Skip to main content

Advertisement

Log in

The effect of simulation games on learning computer programming: A comparative study on high school students’ learning performance by assessing computational problem-solving strategies

  • Published:
Education and Information Technologies Aims and scope Submit manuscript

Abstract

Computer games are quickly gaining momentum by enabling new approaches to teaching and learning experience for programming courses in K-12 curriculum. However, it remains unclear if the game interface and elements created by using three-dimensional (3D) virtual worlds combined with visual programming languages or a visual programming environment can affect students’ learning performance. This quasi-experimental study presents evidence about how a game can assist boys and girls to gain a greater understanding on skills related to CT for developing, implementing and transforming their solution plans into code based on their computational problem-solving strategies. A total of fifty (n = 50) high school students who volunteered to participate in this study divided into a control group (n = 25) and an experimental (n = 25) group that used Scratch and OpenSim with the Scratch4SL palette, respectively to propose their solutions for the same problem-solving tasks via a simulation game. The study findings indicate substantial differences and important points of view about students’ learning performance by assessing their computational problem-solving strategies. Students from the experimental group performed significantly better both in measures of problem-solving and algorithmic thinking. Mean scores on post-questionnaires from the experimental group revealed improvements higher than their control group counterparts in two aspects. First, students of the former group created more complete computational instructions with rules to be specified and delivered the learning goals. Second, students of the same group proposed and applied more correct computational concepts and practices in code. Finally, this study discusses the implications for designing learning experiences using OpenSim with Scratch4SL.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • ACM Education Policy Committee. (2014). Rebooting the pathway to success: Preparing students for computing workforce needs in the United States. Retrieved 20 March 2016 from: http://www.lisakaczmarczyk.com/uploads/3/2/0/9/32096719/acm_pathways_report.pdf.

  • Bienkowski, M., Snow, E., Rutstein, D. W., & Grover, S. (2015). Assessment design patterns for computational thinking practices in secondary computer science: A first look (SRI technical report). Menlo Park: SRI International.

    Google Scholar 

  • Brennan, K., & Resnick, M. (2012). New frameworks for studying and assessing the development of computational thinking. In Proceedings of the 2012 Annual meeting of the American Educational Research Association, Vancouver.

  • Chao, P.-Y. (2016). Exploring students’ computational practice, design and performance of problem-solving through a visual programming environment. Computers & Education, 95(2), 202–215.

    Article  Google Scholar 

  • Cohen, L., Manion, L., & Morrison, K. (2011). Research methods in education. Abingdon: Routledge.

    Google Scholar 

  • CSTA & ISTE (2011). Computational thinking in K–12 education leadership toolkit. Retrieved 20 March 2016 from: http://www.iste.org/docs/ct-documents/ct-leadershipt-toolkit.pdf?sfvrsn=4.

  • Dalgarno, B., & Lee, M. J. W. (2010). What are the learning affordances of 3-D virtual environments? British Journal of Educational Technology, 41(1), 10–32.

    Article  Google Scholar 

  • Davies, S. (2008). The effects of emphasizing computational thinking in an introductory programming course. Frontiers in Education Conference (FIE 2008). 38th Annual, IEEE. https://doi.org/10.1109/fie.2008.4720362.

  • de Raadt, M. (2007). A review of Australasian investigations into problem-solving and the novice programmer. Computer Science Education, 17(3), 201–213.

    Article  Google Scholar 

  • Denner, J., Werner, L., & Ortiz, E. (2012). Computer games created by middle school girls: Can they be used to measure understanding of computer science concepts? Computers & Education, 58(1), 240–249.

    Article  Google Scholar 

  • Esteves, M., Fonseca, B., Morgado, L., & Martins, P. (2011). Improving teaching and learning of computer programming through the use of the second life virtual world. British Journal of Educational Technology, 42(4), 624–637.

    Article  Google Scholar 

  • Garneli, V., & Chorianopoulos, K. (2017). Programming video games and simulations in science education: Exploring computational thinking through code analysis. Interactive Learning Environments, 26, 386–401. https://doi.org/10.1080/10494820.2017.1337036.

    Article  Google Scholar 

  • Garneli, V., Giannakos, M., & Chorianopoulos, K. (2015). Computing education in K-12 schools: A review of the literature. IEEE Global Engineering Education Conference (EDUCON) (pp. 536-544). IEEE: Tallinn, Estonia.

  • Girvan, C., Tangney, B., & Savage, T. (2013). SLurtles: Supporting constructionist learning in 'Second Life'. Computers & Education, 61(4), 115–132.

    Article  Google Scholar 

  • Good, J., Howland, K., & Thackray, L. (2008). Problem-based learning spanning real and virtual worlds: A case study in second life. ALT-J, Research in Learning Technology, 16(3), 163–172.

    Article  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.

    Article  Google Scholar 

  • Grover, S., Pea, R., & Cooper, S. (2015). Designing for deeper learning in a blended computer science course for middle school students. Computers Science Education, 25(2), 199–237.

    Article  Google Scholar 

  • Howland, K., & Good, J. (2015). Learning to communicate computationally with Flip: A bi-modal programming language for game creation. Computers & Education, 80(2), 224–240.

    Article  Google Scholar 

  • Jakos, F., & Verber, D. (2016). Learning basic programming skills with educational games: A case of primary schools in Slovenia. Journal of Educational Computing Research, 55, 673–698. https://doi.org/10.1177/0735633116680219.

    Article  Google Scholar 

  • Kafai, Y., & Burke, Q. (2015). Constructionist gaming: Understanding the benefits of making games for learning. Educational Psychologist, 50(4), 313–334.

    Article  Google Scholar 

  • Knight, J. K. (2010). Biology concept assessment tools: Design and use. Microbiology, 5.

  • Koorsse, M., Cilliers, C., & Calitz, A. (2015). Programming assistance tools to support the learning of IT programming in south African secondary schools. Computers & Education, 82(2), 162–178.

    Article  Google Scholar 

  • Korkmaz, Ö., Çakir, R., & Özden, M. Y. (2017). A validity and reliability study of the Computational Thinking Scales (CTS). Computers in Human Behavior, 72, 558–569. https://doi.org/10.1016/j.chb.2017.01.005.

    Article  Google Scholar 

  • Lahtinen, E., Ala-Mutka, K., & Järvinen, H. (2005). A study of the difficulties of novice programmers. In: Proceedings of the 10th Annual SIGCSE Conference on innovation and Technology in Computer Science Education (pp. 14–18). Caparica: ACM.

    Google Scholar 

  • Liu, C. C., Cheng, Y. B., & Huang, C. W. (2011). The effect of simulation games on the learning of computational problem solving. Computers & Education, 57, 1907–1918.

    Article  Google Scholar 

  • Liu, Z., Zhi, R., Hicks, Z., & Barnes, T. (2017). Understanding problem solving behavior of 6–8 graders in a debugging game. Computer Science Education, 27, 1–29. https://doi.org/10.1080/08993408.2017.1308651.

    Article  Google Scholar 

  • 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(3), 51–61.

    Article  Google Scholar 

  • Marx, J. D., & Cummings, K. (2007). Normalized change. American Journal of Physics, 75, 87–91.

    Article  Google Scholar 

  • Mouza, C., Marzocchi, A., Pan, Y., & Pollock, L. (2016). Development, implementation, and outcomes of an equitable computer science after-school program: Findings from middle-school students. Journal of Research on Technology in Education, 48(2), 84–104.

    Article  Google Scholar 

  • Pellas, N., & Vosinakis, S. (2017a). How can a simulation game support the development of computational problem-solving strategies? In IEEE Global Engineering Education Conference (pp. 1124–1131). IEEE: Greece, Athens.

  • Pellas, N., & Vosinakis, S. (2017b). Learning to think and practice computationally via a 3D simulation game. 11th International Conference on Interactive Mobile Communication, Technologies and Learning (IMCL 2017). In IMCL2017 Proceedings "Advances in Intelligent Systems and Computing" (pp. 193–204). M. E. Auer and T. Tsiatsos (Eds.): IMCL 2017, AISC 725, (pp. 550–562). Thessaloniki, Greece: Springer.

  • Repenning, A., Webb, D., & Ioannidou, A. (2010). Scalable game design and the development of a checklist for getting computational thinking into public schools. In Proceedings of the 41st ACM Technical Symposium On Computer Science Education (SIGCSE ‘10), (pp. 265–269). New York, NY: ACM Press.

  • Rico, M., Martνnez-Muρoz, G., Alaman, X., Camacho, D., & Pulido, E. (2011). Improving the programming experience of high school students by means of virtual worlds. International Journal of Engineering Education, 27(1), 52–60.

    Google Scholar 

  • Robins, A., Rountree, J., & Rountree, N. (2003). Learning and teaching programming: A review and discussion. Computer Science Education, 13, 137–172.

    Article  Google Scholar 

  • Román-González, M., Pérez-González, J.-C., & Jiménez-Fernández, C. (2016). Which cognitive abilities underlie computational thinking? Criterion validity of the computational thinking test. Computers in Human Behavior, 72(1), 678–691.

    Google Scholar 

  • Rosenbaum, E. (2008). Scratch for second life. In S. Veeragoudar Harrell (Chair & Organizer), Virtually there: Emerging designs for STEM teaching and learning in immersive online 3D microworlds. Symposium in proceedings of the international conference on learning sciences – ICLS 2008. Utrecht, The Netherlands: ICLS.

  • Singh, K. (2007). Quantitative social research methods. Thousand Oaks: Sage Publications.

    Book  Google Scholar 

  • Slavin, R. E., Cheung, A., Groff, C., & Lake, C. (2007). Effective reading programs for middle and high schools: A best-evidence synthesis. Baltimore: Johns Hopkins University, Center for Data-Driven Reform in Education.

    Google Scholar 

  • Topu, F. B., Reisoğlu, İ., Yılmaz, T. K., et al. (2018). Information retention’s relationships with flow, presence and engagement in guided 3D virtual environments. Education and Information Technologies. https://doi.org/10.1007/s10639-017-9683-1.

    Article  Google Scholar 

  • Webb, H., & Rosson, M. B. (2013). Using scaffolded examples to teach computational thinking concepts. In Proceeding of the 44th ACM technical symposium on computer science education (pp. 95–100). ACM.

  • Werner, L., Denner, J., & Campe, S. (2015). Children programming games: A strategy for measuring computational learning. ACM Transactions on Computing Education, 14, 24.

    Google Scholar 

  • Wing, J. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35.

    Article  Google Scholar 

  • Witherspoon, E. B., Higashi, R. M., Schunn, C. D., Baehr, E. C., & Shoop, R. (2017). Developing computational thinking practices through a virtual robotics programming curriculum. ACM Transactions on Computing Education, 18(1), 20.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nikolaos Pellas.

Ethics declarations

Conflict of interest

All authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pellas, N., Vosinakis, S. The effect of simulation games on learning computer programming: A comparative study on high school students’ learning performance by assessing computational problem-solving strategies. Educ Inf Technol 23, 2423–2452 (2018). https://doi.org/10.1007/s10639-018-9724-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10639-018-9724-4

Keywords

Navigation