Article Sidebar

Published
Sep 30, 2019
Download
PDF
Statistic
Read Counter : 4274 Download : 2489

Main Article Content

Abstract

Computational thinking is needed in the 21st century, where we live in an era of digitalization. Also, there is a global movement to incorporate computational thinking into the education curriculum, especially Mathematics education. The different of this research with others is this research compares the Polya problem solving and computational thinking. This research was conducted to find out how the relationship/relationship of the Polya problem-solving with the steps of computational thinking. The method used in this research is descriptive qualitative. The subject of this study was mathematics education students. The results showed that the relationship between problem-solving and computational thinking of respondent when solving the problem is when defining the problem in the context of problem-solving, the respondent performs the stage of decomposition and abstraction in the context of computational thinking. During the planning process of the solution process, respondents carried out the generalization stage. When the scene is carrying out the plan and the problem solver to look back to evaluate the solution, the respondent performs the debugging and algorithmic steps.

Keywords

Computational Thinking Graph Problem Solving Polya Mathematics Education

Article Details

References

  1. Adler, R. F., & Kim, H. (2017). Enhancing future K-8 teachers ’ computational thinking skills through modeling and simulations. Journal Education and Information Technologies, 23(4), 1501–1514.
  2. Ambrosio, A. P., Almeida, L. S., Macedo, J., & Franco, A. H. R. (2014). Exploring core cognitive skills of computational thinking. In Psychology of Programming Interest Group Annual Conference 2014 (PPIG 2014), 25-34.
  3. Angeli, C., Voogt, J., Fluck, A., Webb, M., Cox, M., Malyn-Smith, J., & Zagami, J. (2016). A K-6 computational thinking curriculum framework: Implications for teacher knowledge. Journal of Educational Technology & Society, 19(3).
  4. Acharya, K. P. (2016). Fostering critical thinking practices at primary science classrooms in Nepal. Research in Pedagogy, 6(2), 1-7.
  5. Benakli, N., Kostadinov, B., Satyanarayana, A., & Singh, S. (2017). Introducing computational thinking through hands-on projects using R with applications to calculus , probability and data analysis. International Journal of Mathematical Education in Science and Technology, 48(3), 393–427.
  6. Bower, M., Wood, L. N., Howe, C., & Lister, R. (2017). Improving the Computational Thinking Pedagogical Capabilities of School Teachers. Australian Journal of Teacher Education, 42(3), 53–72.
  7. Cho, Y., & Lee, Y. (2017). Possibility of Improving Computational Thinking Through Activity Based Learning. Journal of Theoretical and Applied Information Technology, 95(18), 4385–4393.
  8. Durak, H. Y., & Saritepeci, M. (2017). Analysis of the relation between computational thinking skills and various variables with the structural equation model. Computers & Education, 116, 191–202.
  9. Gadanidis, G. (2017). Artificial intelligence, computational thinking, and mathematics education. The International Journal of Information and Learning Technology, 34(2), 133–139.
  10. Geary, D. C., Saults, S. J., Liu, F., & Hoard, M. K. (2000). Sex Differences in Spatial Cognition , Computational Fluency , and Arithmetical Reasoning. Journal of Experimental Child Psychology, 77, 337–353.
  11. Grover, S., & Pea, R. (2013). Computational Thinking in K – 12 : A Review of the State of the Field, 42(1), 38–43.
  12. Hartnett, J. (2015). Teaching Computation in Primary School without Traditional Written Algorithms. In Proceedings of the 38th annual conference of the Mathematics Education Research Group of Australasia, 285–292.
  13. Hu, C. (2011). Computational Thinking – What It Might Mean and What We Might Do about It. In ITiCSE ’11: Proceedings of the 16th annual joint conference on Innovation and technology in computer science education, 223–227.
  14. Kong, S. (2016). A framework of curriculum design for computational thinking development in K-12 education. Journal of Computers in Education, 3(4), 377–394.
  15. Korucu, A., Gencturk, A., & Gundogdu, M. (2017). Examination of the computational thinking skills of students. Journal of Learning and Teaching in Digital Age, 2(1), 11-19.
  16. Lockwood, E., DeJarnette, A. F., Asay, A., & Thomas, M. (2016). Algorithmic Thinking: An Initial Characterization of Computational Thinking in Mathematics. North American Chapter of the International Group for the Psychology of Mathematics Education.
  17. Merle, L. J. (2016). Reflective learning and prospective teachers’conceptual understanding, critical thinking, problem solving, and mathematical communication skills. Research in Pedagogy, 6(2), 43-58.
  18. Rambally, G. (2017). Integrating Computational Thinking in Discrete Structures. In Emerging Research, Practice, and Policy on Computational Thinking, 99-119.
  19. Reiss, K., & Törner, G. (2007). Problem solving in the mathematics classroom: The German perspective. ZDM - International Journal on Mathematics Education, 39(5-6), 431–441.
  20. Son, J. W., & Lee, J. E. (2016). Pre-Service Teachers' Understanding of Fraction Multiplication, Representational Knowledge, and Computational Skills. Mathematics Teacher Education and Development, 18(2), 5-28.
  21. Sung, W., Ahn, J., & Black, J. B. (2017). Introducing Computational Thinking to Young Learners: Practicing Computational Perspectives Through Embodiment in Mathematics Education. Technology, Knowledge and Learning, 22(3), 443–463.
  22. Tsai, M., & Tsai, C. (2017). Applying online externally-facilitated regulated learning and computational thinking to improve students ’ learning. Universal Access in the Information Society, 17(4), 811-820.
  23. Voogt, J., Fisser, P., Good, J., Mishra, P., & Yadav, A. (2015). Computational thinking in compulsory education : Towards an agenda for research and practice. Education and Information Technologies, 20(4), 715–728.
  24. Voskoglou, M. G., & Buckley, S. (2012). Problem solving and computational thinking in a learning environment. arXiv preprint arXiv:1212.0750.
  25. Voskoglou, M. G. (2013). Problem solving, fuzzy logic and computational thinking. Egyptian Computer Science Journal, 37(1), 131-145.
  26. 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.
  27. Yasar, O., Maleikal, J., Veronesi, P., & Little, L. J. (2017). The essence of computational thinking and tools to promote it. In American Society for Engineering Education.
  28. Zhong, B., Wang, Q., Chen, J., & Li, Y. (2016). An Exploration of Three-Dimensional Integrated Assessment for Computational Thinking. Journal of Educational Computing Research, 53(4), 562–590.