Exploration of Computational Thinking Based on Bebras Performance in Webduino Programming by High School Students

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11003)


The 12-year Basic Education Curriculum Guidelines by the Ministry of Education in Taiwan includes learning performances related to computational thinking and programming languages in technology courses. The students will develop other important competence through programming. Learning a programming language should not only involve focus on writing the programs, but should also stimulate students’ computational thinking competence and allow them to solve daily problems through information techniques. Situated learning emphasizes students’ learning in real scenarios where knowledge is applied as the tool in these real situations. Without such scenarios, the tool has limited value. Likewise, computational thinking competence can be translated as effective problem-solving by the means of information technology. Hence, the thinking process involves analyzing the problems resulting in answers. In addition, the Bebras learning model is based on a concept of informatics which supports comprehension of information science phenomenon and development of computational thinking. This study explored the effects of computational thinking competence on the Bebras test performance. The study targeted senior high school students’ who learned program design using a situated learning strategy.

The results confirm the importance of the situated learning strategy when cultivating students’ computational thinking competence. Based on homogeneity of two groups of students, the experimental group’s posttest score of computational thinking is higher than that of control group. The experimental group were exposed to a situated learning strategy and the control group was not. Significant difference between the two groups shows that the situated learning strategy reinforces computational thinking competence.


Situated learning Computational thinking Bebras 



This research is partially supported by the Ministry of Science and Technology (MOST), Taiwan, R.O.C. under Grant MOST 104-2511-S-224-003-MY3, MOST 105-2628-S-224-001-MY3.


  1. 1.
    Resnick, M.: Learn to code, code to learn. EdSurge, May 2013Google Scholar
  2. 2.
    Chen, G., Shen, J., Barth-Cohen, L., Jiang, S., Huang, X., Eltoukhy, M.: Assessing elementary students’ computational thinking in everyday reasoning and robotics programming. Comput. Educ. 109, 162–175 (2017)CrossRefGoogle Scholar
  3. 3.
    Opmanis, M., Dagiene, V., Truu, A.: Task types at “Beaver” contests. Inf. Technol. Sch. 509–519 (2006)Google Scholar
  4. 4.
    Brown, J.S., Collins, A., Duguid, P.: Situated cognition and the culture of learning. Educ. Res. 18, 32–42 (1989)CrossRefGoogle Scholar
  5. 5.
    Wing, J.: Research notebook: computational thinking—what and why? The Link Magazine, Spring. Carnegie Mellon University, Pittsburgh (2011)Google Scholar
  6. 6.
    Leonard, J., Buss, A., Gamboa, R., Mitchell, M., Fashola, O.S., Hubert, T., Almughyirah, S.: Using robotics and game design to enhance children’s self-efficacy, STEM attitudes, and computational thinking skills. J. Sci. Educ. Technol. 25, 860–876 (2016)CrossRefGoogle Scholar
  7. 7.
    Chaudhary, V., Agrawal, V., Sureka, P., Sureka, A.: An experience report on teaching programming and computational thinking to elementary level children using lego robotics education kit. In: 2016 IEEE 8th International Conference on Technology for Education (T4E 2016), pp. 38–41 (2016)Google Scholar
  8. 8.
    Yindi, D.: Visual basic program designing based on computational thinking capabilities training. In: Proceedings of the 2nd Information Technology and Mechatronics Engineering Conference (ITOEC 2016), vol. 24, pp. 175–178 (2016)Google Scholar
  9. 9.
    Parmar, D., Isaac, J., Babu, S.V., D’Souza, N., Leonard, A.E., Jorg, S., Gundersen, K., Daily, S.B.: Programming moves: design and evaluation of applying embodied interaction in virtual environments to enhance computational thinking in middle school students. In: 2016 IEEE Virtual Reality Conference (VR), pp. 131–140 (2016)Google Scholar
  10. 10.
    Hemmendinger, D.: A plea for modesty. ACM Inroads 1, 4–7 (2010)CrossRefGoogle Scholar
  11. 11.
    Gardiner, L.R., Corbitt, G., Adams, S.J.: Program assessment: Getting to a practical how-to model. J. Educ. Bus. 85, 139–144 (2009)CrossRefGoogle Scholar
  12. 12.
    Meyers, S., Lester, D.: The effects of situated learning through a community partnership in a teacher preparation program. SAGE Open 3(3) (2013).
  13. 13.
    Lave, J., Wenger, E.: Situated Learning: Legitimate Peripheral Participation. Cambridge University Press, Cambridge (1991)CrossRefGoogle Scholar
  14. 14.
    Stein, D.: Situated Learning in Adult Education. ERIC Digest No. 195 (1998)Google Scholar
  15. 15.
    Chen, H.-R., Lin, Y.-S.: An examination of digital game-based situated learning applied to Chinese language poetry education. Technol. Pedagog. Educ. 25, 171–186 (2016)CrossRefGoogle Scholar
  16. 16.
    Angeles Bravo-Alvarez, M., Escolano-Perez, E., Navas-Macho, P., Luisa Herrero-Nivela, M., Eguinoa-Zaborras, F., Acero-Ferrero, M.: A situated learning experience: student satisfaction and improvement of their assessment skills in joint reference disorder. In: ICERI 2015: 8th International Conference of Education, Research and Innovation, pp. 7819–7825 (2015)Google Scholar
  17. 17.
    Lin, W.-C., Huang, D.-Y., Huang, C.-W., Liu, Y.-C., Chen, G.-D.: A video comic for group situated learning in the classroom. In: Edulearn15: 7th International Conference On Education and New Learning Technologies, pp. 4264–4271 (2015)Google Scholar
  18. 18.
    Dagienė, V., Futschek, G.: Bebras international contest on informatics and computer literacy: criteria for good tasks. In: Mittermeir, R.T., Sysło, M.M. (eds.) ISSEP 2008. LNCS, vol. 5090, pp. 19–30. Springer, Heidelberg (2008). Scholar
  19. 19.
    Verhoeff, T., Horváth, G., Diks, K., Cormack, G.: A proposal for an IOI syllabus. Teach. Math. Comput. Sci. 4, 193–216 (2006)CrossRefGoogle Scholar
  20. 20.
    Dagiene, V., Skupiene, J.: Learning by competitions: olympiads in informatics as a tool for training high-grade skills in programming. In: ITRE 2004: 2nd International Conference on Information Technology: Research and Education 2004, pp. 79–83 (2004)Google Scholar
  21. 21.
    Dagiene, V.: Information technology contests-introduction to computer science in an attractive way. Inform. Educ. 5, 37 (2006)Google Scholar

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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.School of Technological and Vocational EducationNational Yunlin University of Science and TechnologyYunlinTaiwan, R.O.C.
  2. 2.Oslo Metropolitan UniversityOsloNorway

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