Parents' and children's learning when collaborating on inquiry-based mathematics and computational thinking tasks
Anders Kalsgaard Møller 1 * , Camilla Finsterbach Kaup 1 2
More Detail
1 Aalborg University, Denmark
2 University College of Northern Denmark
* Corresponding Author

Abstract

In this paper we study how children aged 12-15 years learn together with their parents while solving a series of playful inquiry-based tasks with an educational robot. The purpose of the study is to understand how children and their parents learn mathematics and computational thinking in non-formal out-of-school learning activities. For the study we designed tasks that included mathematic problem solving and programming. The tasks were designed based on input from three mathematics teachers who participated in individual workshops. Over a period of approximately six weeks, three families worked together on the tasks. In the process, they were told to self-record and self-assess the process. The families video-recorded the process and after each task they completed they answered a few questions. At the end of the intervention, we interviewed the families about the process. The results showed examples of how the families worked with mathematics and programming within different practices. In general, the children were more challenged when it came to understanding the problems, the abstraction process and problem solving. In this part they received guidance from the parents. Conversely, the children were not particularly challenged by programming and in applying mathematics in the solutions..

Keywords

References

  • Bers, M. U. (2012). Designing digital experiences for positive youth development: From playpen to playground. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199757022.001.0001
  • Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3, 77–101. https://doi.org/10.1191/1478088706qp063oa
  • 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, 1, 1-25. http://scratched.gse.harvard.edu/ct/files/AERA2012.pdf
  • Denning, P. J., & Freeman, P. A. (2009). The profession of IT computing's paradigm. Communications of the ACM, 52(12), 28-30. https://doi.org/10.1145/1610252.1610265
  • Ehsan, H., & Cardella, M. E. (2017). Capturing the computational thinking of families with young children. Paper presented at 2017 ASEE annual conference and exposition. Columbus, Ohio. http://doi.org/10.18260/1-2--28010
  • Eshach, H. (2007). Bridging in-school and out-of-school learning: Formal, non-formal, and informal education. Journal of Science Education and Technology, 16, 171–190. https://doi.org/10.1007/s10956-006-9027-1
  • García-Valcárcel-Muñoz-Repiso, A., & Caballero-González, Y. A. (2019). Robotics to develop computational thinking in early Childhood Education. Comunicar. Media Education Research Journal, 27(1), 63-72. http://doi.org/10.3916/C59-2019-06
  • Gaver, B., Dunne, T., & Pacenti, E. (1999). Design: cultural probes. interactions, 6(1), 21-29. https://doi.org/10.1145/291224.291235
  • González, Y. A. C., & Muñoz-Repiso, A. G. V. (2018). A robotics-based approach to foster programming skills and computational thinking: Pilot experience in the classroom of early childhood education. In Proceedings of the sixth international conference on technological ecosystems for enhancing multiculturality (pp. 41-45). https://doi.org/10.1145/3284179.3284188
  • Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field. Educational researcher, 42(1), 38-43. https://doi.org/10.3102/0013189X12463051
  • Hmelo-Silver, C. E., Duncan, R. G., & Chinn, C. A. (2007). Scaffolding and achievement in problem-based and inquiry learning: a response to Kirschner, Sweller, and Clark (2006). Educational Psychologist, 42(2), 99-107. https://doi.org/10.1080/00461520701263368
  • Humble, N., & Mozelius, P. (2022). Content analysis or thematic analysis: Similarities, differences and applications in qualitative research. In M. A. Y. Oliveira & C. Costa (Eds.), Proceedings of the European Conference on Research Methodology for Business and Management Studies (vol. 21, pp. 76-81). Academic Conferences International Limited.
  • Kallia, M., Borkulo, S., Drijvers, P., Barendsen, E. & Tolboom, J. (2021) Characterising computational thinking in mathematics education: A literature-informed Delphi study. Research in Mathematics Education, 23(2), 159-187. https://doi.org/10.1080/14794802.2020.1852104
  • Lajoie, S. P. (2005). Extending the scaffolding metaphor. Instructional Science, 33(5), 541-557. https://doi.org/10.1007/s11251-005-1279-2
  • Lauricella, A. R., Barr, R., & Calvert, S. L. (2014). Parent–child interactions during traditional and computer storybook reading for children’s comprehension: Implications for electronic storybook design. International Journal of Child-Computer Interaction, 2(1), 17-25. https://doi.org/10.1016/j.ijcci.2014.07.001
  • Lockwood, E., DeJarnette, A. F., Asay, A., & Thomas, M. (2016). Algorithmic thinking: An initial characterization of computational thinking in mathematics. In M. B. Wood, E. E. Turner, M. Civil & J. A. Eli, (Eds.), North American Chapter of the International Group for the Psychology of Mathematics Education (pp.1588-1595). The University of Arizona.
  • 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
  • Papert, S. (1980). Mindstorms: children. Computers and powerful ideas, New York Basic Books Inc.
  • Pei, C., Weintrop, D. & Wilensky, U. (2018). Cultivating computational thinking practices and mathematical habits of mind in lattice land. Mathematical Thinking and Learning, 20, 75-89. https://doi.org/10.1080/10986065.2018.1403543
  • Ravitch, S. M., & Carl, N. M. (2021). Qualitative research: Bridging the conceptual, theoretical, and methodological. Sage Publications.
  • Saye, J. W., & Brush, T. (2002). Scaffolding critical reasoning about history and social issues in multimedia-supported learning environments. Educational Technology Research and Development, 50(3), 77-96. https://doi.org/10.1007/BF02505026
  • Schwartz, D. L. (1995). The emergence of abstract representations in dyad problem solving. The Journal of the Learning Sciences, 4(3), 321-354. https://doi.org/10.1207/s15327809jls0403_3
  • Sheehan, K. J., Pila, S., Lauricella, A. R., & Wartella, E. A. (2019). Parent-child interaction and children's learning from a coding application. Computers & Education, 140, 103601. https://doi.org/10.1016/j.compedu.2019.103601
  • Schoenfeld, A. H. (1992). Learning to think mathematically: Problem solving, metacognition, and sense making in mathematics. In NCTM Handbook of research on mathematics teaching and learning (pp. 334-370). NCTM. https://doi.org/10.1177/002205741619600202
  • Stevens, R., & Bransford, J. (2007). The LIFE Center's lifelong and lifewide diagram. In J. A. Banks (Ed.), Learning in and out of school in diverse environments: Life-long, life-wide, life-deep. University of Washington Center for Multicultural Education.
  • Strouse, G. A., Troseth, G. L., O'Doherty, K. D., & Saylor, M. M. (2018). Co-viewing supports toddlers’ word learning from contingent and noncontingent video. Journal of Experimental Child Psychology, 166, 310-326. https://doi.org/10.1016/j.jecp.2017.09.005.
  • Sung, W. & Black, J. (2021). Factors to consider when designing effective learning: Infusing computational thinking in mathematics to support thinking-doing. Journal of Research on Technology in Education, 53(4), 404-426. https://doi.org/10.1080/15391523.2020.1784066
  • Vygotsky, L. S., & Cole, M. (1978). Mind in society: Development of higher psychological processes. Harvard University Press. https://doi.org/10.2307/j.ctvjf9vz4
  • 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. https://doi.org/10.1007/s10956-015-9581-5
  • Wenger, E. (2010). Communities of practice and social learning systems: the career of a concept. In: C. Blackmore (Eds.), Social Learning Systems and Communities of Practice (pp. 179-198). Springer. https://doi.org/10.1007/978-1-84996-133-2_11
  • Wing, J. (2011). Research notebook: Computational thinking—What and why. The link magazine, 6, 20-23.
  • Wood, D., Bruner, J. S., & Ross, G. (1976). The role of tutoring in problem solving. Journal of Child Psychology and Psychiatry, 17(2), 89-100. https://doi.org/10.1111/j.1469-7610.1976.tb00381.x
  • Wyeth, P., & Diercke, C. (2006). Designing cultural probes for children. In Proceedings of the 18th Australia conference on Computer-Human Interaction: Design: Activities, Artefacts and Environments (pp. 385-388). https://doi.org/10.1145/1228175.1228252
  • Zhang, L., & Nouri, J. (2019). A systematic review of learning computational thinking through Scratch in K- 9. Computers & Education, 141, 103607. https://doi.org/10.1016/j.compedu.2019.103607

License

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.