Advertisement

Learning to Think and Practice Computationally via a 3D Simulation Game

  • Nikolaos PellasEmail author
  • Spyridon Vosinakis
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 725)

Abstract

Various studies have presented controversial results about the way that young students tried to cultivate and practice their computational thinking (CT) skills with Computer science concepts through the game making programming. However, there is still limited evidence addressing how the gameplay of a simulation game (SG) can be associated with the development of computational problem-solving practices. Therefore, the purpose of the present study is threefold: (a) to elaborate a rationale on how a 3D SG can support the development of computational problem-solving practices using OpenSimulator with Scratch4SL, (b) to analyze how the in-game elements should be mapped to assist basic CT skills cultivation and programming concepts to support students in learning how to think and practice computationally, and (c) to summarize the findings from a preliminary mixed methods study following a game playing approach in regard to the learning experience with a total of fifteen (n = 15) junior high school students. The results indicate that students had a greater range of expressing sufficiently alternative and self-explanatory solutions in blended instruction. The instructor’s feedback and guidance facilitate them to rationalize decisions taken on the cognitive aspects of computational practices in coding.

Keywords

Computational thinking Game-based learning Virtual worlds 

References

  1. 1.
    Liu, C., Cheng, Y., Huang, C.: The effect of simulation games on the learning of computational problem-solving. Comput. Educ. 57, 1907–1918 (2011)CrossRefGoogle Scholar
  2. 2.
    Mouza, et al.: Development, implementation, and outcomes of an equitable computer science after-school program: findings from middle-school students. J. Res. Technol. Educ. 48, 84–104 (2016)CrossRefGoogle Scholar
  3. 3.
    Grover, S., Pea, R.: Computational thinking in K–12: a review of the state of the field. Educ. Res. 42, 38–43 (2013)CrossRefGoogle Scholar
  4. 4.
    Lye, S., Koh, L.: Review on teaching and learning of computational thinking through programming: what is next for K-12? Comput. Hum. Behav. 41, 51–61 (2014)CrossRefGoogle Scholar
  5. 5.
    Kalelioglu, F., Gülbahar, Y., Kukul, V.: A framework for computational thinking based on a systematic research review. Baltic J. Mod. Comput. 4, 583–596 (2016)Google Scholar
  6. 6.
    Pellas, N., Vosinakis, S.: How can a simulation game support the development of computational problem-solving strategies? In: EDUCON. IEEE, Athens, pp. 1124–1131 (2017)Google Scholar
  7. 7.
    Brennan, K., Resnick, M.: New frameworks for studying and assessing the development of computational thinking. In: AERA, Vancouver, Canada (2012)Google Scholar
  8. 8.
    Kafai, Y., Burke, Q.: Constructionist gaming: understanding the benefits of making games for learning. Educ. Psychol. 50, 313–334 (2015)CrossRefGoogle Scholar
  9. 9.
    Esteves, M., et al.: Improving teaching and learning of computer programming through the use of the Second Life virtual world. BJET 42, 624–637 (2011)CrossRefGoogle Scholar
  10. 10.
    Girvan, C., Tangney, B., Savage, T.: SLurtles: supporting constructionist learning in Second Life. Comput. Educ. 61, 115–132 (2013)CrossRefGoogle Scholar
  11. 11.
    Rico, M., et al.: Improving the programming experience of high school students by means of virtual worlds. Int. J. Eng. Educ. 27, 52–60 (2011)Google Scholar
  12. 12.
    Howland, K., Good, J.: Learning to communicate computationally with Flip: a bi-modal programming language for game creation. Comput. Educ. 80, 224–240 (2015)CrossRefGoogle Scholar
  13. 13.
    Wing, J.: Computational thinking. CACM 49, 33–35 (2006)CrossRefGoogle Scholar
  14. 14.
    Theodoropoulos, A., Antoniou, A., Lepouras, G.: How do different cognitive styles affect learning programming? Insights from a game-based approach in Greek schools. ACM Trans. Comput. Educ. 17, 3 (2016)CrossRefGoogle Scholar
  15. 15.
    Román-González, M., Pérez-González, J.-C., Jiménez-Fernández, C.: Which cognitive abilities underlie computational thinking? Criterion validity of the computational thinking test. Comput. Hum. Behav. 72, 678–691 (2017)CrossRefGoogle Scholar
  16. 16.
    Faiola, A., Newlon, C., Pfaff, D., Smyslova, O.: Correlating the effects of flow and telepresence in virtual worlds: enhancing our understanding of user behavior in game-based learning. Comput. Hum. Behav. 29, 1113–1121 (2013)CrossRefGoogle Scholar
  17. 17.
    Bargas-Avila, J.A., Hornbæk, K.: Old wine in new bottles or novel challenges: a critical analysis of empirical studies of user experience. In: SIGCHI. ACM, New York, pp. 2689–2698 (2011)Google Scholar
  18. 18.
    Tullis, T., Albert, W.: Measuring the User Experience: Collecting, Analyzing, and Presenting Usability Metrics. Morgan Kaufmann Publishers Inc., San Francisco (2013)Google Scholar

Copyright information

© Springer International Publishing AG, a part of Springer Nature 2018

Authors and Affiliations

  1. 1.University of the AegeanMytileneGreece

Personalised recommendations