Investigating Informatics Teachers’ Initial Pedagogical Content Knowledge on Modeling and Simulation

  • Nataša GrgurinaEmail author
  • Erik Barendsen
  • Cor Suhre
  • Klaas van Veen
  • Bert Zwaneveld
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10696)


Computational science, comprised of modeling and simulation, is a new theme in the new 2019 Dutch secondary education informatics curriculum. To investigate the pedagogical content knowledge (PCK) on modeling and simulation, we interviewed ten informatics teachers and analyzed their PCK, distinguishing its four elements - knowledge of goals and objectives, students’ understanding, instructional strategies and assessment - and investigated potential differential features of their PCK in order to typify teachers’ individual PCK. We charted the teachers’ PCK in terms of these four elements and found differential features related to knowledge of goals and objectives and related to knowledge of assessment, dividing these teachers into four distinct groups. However, these differential features do not lead to distinct types of PCK. Our findings will be used to explore the future development of teachers’ PCK and they will contribute to the development of teaching materials, assessment instruments and teacher training courses on modeling.


Pedagogical content knowledge Computational science Modeling and simulation Informatics Secondary education 



This work is supported by the The Netherlands Organisation for Scientific Research grant nr. 023.002.138.


  1. 1.
    Alturki, R.A.: Measuring and improving student performance in an introductory programming course. Inform. Educ. Int. J. 15(2), 183–204 (2016)Google Scholar
  2. 2.
    Barendsen, E., Tolboom, J.: Advisory Report (Intended) Curriculum for Informatics for Upper Secondary Education. SLO, Enschede (2016)Google Scholar
  3. 3.
    Cohen, L., Manion, L., Morrison, K.R.B.: Research Methods in Education, 6th edn. Routledge, New York (2007)Google Scholar
  4. 4.
    Grgurina, N., Tolboom, J.: The first decade of informatics in dutch high schools. Inform. Educ. 7(1), 55–74 (2008)Google Scholar
  5. 5.
    Grgurina, N.: Computational thinking in dutch secondary education (2013)Google Scholar
  6. 6.
    Grgurina, N., Barendsen, E., Zwaneveld, B., van Veen, K., Stoker, I.: Computational thinking skills in dutch secondary education: exploring pedagogical content knowledge. ACM (2014)Google Scholar
  7. 7.
    Grgurina, N., Barendsen, E., Zwaneveld, B., van Veen, K., Stoker, I.: Computational thinking skills in dutch secondary education: exploring teacher’s perspective. ACM (2014)Google Scholar
  8. 8.
    Grgurina, N., Barendsen, E., Zwaneveld, B., van Veen, K., Suhre, C.: Defining and observing modeling and simulation in informatics. In: Brodnik, A., Tort, F. (eds.) ISSEP 2016. LNCS, vol. 9973, pp. 130–141. Springer, Cham (2016). CrossRefGoogle Scholar
  9. 9.
    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)Google Scholar
  10. 10.
    Henze, I., van Driel, J.H., Verloop, N.: Development of experienced science teachers’ pedagogical content knowledge of models of the Solar System and the Universe. Int. J. Sci. Educ. 30(10), 1321–1342 (2008)CrossRefGoogle Scholar
  11. 11.
    Henze, I., van Driel, J.H., Verloop, N.: Science teachers’ knowledge about teaching models and modelling in the context of a new syllabus on public understanding of science. Res. Sci. Educ. 37(2), 99–122 (2007)CrossRefGoogle Scholar
  12. 12.
    Justi, R., Gilbert, J.: Teachers’ views on the nature of models. Int. J. Sci. Educ. 25(11), 1369–1386 (2003)CrossRefGoogle Scholar
  13. 13.
    Justi, R.S., Gilbert, J.K.: Science teachers’ knowledge about and attitudes towards the use of models and modelling in learning science. Int. J. Sci. Educ. 24(12), 1273–1292 (2002)CrossRefGoogle Scholar
  14. 14.
    Lee, E., Brown, M.N., Luft, J.A., Roehrig, G.H.: Assessing beginning secondary science teachers’ PCK: pilot year results. School Sci. Math. 107(2), 52–60 (2007)CrossRefGoogle Scholar
  15. 15.
    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. Kluwer (1999)Google Scholar
  16. 16.
    Rahimi, E., Barendsen, E., Henze, I.: Typifying informatics teachers’ PCK of designing digital artefacts in dutch upper secondary education. In: Brodnik, A., Tort, F. (eds.) ISSEP 2016. LNCS, vol. 9973, pp. 65–77. Springer, Cham (2016). CrossRefGoogle Scholar
  17. 17.
    Saeli, M.: Teaching programming for secondary school: a pedagogical content knowledge base approach. Ph.D., Eindhoven Institute of Technology (2012)Google Scholar
  18. 18.
    Sanders, L.R., Borko, H., David Lockard, J.: Secondary science teachers’ knowledge base when teaching science courses in and out of their area of certification. J. Res. Sci. Teach. 30(7), 723–736 (1993)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Nataša Grgurina
    • 1
    Email author
  • Erik Barendsen
    • 2
    • 3
  • Cor Suhre
    • 1
  • Klaas van Veen
    • 1
  • Bert Zwaneveld
    • 3
  1. 1.Teaching and Teacher EducationUniversity of GroningenGroningenThe Netherlands
  2. 2.Radboud UniversityNijmegenThe Netherlands
  3. 3.Open UniversityHeerlenThe Netherlands

Personalised recommendations