Integrating computational thinking to enhance students’ mathematical understanding
Camilla Finsterbach Kaup 1 2 * , Pernille Ladegaard Pedersen 3, Torben Tvedebrink 2
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1 University College of Northern Denmark, Denmark
2 Aalborg University, Denmark
3 VIA University College, Denmark
* Corresponding Author

Abstract

This study aimed to examine whether a computational thinking (CT) intervention related to a) number knowledge and arithmetic b) algebra, and c) geometry impacts students’ learning performance in primary schools. To this end, a quasi-experimental, nonequivalent group design was employed, with 61 students assigned to the experimental group and 47 students to the control group (n = 108). The experimental group comprised students in primary school who were to be followed across the second and third grades. The experimental group underwent work with digital CT activities, while the control group did not receive such interventions. A one-way analysis of variance (ANOVA) was performed on the data gathered to assess the ability differences between students from the experimental and control groups. The pre-and post-test results revealed that the experimental group’s performance was significantly better than the control group’s performance for the content areas involving CT activities.

Keywords

References

  • Bagley, S., & Rabin, J. M. (2015). Students’ Use of Computational Thinking in Linear Algebra. International Journal of Research in Undergraduate Mathematics Education, 2(1), 83–104. https://doi.org/10.1007/s40753-015-0022-x
  • 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? Inroads, 2, 48–54. https://doi.org/10.1145/1929887.1929905
  • Barcelos, T. S., Muñoz-Soto, R., Villarroel, R., Merino, E., & Silveira, I. F. (2018). Mathematics learning through computational thinking activities: a systematic literature review. Journal of Universal Computer Science, 24(7), 815-845.
  • Bocconi, S., Chioccariello, A., Dettori, G., Ferrari, A., & Engelhardt, K. (2016). Developing computational thinking in compulsory education – Implications for policy and practice. EUR 28295 EN. Rapport. Luxembourg: Publications Office of the European Union. https://doi.org/10.2791/792158
  • Brown, N. C. C., Sentance, S., Crick, T., & Humphreys, S. (2014). Restart. ACM Transactions on Computing Education, 14(2), 1–22. https://doi.org/10.1145/2602484
  • Chan, S. W., Looi, C. K., Ho, W. K., Huang, W., Seow, P., & Wu, L. (2021). Learning number patterns through computational thinking activities: A Rasch model analysis. Heliyon, 7(9), e07922. https://doi.org/10.1016/j.heliyon.2021.e07922
  • Chongo, S., Osman, K., & Nayan, N. A. (2020). Level of computational thinking skills among secondary science student: variation across gender and mathematics achievement. Science Education International, 31(2), 159-163. http://dx.doi.org/10.33828/sei.v31.i2.4
  • Città, G., Gentile, M., Allegra, M., Arrigo, M., Conti, D., Ottaviano, S., Reale, F., & Sciortino, M. (2019). The effects of mental rotation on computational thinking. Computers &Amp; Education, 141, 103613. https://doi.org/10.1016/j.compedu.2019.103613
  • Clements, D. H. (2002). Computers in early childhood mathematics. Contemporary Issues in Early Childhood, 3(2), 160–181. https://doi.org/10.2304/ciec.2002.3.2.2
  • Clements, D. H., Wilson, D. C., & Sarama, J. (2004). Young children's composition of geometric figures: A learning trajectory. Mathematical Thinking and Learning, 6(2), 163-184. https://doi.org/10.1207/s15327833mtl0602_5
  • Creswell, J. W. & Creswell J. D. (2018). Research design (5th edition). SAGE Publications.
  • Echeverría, L., Cobos, R., Morales, M., Moreno, F. & Negrete, V. (2019). Promoting computational thinking skills in primary school students to improve learning of geometry. In Proceedings of 2019 IEEE Global Engineering Education Conference (EDUCON) (pp. 424–429). IEEE. https://doi.org/10.1109/EDUCON.2019.8725088
  • Grover, S., & Pea, R. (2018). Computational Thinking: A competency whose time has come. In S. Sentence, E. Barendsen, & C. Schulte (Eds.), Computer Science Education: Perspectives on Teaching and Learning (pp. 20–38). Bloomsbury.
  • Gyldendal Om matematikprofilen (n.d.). Velkommen til Matematikprofilen [Welcome to the Mathematics profile]. https://matematikprofilen.gyldendal.dk/
  • Hickmott, D., Prieto-Rodriguez, E. & Holmes, K. A (2018). Scoping review of studies on computational thinking in k–12 mathematics classrooms. Digital Experiences in Mathematics Education, 4, 48–69. https://doi.org/10.1007/s40751-017-0038-8
  • Israel, M., & Lash, T. (2019). From classroom lessons to exploratory learning progressions: Mathematics + computational thinking. Interactive Learning Environments, 28, 1–21. https://doi.org/10.1080/10494820.2019.1674879
  • Kaas, T. (2022). Tidlig algebra i grundskolens matematikundervisning [Early algebra in primary school mathematics education]. [Unpublished doctoral dissertation]. Aarhus University, Denmark.
  • Kaput, J. (2008). What is algebra? What is algebraic reasoning? In J. Kaput, D. Carraher, & M. Blanton (Eds.), Algebra in the early grades (pp. 5–17). Lawrence Erlbaum Associates.
  • Kieran, C., Pang, J., Schifter, D., & Ng, S. F. (2016). Early Algebra: Research into its Nature, its Learning, its Teaching (ICME-13 Topical Surveys) (1st ed. 2016 ed.). Springer. https://doi.org/10.1007/978-3-319-32258-2
  • Kotsopoulos, D., Floyd, L., Khan, S., Namukasa, I. K., Somanath, S., Weber, J., & Yiu, C. (2017). A Pedagogical Framework for Computational Thinking. Digital Experiences in Mathematics Education, 3(2), 154–171. https://doi.org/10.1007/s40751-017-0031-2
  • Kreiner, S. (in press). Krav til og afprøvning af pædagogiske test [Requirements for and testing of educational tests].
  • Lakoff, G., & Núñez, R. E. (2000). Where mathematics comes from: How the embodied mind brings mathematics into being. Basic Books. https://doi.org/10.2307/3072449
  • Lee, I., Grover, S., Martin, F., Pillai, S., & Malyn-Smith, J. (2020). Computational thinking from a disciplinary perspective: Integrating computational thinking in K-12 science, technology, engineering, and mathematics education. Journal of Science Education and Technology, 29, 1-8. https://doi.org/10.1007/s10956-019-09803-w
  • Lee, J., Joswick, C., & Pole, K. (2023). Classroom play and activities to support computational thinking development in early childhood. Early Childhood Education Journal, 51(3), 457-468. https://doi.org/10.1007/s10643-022-01319-0
  • Niemelä, P. (2018). From legos and logos to lambda a hypothetical learning trajectory for computational thinking. Tampere University of Technology.
  • Niemelä, P., Partanen, T., Harsu, M., Leppänen, L., & Ihantola, P. (2017). Computational thinking as an emergent learning trajectory of mathematics. In Proceedings of the 17th Koli Calling International Conference on Computing Education Research (pp. 70-79). https://doi.org/10.1145/3141880.3141885
  • Papert, S. (1980). Mindstorms. Children, computers and powerful ideas. BasicBooks.
  • Papert, S. (1996). An exploration in the space of mathematics educations. International Journal of Computers for Mathematical Learning, 1(1), 95-123.
  • 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
  • Pérez, A. (2018). A framework for computational thinking dispositions in mathematics education. Journal for Research in Mathematics Education, 49(4), 424–461. https://doi.org/10.5951/jresematheduc.49.4.0424
  • Radford, L. (2018). The emergence of symbolic algebraic thinking in primary school. I. C. Kieran (Ed.), Teaching and learning algebraic thinking with 5-to 12-year-olds (s. 3-25). Springer. https://doi.org/10.1007/978-3-319-68351-5_1
  • Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Mifflin and Company.
  • Sung, W., Ahn, J., & Black, J. (2017). Introducing computational thinking to young learners: practicing computational perspectives through embodiment in mathematics education. Technology, Knowledge and Learning, 22, 443-463. https://doi.org/10.1007/s10758-017-9328-x
  • 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
  • Suter, L. G., Fraenkel, L., & Holmboe, E. S. (2006). What factors account for referral delays for patients with suspected rheumatoid arthritis?. Arthritis Care & Research: Official Journal of the American College of Rheumatology, 55(2), 300-305. https://doi.org/10.1002/art.21855
  • Van de Walle, J.A. (1998). Elementary and middle school mathematics: Teaching developmentally (3rd ed.).Long-man.
  • 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, 127–147. https://doi.org/10.1007/s10956-015-9581-5
  • Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35. https://doi.org/10.1145/1118178.1118215
  • Xu, W., Geng, F., & Wang, L. (2022). Relations of computational thinking to reasoning ability and creative thinking in young children: Mediating role of arithmetic fluency. Thinking Skills and Creativity, 44, 101041. https://doi.org/10.1016/j.tsc.2022.101041

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