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The aim of the present article is to analyze the relation of physical computing with the computational thinking dimensions and the transdisciplinary approach of STEM epistemology in inquiry-based learning environments, when the methodology of the computational experiment is implemented. We argue that computational science and computational experiment can be applied in connection with STEM epistemology, when physical computing activities are embedded in the curriculum for Higher Education students. In order to implement this connection, we present software applications that combine algorithms and physical computing. We believe that engaging students through their existing STEM courses in physical computing - in the form of the computational experiment methodology- is a strategy that is much more likely to succeed in increasing the interest and appeal of STEM epistemology. Different learning modules were designed, which covered the combination of easy java simulations (Ejs) with Arduino and Raspberry pi.

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References

  1. C. Angeli, J. Voogt, A. Fluck, M. Webb, J. Malyn-Smith and J. Zagami, “A K-6 Computational Thinking Curriculum Framework- Implications for Teacher Knowledge,” Educational Technology & Society, vol. 19 no. 3, pp. 47–57, 2016.
     Google Scholar
  2. L. D. Asay, and M.K. Orgill, “Analysis of essential features of inquiry found in articles published in The Science Teacher, 1998-2007,” Journal of Science Teacher Education, vol. 21, pp. 57-79, 2010.
     Google Scholar
  3. V. Barr and C. Stephenson, “Bringing Computational Thinking to K-12: What Is Involved and What Is the Role of the Computer Science Education Community?” ACM Inroads, vol. 2, no.1, pp. 48-54, 2010.
     Google Scholar
  4. T. Bell, D. Urhahne, S. Schanze, and R. Ploetzner, “Collaborative inquiry learning: models, tools and challenges,” International Journal of Science Education, vol. 32, no. 3, pp. 349-377, 2010.
     Google Scholar
  5. P.L. Bell, C. Hoadley, and M.C. Linn, “Design-based research as educational inquiry,” in Internet environments for science education, Eds. M.C. Linn, and P.L. Bell, Mahwah, NJ: Lawrence Erlbaum Associates, 2004.
     Google Scholar
  6. R. W. Bybee, L.W. Trowbridge, and J.C. Powell, Teaching Secondary School Science: Strategies for Developing Scientific Literacy, New Jersey Merrill, 2008.
     Google Scholar
  7. I. Cetin, and C. Andrews-Larson, “Learning sorting algorithms through visualization construction,” Computer Science Education, vol. 26, no. 1, pp. 27-43, 2016
     Google Scholar
  8. P. Curzon, “cs4fn and computational thinking unplugged,” WiPSE ’13. Proceedings of the 8th Workshop in Primary and Secondary Computing Education, pp. 47-50, 2013.
     Google Scholar
  9. European Commission. Developing Computational Thinking in Compulsory Education. JRC SCIENCE FOR POLICY REPORT [Online]. Available: http://publications.jrc.ec.europa.eu/repository/
     Google Scholar
  10. bitstream/JRC104188/jrc104188_computhinkreport.pdf, 2016
     Google Scholar
  11. T.R. Kelley, and J.G. Knowles, “A conceptual framework for integrated STEM education,” International Journal of STEM Education, vol. 3 no. 11, 2016.
     Google Scholar
  12. D. Klahr, and K. Dunbar, “Dual space search during scientific reasoning. Cognitive Science,” vol. 12, pp. 1-48, 1998.
     Google Scholar
  13. R.H. Landau, J. Paez, and C. Bordeianu, A Survey of computational physics: introductory computational science, New Jersey: Princeton University Press, 2008.
     Google Scholar
  14. S. Libow Martinez, and G. Stager, Invent to Learn - Making, Tinkering, and Engineering in the Classroom, Torrance, CA: Constructing Modern Knowledge Press, 2013.
     Google Scholar
  15. I.K. Namukasa, D. Kotsopoulos, L. Floyd, J. Weber, Y.B. Kafai, and S. Khan, ‘‘From computational thinking to computational participation: Towards achieving excellence through coding in elementary schools,’’ in: Math + coding symposium, ed G. Gadanidis. London: Western University, 2015.
     Google Scholar
  16. S. Papert, Mindstorms: Children, computers, and powerful ideas, New York: Basic Books, 1980.
     Google Scholar
  17. M. Przybylla, and R. Romeike, R, “Physical computing and its scope - towards a constructionist computer science curriculum with physical computing,” Informatics in Education, vol. 13, no. 2, pp. 225-240, 2014.
     Google Scholar
  18. M. Przybylla, and R. Romeike, “Physical computing in computer science education,” Proceedings of the 9th Workshop in Primary and Secondary Computing Education. Berlin, Germany. November 5-7, pp. 136-137, 2014.
     Google Scholar
  19. S. Psycharis, “Inquiry-based computational experiment, acquisition of threshold concepts and argumentation in science and mathematics education,” Journal of Educational Technology & Society, vol. 19, no. 3, 2016.
     Google Scholar
  20. S. Psycharis, “The impact of computational experiment and formative assessment in inquiry-based teaching and learning approach in STEM education,” Journal of Science Education, and Technology, vol. 25, no. 2, pp. 316-326, 2015.
     Google Scholar
  21. S. Psycharis, “The effect of the computational models on learning performance, scientific reasoning, epistemic beliefs and argumentation,” Computers & Education, vol. 68, pp. 253–265, 2013.
     Google Scholar
  22. M. Resnick, J. Maloney, A. Monroy-Hernandez, N. Rusk, E. Eastmond, and K. Brennan, K., “Scratch: Programming for all,” Communications of the ACM, vol. 52, no. 11, pp. 60-67, 2009.
     Google Scholar
  23. M. Sanders, “A rationale for new approaches to STEM education and STEM education graduate programs,” presented at the 93rd Mississippi Valley Technology Teacher Education Conference, Nashville, TN, 2006.
     Google Scholar
  24. S. Schulz, and N. Pinkwart, N., Physical Computing in STEM Education [Online]. Available: https://cses.informatik.hu-berlin.de/pubs/2015/wipsce/physical-computing-in-stem-education.pdf, 2016
     Google Scholar
  25. J. M. Wing, “Computational thinking and thinking about computing,” Communications of the ACM, vol. 49, pp. 33-35, 2006.
     Google Scholar