L., & Cassady, J. C. (2007). Psychological types of academically gifted adolescents. Gifted Child Quarterly,51(3), 285–294. Csikszentmihalyi, M. (2004). Good business: Leadership, flow, and the making of meaning. New York, NY: Penguin. Denning, P. J. (2005). Is computer science science? Communications of the ACM,48(4), 27–31. Duckworth, A. L., Peterson, C., Matthews, M. D., & Kelly, D. R. (2007). Grit: Perseverance and passion for long-term goals. Journal of Personality & Social Psychology,92(6), 1087–1102. Feldman, D. H. (1986). Nature's gambit: The mystery and meaning of the child prodigy. New York: Basic Books. Gagné, F. (2013). The DMGT: Changes within, beneath, and beyond. Talent Development & Excellence,5(1), 5–19. Grey, S., Parker, D., & Gordon, N. (2018). Constraints and autonomy for creativity in extracurricular gamejams and curricular assessment. Retrieved March 31, 2019 from https://journal.alt.ac.uk/index.php/rlt/article/view/2023. Grover, S., & Pea, R. (2013). Computational thinking in K-12: A review of the state of the field. Educational Researcher,42(1), 38–43. Holt, L. (2011). Creating digital stories with Scratch to promote computational thinking. Paper presented at the 2011 Society for Information Technology & Teacher Education (SITE) International Conference, Nashville, Tennessee. International Society for Technology in Education (ISTE) & Computer Science Teachers Association (CSTA). (2014). Computational Thinking Leadership Toolkit 2st edition. Retrieved March 31, 2019 from https://www.iste.org/explore/articleDetail?articleid=152&category=Solutions&article=Computational-thinking-for-all. Jacobs, J. E., Finken, L. L., Griffin, N. L., & Wright, J. D. (1998). The career plans of science-talented rural adolescent girls. American Educational Research Journal,35(4), 681–704. Joo, Y. J., & Kim, D. S. (2016). Influence of grit (perseverance of effort and consistency of interest), teacher support, and parent support on self-regulation and educational satisfaction in children in a gifted education program. Special Education Research,15(1), 29–49. Kafai, Y. B. (2016). From computational thinking to computational participation in K-12 education. Communications of the ACM,59(8), 26–27. Kalelioğlu, F. (2015). A new way of teaching programming skills to K-12 students: Code.org. Computers in Human Behavior,52, 200–210. Kim, J. A., Moo, D. J., & Lee, S. K. (2017). 2017 Gifted education statistics [SM 2017-11]. Retrieved March 31, 2019 from https://goo.gl/DgQbcp. Kong, S. C., Chiu, M. M., & Lai, M. (2018). A study of primary school students' interest, collaboration attitude, and programming empowerment in computational thinking education. Computers & Education,127, 178–189. Lee, J. M., Jung, Y. J., & Park, H. K. (2017). Gender differences in computational thinking, creativity, and academic interest on elementary SW education. Journal of the Korean Association of Information Education.,21(4), 381–391. Mills, C. J. (2003). Characteristics of effective teachers of gifted students: Teacher background and personality styles of students. Gifted Child Quarterly,47(4), 272–281. Ministry of Education. (2003). Promotion of education for the gifted and talented law. Retrieved March 31, 2019 from https://goo.gl/hFQgjm. Myers, I. B. (1962). Manual: The Myers-Briggs type indicator. Princeton, NJ: Educational Testing Service. Olszewski-Kubilius, P. (2018). The role of the family in talent development. In Handbook of giftedness in children (pp. 129–147). Boston, MA Springer. Olszewski-Kubilius, P., & Lee, S. Y. (2004). The role of participation in in-school and outside-of-school activities in the talent development of gifted students. Journal of Secondary Gifted Education,15(3), 107–123. Peers, S. (2018). Statistics on women in engineering. Retrieved March 31, 2019 from https://goo.gl/gaM5Ae. Perković, L., Settle, A., Hwang, S., & Jones, J. (2010). A framework for computational thinking across the curriculum. Paper presented at the 15th annual conference on Innovation and technology in computer science education [ITiCSE], Ankara, Turkey. Ray, R., & Brown, J. (2015). Reassessing student potential for medical school success: Distance traveled, grit, and hardiness. Military Medicine,180(4S), 138–141. Reis, S. M., & Graham, C. (2005). Needed: Teachers to encourage girls in math, science, and technology. Gifted Child Today,28(3), 14–21. Robertson, J. (2012). Making games in the classroom: Benefits and gender concerns. Computers & Education,59(2), 385–398. Román-González, M., Pérez-González, J. C., & Jiménez-Fernández, C. (2017). Which cognitive abilities underlie computational thinking? Criterion validity of the computational thinking test. Computers in Human Behavior,72, 678–691. Saldaña, J. (2015). The coding manual for qualitative researchers. Thousand Oaks, CA: Sage. Sampson, W. A. (2002). Black student achievement: How much do family and school really matter?. Lanham, MD: Scarecrow Press. Selby, C., & Woollard, J. (2013). Computational thinking: the developing definition. University of Southampton (E-prints). Retrieved March 31, 2019 from https://eprints.soton.ac.uk/id/eprint/356481. Seneviratne, O. (2017). Making computer science attractive to high school girls with computational thinking approaches: A case study. Handbook of emerging research, practice, and policy on computational thinking (pp. 21–32). Cham: Springer. Siegle, D., Rubenstein, L. D., & Mitchell, M. S. (2014). Honors students’ perceptions of their high school experiences: The influence of teachers on student motivation. Gifted Child Quarterly,58(1), 35–50. Sosniak, L. (2003). Developing talent: Time, task, and context. Handbook of gifted education (pp. 247–253). Pearson Education: New York, NY. Tirri, K., Kuusisto, E., & Aksela, M. (2013). What kind of learning is interactive and meaningful to gifted science students? Handbook of Interaction in educational domains (pp. 131–145). Rotterdam, NL: Sense Publishers. Uttal, D. H., Miller, D. I., & Newcombe, N. S. (2013). Exploring and enhancing spatial thinking: Links to achievement in science, technology, engineering, and mathematics? Current Directions in Psychological Science,22(5), 367–373. Van Langen, A., Rekers-Mombarg, L., & Dekkers, H. (2006). Sex-related differences in the determinants and process of science and mathematics choice in pre-university education. International Journal of Science Education,28(1), 71–94. Vos, N., Van Der Meijden, H., & Denessen, E. (2011). Effects of constructing versus playing an educational game on student motivation and deep learning strategy use. Computers & Education,56(1), 127–137. Wang, M. T., & Degol, J. L. (2017). Gender gap in science, technology, engineering, and mathematics (STEM): Current knowledge, implications for practice, policy, and future directions. Educational Psychology Review,29(1), 119–140. Watters, J. J., & Diezmann, C. M. (2003). The gifted student in science: Fulfilling potential. Australian Science Teachers Journal,49(3), 46–53. Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., et al. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education & Technology,25(1), 127–147. Wing, J. M. (2006). Computational thinking. Communications of the ACM,49(3), 33–36. Wing, J. M. (2008). Computational thinking and thinking about computing. Philosophical transactions of the Royal Society of London: Mathematical, Physical & Engineering Sciences,366(1881), 3717–3725. Yasar, O., & Landau, R. H. (2003). Elements of computational science and engineering education. SIAM Review,45(4), 787–805.