Children’s knowledge construction of computational thinking in a play-based classroom

References

• Barab, S., & Squire, K. (2004). Design-based research: Putting a stake in the ground. Journal of the Learning Sciences, 13(1), 1–14. doi:10.1207/s15327809jls1301_1
   Web of Science ®Google Scholar
• Beckers, J., Dolmans, D., & Van Merriënboer, J. (2016). E-portfolios enhancing students’ self-directed learning: A systematic review of influencing factors. Australasian Journal of Educational Technology, doi:10.14742/ajet.2528
   Web of Science ®Google Scholar
• Bell, T., & Vahrenhold, J. (2018). CS unplugged: How is it used, and does it work? In H.-J. Böckenhauer, D. Komm, & W. Unger (Eds.), Adventures between lower bounds and higher altitudes (pp. 497–521). Switzerland: Springer. doi:10.1007/978-3-319-98355-4_29
   Google Scholar
• Bers, M. U. (2018). Coding and computational thinking in early childhood: The impact of Scratch Jr in Europe. European Journal of STEM Education, 3(3), doi:10.20897/ejsteme/3868
   Google Scholar
• 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. doi:10.1016/j.compedu.2013.10.020
   Web of Science ®Google Scholar
• Boyer, S. L., Edmondson, D. R., Artis, A. B., & Fleming, D. (2014). Self-Directed learning. Journal of Marketing Education, 36(1), 20–32. doi:10.1177/0273475313494010
   Google Scholar
• Brennan, K., & Resnick, M. (2012). New frameworks for studying and assessing the development of computational thinking. Proceedings of the 2012 Annual Meeting of the American Educational Research Association, Vancouver, Canada (pp. 1–25).
   Google Scholar
• Clements, D. H., & Meredith, J. S. (1992). Research on logo: Effects and efficacy. Journal of Computing in Childhood Education, 4(4), 263–290.
   Google Scholar
• Curriculum Development Council. (2017). Kindergarten education curriculum guide: Joyful learning through play balanced development all the way. Hong Kong: Hong Kong SAR Education Bureau.
   Google Scholar
• Elias, J. L., & Merriam, S. B. (1995). Philosophical foundations of adult education. Melbourne: Krieger Publishing Company.
   Google Scholar
• Fleer, M. (2021). A cultural–historical critique of how engineering knowledge is constructed through research in play-based settings: What counts as evidence and what is invisible? Research in Science Education, 52(4), 1355–1373. doi:10.1007/s11165-021-10012-y
   Web of Science ®Google Scholar
• Godhe, A. L., Lilja, P., & Selwyn, N. (2019). Making sense of making: Critical issues in the integration of maker education into schools. Technology, Pedagogy and Education, 28(3), 317–328. doi:10.1080/1475939X.2019.1610040
   Web of Science ®Google Scholar
• Goldstein, J., & Flake, J. K. (2015). Towards a framework for the validation of early childhood assessment systems. Educational Assessment, Evaluation and Accountability, 28(3), 273–293. doi:10.1007/s11092-015-9231-8
   Web of Science ®Google Scholar
• Groen, J. E., & Kawalilak, C. (2014). Pathways of adult learning: Professional and education narratives. Portland: Canadian Scholars’ Press.
   Google Scholar
• Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field. Educational Researcher, 42(1), 38–43. doi:10.3102/0013189(12463051
   Web of Science ®Google Scholar
• Jonassen, D. H. (1999). Designing constructivist learning environments. In C. M. Reigeluth (Ed.), Instructional-design theories and models: A new paradigm of instructional theory (Vol. 2, pp. 215–239). Pennsylvania: Lawrence Erlbaum Associates.
   Google Scholar
• Jossberger, H., Brand-Gruwel, S., Boshuizen, H., & van de Wiel, M. (2010). The challenge of self-directed and self-regulated learning in vocational education: A theoretical analysis and synthesis of requirements. Journal of Vocational Education & Training, 62(4), 415–440. doi:10.1080/13636820.2010.523479
   Google Scholar
• Knowles, M. S. (1970). The modern practice of adult education: Andragogy versus pedagogy. New York: The Association Press.
   Google Scholar
• Knowles, M. S. (1975). Self-directed learning: A guide for learners and teachers. Chicago: Follett.
   Google Scholar
• Leach, N. (2018). Impactful learning environments: A humanistic approach to fostering adolescents’ postindustrial social skills. Journal of Humanistic Psychology, 62(3), 377–396. doi:10.1177/0022167818779948
   Google Scholar
• Li, W., & Yang, W. (2023). Promoting children’s computational thinking: A quasi-experimental study of web-mediated parent education. Journal of Computer Assisted Learning, 39(5), 1564–1575. doi:10.1111/jcal.12818
   Web of Science ®Google Scholar
• Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook. California: SAGE.
   Google Scholar
• Morris, T. H. (2019). Self-directed learning: A fundamental competence in a rapidly changing world. International Review of Education, 65(4), 633–653. doi:10.1007/s11159-019-09793-2
   Web of Science ®Google Scholar
• Müller, U., Overton, W. F., & Reene, K. (2001). Development of conditional reasoning: A longitudinal study. Journal of Cognition and Development, 2(1), 27–49. doi:10.1207/S15327647JCD0201_2
   Web of Science ®Google Scholar
• Murtonen, M., Gruber, H., & Lehtinen, E. (2017). The return of behaviourist epistemology: A review of learning outcomes studies. Educational Research Review, 22, 114–128. doi:10.1016/j.edurev.2017.08.001
   Web of Science ®Google Scholar
• Ng, O.-L., & Cui, Z. (2020). Examining primary students’ mathematical problem-solving in a programming context: Towards computationally enhanced mathematics education. ZDM – Mathematics Education, 53(4), 847–860. doi:10.1007/s11858-020-01200-7
   Google Scholar
• Nor, M. M., & Saeednia, Y. (2009). Exploring self-directed learning among children. International Journal of Human and Social Sciences, 4(9), 658–663.
   Google Scholar
• Organisation for economics and Co-operation development (OECD). (2018). Compendium of productivity indicators 2018. Paris: OECD.
   Google Scholar
• Otterborn, A., Schönborn, K. J., & Hultén, M. (2020). Investigating preschool educators’ implementation of computer programming in their teaching practice. Early Childhood Education Journal, 48(3), 253–262. doi:10.1007/s10643-019-00976-y
   Web of Science ®Google Scholar
• Papert, S. (1980). Redefining childhood: The computer presence as an experiment in developmental psychology. IFIP Congress (pp. 993–998).
   Google Scholar
• Parnafes, O., & Disessa, A. A. (2013). Microgenetic learning analysis: A methodology for studying knowledge in transition. Human Development, 56(1), 5–37. doi:10.1159/000342945
   Web of Science ®Google Scholar
• Piaget, J. (1971). Developmental stages and developmental processes. In D. R. Green, M. P. Ford, & G. B. Flamer (Eds.), Measurement and piaget (pp. 172–188). New York: McGraw-Hill.
   Google Scholar
• Pugnali, A., Sullivan, A., & Bers, M. U. (2017). The impact of user interface on young children’s computational thinking. Journal of Information Technology Education: Innovations in Practice, 16, 171–193. doi:10.28945/3768
   Web of Science ®Google Scholar
• Rogers, C. R. (1969). Freedom to learn. Columbus: C. E. Merrill Publishing Company.
   Google Scholar
• Sawatsky, A. P., Ratelle, J. T., Bonnes, S. L., Egginton, J. S., & Beckman, T. J. (2017). A model of self-directed learning in internal medicine residency: A qualitative study using grounded theory. BMC Medical Education, 17(1). doi:10.1186/s12909-017-0869-4
   Google Scholar
• Shute, V. J., Sun, C., & Asbell-Clarke, J. (2017). Demystifying computational thinking. Educational Research Review, 22, 142–158. doi:10.1016/j.edurev.2017.09.003
   Web of Science ®Google Scholar
• Sullivan, A., & Bers, M. U. (2015). Robotics in the early childhood classroom: Learning outcomes from an 8-week robotics curriculum in pre-kindergarten through second grade. International Journal of Technology and Design Education, 26(1), 3–20. doi:10.1007/s10798-015-9304-5
   Web of Science ®Google Scholar
• Sullivan, A., & Bers, M. U. (2018). Dancing robots: Integrating art, music, and robotics in Singapore’s early childhood centers. International Journal of Technology and Design Education, 28(2), 325–346. doi:10.1007/s10798-017-9397-0
   Web of Science ®Google Scholar
• Tang, X., Yin, Y., Lin, Q., Hadad, R., & Zhai, X. (2020). Assessing computational thinking: A systematic review of empirical studies. Computers & Education, 148, 103798. doi:10.1016/j.compedu.2019.103798
   Web of Science ®Google Scholar
• Tough, A. M. (1971). The adult’s learning projects: A fresh approach to theory and practice in adult education. Toronto: Ontario Institute for Studies in Education.
   Google Scholar
• Vygotsky, L. S. (1994). The problem of the environment. In J. Valsiner & R. v. Veer (Eds.), The Vygotsky reader (pp. 347–348). Cambridge: Blackwell.
   Google Scholar
• Vygotsky, L. S. (1997). The collected works of L. S. Vygotsky. The history of the development of higher mental functions. New York: Plenum.
   Google Scholar
• Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35. doi:10.1145/1118178.1118215
   Web of Science ®Google Scholar
• Yang, W., Luo, H., & Su, J. (2022). Towards inclusiveness and sustainability of robot programming in early childhood: Child engagement, learning outcomes and teacher perception. British Journal of Educational Technology, 53(6), 1486–1510. doi:10.1111/bjet.13266
   Web of Science ®Google Scholar
• Zapata-Cáceres, M., Martin-Barroso, E., & Roman-Gonzalez, M. (2020). Computational thinking test for beginners: Design and content validation. 2020 IEEE Global Engineering Education Conference (EDUCON), 1905–1914. doi:10.1109/educon45650.2020.9125368
   Google Scholar
• Zeng, Y., Yang, W., & Bautista, A. (2023a). Computational thinking in early childhood education: Reviewing the literature and redeveloping the three-dimensional framework. Educational Research Review, 39, 100520. doi:10.1016/j.edurev.2023.100520
   Web of Science ®Google Scholar
• Zeng, Y., Yang, W., & Bautista, A. (2023b). Teaching programming and computational thinking in early childhood education: A case study of content knowledge and pedagogical knowledge. Frontiers in Psychology, 14. doi:10.3389/fpsyg.2023.1252718
   Web of Science ®Google Scholar
• Zhang, L. C., & Nouri, J. (2019). A systematic review of learning computational thinking through Scratch in K–9. Computers & Education, 141, 103607. doi:10.1016/j.compedu.2019.103607
   Web of Science ®Google Scholar