Abstract
Computational Thinking (CT) is gaining a lot of attention in education. In this study we focus on the CT aspect modeling and simulation. We conducted a case study analyzing the projects of 12th grade high school informatics students in which they made models and ran simulations of phenomena from other disciplines. We constructed an analytic framework based on literature about modeling and analyzed students’ project documentation, recordings of student groups at work and during presentations, survey results and interviews with individual students. We examined how to discern the elements of our framework in the students’ work. Moreover, we determined which data sources are suitable for observing students’ learning. Finally, we investigated what difficulties students encounter while working on modeling and simulation projects. Our findings result in an operational definition of modeling and simulation, and provide input for future development of both assessment instruments and instructional strategies.
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References
Barendsen, E., Tolboom, J.: Advisory Report (Intended) Curriculum for Informatics for Upper Secondary Education. SLO, Enschede (2016)
Blikstein, P., Wilensky, U.: An atom is known by the company it keeps: content, representation and pedagogy within the epistemic revolution of the complexity sciences (2009)
Borshchev, A.: The Big Book of Simulation Modeling: Multimethod Modeling with AnyLogic 6. AnyLogic North America, Chicago (2013)
Brennan, K., Resnick, M.: New frameworks for studying and assessing the development of computational thinking (2012)
CSTA Computational Thinking Task Force. Operational Definition of Computational Thinking for K-12 Education. http://csta.acm.org/Curriculum/sub/CurrFiles/CompThinkingFlyer.pdf. Accessed 16 Oct 2013
Caspersen, M.E., Nowack, P.: Model-Based Thinking & Practice
Comer, D.E., Gries, D., Mulder, M.C., Allen Tucker, A., Turner, J., Young, P.R., Denning, P.J.: Computing as a discipline. Commun. ACM 32(1), 9–23 (1989)
Gouws, L., Bradshaw, K., Wentworth, P.: First year student performance in a test for computational thinking. ACM, East London, South Africa (2013)
Granger, C.: Coding is not the new literacy. http://www.chris-granger.com/2015/01/26/coding-is-not-the-new-literacy/. Accessed 09 Oct 2015
Grgurina, N.: Computational thinking in Dutch secondary education (2013)
Grgurina, N., Barendsen, E., Zwaneveld, B., van Veen, K., Stoker, I.: Computational thinking skills in Dutch secondary education: exploring pedagogical content knowledge. ACM (2014)
Grgurina, N., Barendsen, E., Zwaneveld, B., van Veen, K., Stoker, I.: Computational thinking skills in Dutch secondary education: exploring teacher’s perspective. ACM (2014)
Grgurina, N., Barendsen, E., van Veen, K., Suhre, C., Zwaneveld, B.: Exploring students’ computational thinking skills in modeling and simulation projects: a pilot study. ACM (2015)
Grover, S.: Robotics and engineering for middle and high school students to develop computational thinking (2011)
Law, A.M.: Simulation Modeling and Analysis, 5th edn. McGraw-Hill, New York (2015)
Maaß, K.: What are modelling competencies? ZDM Math. Educ. 38(2), 113–142 (2006)
Magnusson, S., Krajcik, J., Borko, H.: Nature, sources, and development of pedagogical content knowledge for science teaching. In: Gess-Newsome, J., Lederman, N.G. (eds.) Examining Pedagogical Content Knowledge, pp. 95–132. Springer, Netherlands (1999)
Meerbaum-Salant, O., Armoni, M., Ben-Ari, M.: Learning computer science concepts with scratch. Comput. Sci. Educ. 23(3), 239–264 (2013)
Perrenet, J., Zwaneveld, B.: The many faces of the mathematical modeling cycle. J. Math. Model. Appl. 1(6), 3–21 (2012)
Polya, G.: How to Solve It: A New Aspect of Mathematical Method. Princeton University Press, Princeton (2008)
Robins, A., Rountree, J., Rountree, N.: Learning and teaching programming: a review and discussion. Comput. Sci. Educ. 13(2), 137–172 (2003)
Shulman, L.S.: Those who understand: knowledge growth in teaching. Educ. Res. 15(2), 4–14 (1986)
Spodniakova Pfefferova, M.: Computer simulations and their influence on students’ understanding of oscillatory motion. Inform. Educ. 14(2), 279–289 (2015)
Taub, R., Armoni, M., Ben-Ari, M.M.: Abstraction as a bridging concept between computer science and physics. ACM (2014)
Van Overveld, K., Borghuis, T., van Berkum, E.: From problems to numbers and back. In: Lecture Notes to ‘A Discipline-Neutral Introduction to Mathematical Modelling’. Eindhoven University of Technology, Eindhoven (2015)
Werner, L., Denner, J., Campe, S., Kawamoto, D.C.: The fairy performance assessment: measuring computational thinking in middle school. ACM, Raleigh, North Carolina, USA (2012)
Wilensky, U.: Computational thinking through modeling and simulation. White paper Presented at the Summit on Future Directions in Computer Education, Orlando, FL (2014). http://www.stanford.edu/~coopers/2013Summit/WilenskyUriNorthwesternREV.pdf
Wilensky, U., Brady, C.E., Horn, M.S.: Fostering computational literacy in science classrooms. Commun. ACM 57(8), 24–28 (2014)
Wilensky, U., Rand, W.: An Introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo. MIT Press, Cambridge (2015)
Wing, J.M.: Computational thinking. Commun. ACM 49(3), 33–35 (2006)
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This work is supported by The Netherlands Organisation for Scientific Research grant nr. 023.002.138.
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Grgurina, N., Barendsen, E., Zwaneveld, B., van Veen, K., Suhre, C. (2016). Defining and Observing Modeling and Simulation in Informatics. In: Brodnik, A., Tort, F. (eds) Informatics in Schools: Improvement of Informatics Knowledge and Perception. ISSEP 2016. Lecture Notes in Computer Science(), vol 9973. Springer, Cham. https://doi.org/10.1007/978-3-319-46747-4_11
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