skip to main content
10.1145/2493394.2493395acmconferencesArticle/Chapter ViewAbstractPublication PagesicerConference Proceedingsconference-collections
research-article

Towards a conceptualization of pedagogical content knowledge for computer science

Published:12 August 2013Publication History

ABSTRACT

ccording to the current state of research, it seems uncontroversial that the Pedagogical Content Knowledge (PCK) of teachers is a crucial factor for the success of teaching and learning in the context of many school subjects. Yet, the research about PCK in the subject of computer science (CS) is still sparse. Thus, we are working on a conceptualization of PCK for computer science (CS) that is based on literature on the one hand and empirically validated on the other. As a first step towards this goal, we have developed a category system from a set of publications from general pedagogy as well as from educational research in other subjects. Additionally, we have compared this system with the outcomes of a former survey among teachers about the preparation of lessons. Currently, we are coding all curricula for teacher education in Germany with this category system and preparing interviews among experts, applying the Critical Incident Technique.

References

  1. Aufschnaiter, C. von and Blömeke, S. 2010. Professionelle Kompetenz von (angehenden) Lehrkräften erfassen -- Desiderata. Zeitschrift für Didaktik der Naturwissenschaften 16, 361--367.Google ScholarGoogle Scholar
  2. Ball, D. L., Thames, M. H., and Phelps, G. 2008. Content Knowledge for Teaching: What Makes It Special? Journal of Teacher Education 59, 5, 389--407.Google ScholarGoogle ScholarCross RefCross Ref
  3. Baumert, J., Blum, W., Brunner, M., Dubberke, T., Jordan, A., Klusmann, U., Krauss, S., Kunter, M., Löwen, K., Neubrand, M., and Yi-Mia, T. 2009. Professionswissen von Lehrkräften, kognitiv aktivierender Mathematikunterricht und die Entwicklung von mathematischer Kompetenz (COACTIV): Dokumentation der Erhebungsinstrumente. Berlin: Max-Planck-Institut für Bildungsforschung. Materialien aus der Bildungsforschung 83.Google ScholarGoogle Scholar
  4. Blömeke, S., Kaiser, G., and Lehmann, R. 2011. Messung professioneller Kompetenz angehender Lehrkräfte: "Mathematics Teaching in the 21st Century" und die IEA-Studie TEDS-M. In Empirische Fundierung in den Fachdidaktiken, H. Bayrhuber, U. Harms, B. Muszynski, B. Ralle, M. Rothgangel, L.-H. Schön, H. J. Vollmer and H.-G. Weigand, Eds. Fachdidaktische Forschungen 1. Waxmann, Münster, 9--26.Google ScholarGoogle Scholar
  5. Brinda, T. and Hubwieser, P. 2010. How to teach didactics of informatics to informatics student teachers. In New developments in ICT and Informatics education.Google ScholarGoogle Scholar
  6. Carlsen, W. 1999. Domains of Teacher Knowledge. In Examining Pedagogical Content Knowledge. The Construct and Its Implications for Science Education, J. Gess-Newsome and N. G. Lederman, Eds. Kluwer Academic Publishers, Dordrecht, Boston, London, 133--146.Google ScholarGoogle Scholar
  7. Cassell, C. and Symon, G. 2004. Essential guide to qualitative methods in organizational research. Sage Publications, London, Thousand Oaks.Google ScholarGoogle Scholar
  8. Diethelm, I., Hubwieser, P., and Klaus, R. 2012. Students, teachers and phenomena: educational reconstruction for computer science education. In Proceedings of the 12th Koli Calling International Conference on Computing Education Research. Koli Calling '12. ACM, New York, NY, USA, 164--173. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Edvardsson, B. and Roos, I. 2001. Critical incident techniques. Towards a framework for analysing the criticality of critical incidents. International Journal of Service Industry Management 12, 3, 251--268.Google ScholarGoogle ScholarCross RefCross Ref
  10. Fincher, S. and Petre, M. 2004. Computer science education research. Taylor & Francis, London, New York. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Flanagan, J. C. 2006. The critical incident technique. Neo-empiricism, 151--188.Google ScholarGoogle Scholar
  12. Hartmann, W., Näf, M., and Reichert, R. 2006. Informatikunterricht planen und durchführen. eXamen.press. Springer, Berlin.Google ScholarGoogle Scholar
  13. Hattie, J. A. C. 2008. Visible learning. A synthesis of over 800 meta-analyses relating to achievement. Routledge, London ;, New York, N.Y.Google ScholarGoogle Scholar
  14. Hazzan, O., Lapidot, T., and Ragonis, N. 2011. Guide to teaching computer science. An activity-based approach. Springer, Berlin. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Heimann, P. 1962. Didaktik als Theorie und Lehre. Die Deutsche Schule 54, 9, S. 409ff.Google ScholarGoogle Scholar
  16. Hubwieser, P. 2007. Didaktik der Informatik: Grundlagen, Konzepte, Beispiele ; mit 68 Tabellen. eXamen.press. Springer, Berlin.Google ScholarGoogle Scholar
  17. Hubwieser, P., Armoni, M., Brinda, T., Dagiene, V., Diethelm, I., Giannakos, M. N., Knobelsdorf, M., Magenheim, J., Mittermeir, R. T., and Schubert, S. E. 2011. Computer science/informatics in secondary education. In Proceedings of the 16th annual conference reports on Innovation and technology in computer science education - working group reports. ITiCSE-WGR '11. ACM, New York, NY, USA, 19--38. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Kattmann, U., Duit, R., and Gropengießer, H. The Model of Educational Reconstruction - bringing together issues of scientific clarification and students' conceptions. European Researchers in Didaktik of Biology: What - why - how?; research in didaktik of biology.Google ScholarGoogle Scholar
  19. Kinnunen, P. n.d. Guidelines of computer science education research. http://www.cs.hut.fi/Research/COMPSER/ROLEP/seminaari-k05/S_05-nettiin/Guidelines_of_CSE-teksti-paivi.pdf. Accessed 29 November 2005.Google ScholarGoogle Scholar
  20. Koppelman, H. 2008. Pedagogical Content Knowledge and Educational Cases in Computer Science: An Exploration. In Proceedings of the Informing Science & IT Education Joint Conference (InSITE) 2008. Varna, Bulgaria, June 22--25., Informing Science Institute, Ed., Santa Rosa, CA, 125--133.Google ScholarGoogle ScholarCross RefCross Ref
  21. Lindmeier, A. 2011. Modeling and measuring knowledge and competencies of teachers. A threefold domain-specific structure model for mathematics. Zugl.: München, Univ., Diss., 2010. Empirische Studien zur Didaktik der Mathematik 7. Waxmann, Münster u.a.Google ScholarGoogle Scholar
  22. Magenheim, J., Nelles, W., Rhode, T., Schaper, N., Schubert, S. E., and Stechert, P. 2010. Competencies for informatics systems and modeling: Results of qualitative content analysis of expert interviews. In Education Engineering (EDUCON), 2010 IEEE, 513--521.Google ScholarGoogle Scholar
  23. Magnusson, S., Krajcik, L., and Borko, H. 1999. Nature, sources and development of pedagogical content knowledge. In Examining pedagogical content knowledge, J. Gess-Newsome and N. G. Lederman, Eds. Kluwer Academic Publishers, Dordrecht, 95--132.Google ScholarGoogle Scholar
  24. Mayring, P. 2000. Qualitative Content Analysis. Forum: Qualitative Social Research 1, 2.Google ScholarGoogle Scholar
  25. Mayring, P. 2010. Qualitative Inhaltsanalyse. Grundlagen und Techniken. Beltz Pädagogik. Beltz, Weinheim.Google ScholarGoogle Scholar
  26. Oser, F. 1997. Standards in der Lehrerbildung. Teil 1: Berufliche Kompetenzen, die hohen Qualitätsmerkmalen entsprechen. Heft 1/1997, S. . Beiträge zur Lehrerbildung, 1, 26--37.Google ScholarGoogle Scholar
  27. Randolph, J., Julnes, G., Sutinen, E., and Lehman, S. 2008. A Methodological Review of Computer Science Education Research. Journal of Information Technology Education 7, 135--162.Google ScholarGoogle ScholarCross RefCross Ref
  28. Riese, J. 2009. Professionelles Wissen und professionelle Handlungskompetenz von (angehenden) Physiklehrkräften. Dissertation, Universität Paderborn.Google ScholarGoogle Scholar
  29. Riese, J. and Reinhold, P. 2008. Entwicklung und Validierung eines Instruments zur Messung professioneller Handlungskompetenz bei (angehenden) Physiklehrkräften. Lehrerbildung auf dem Prüfstand 1, 2, 625--640.Google ScholarGoogle Scholar
  30. Saeli, M. 2012. Teaching Programming for Secondary School: a Pedagogical Content Knowledge Based Approach. Dissertation, Technische Universiteit Eindhoven.Google ScholarGoogle Scholar
  31. Schaper, N. 2009. (Arbeits-)Psychologische Kompetenzforschung. In Forschungsperspektiven in Facharbeit und Berufsbildung. Strategien und Methoden der Berufsbildungsforschung, M. Fischer and G. Spöttl, Eds. Peter Lang, Frankfurt am Main, 91--115.Google ScholarGoogle Scholar
  32. Schaper, N. 2009. Aufgabenfelder und Perspektiven bei der Kompetenzmodellierung und -messung in der Lehrerbildung. Lehrerbildung auf dem Prüfstand 2, Themenheft 1, 166--199.Google ScholarGoogle Scholar
  33. Schmelzing, S., Wüsten, S. S. A., and Neuhaus, B. 2008. Evaluation von zentralen Inhalten der Lehrerbildung: Ansätze zur Diagnostik fachdidaktischen Wissens von Biologielehrkräften. Lehrerbildung auf dem Prüfstand 1, 2, 641--661.Google ScholarGoogle Scholar
  34. Schubert, S. and Schwill, A. 2011. Didaktik der Informatik. Spektrum Akademischer Verl., Heidelberg ;, Berlin.Google ScholarGoogle Scholar
  35. Sekretariat der ständigen Konferenz der Kultusminister der Länder in der Bundesrepublik Deutschland. Standards für die Lehrerbildung: Bildungswissenschaften. Beschluss der Kultusministerkonferenz vom 16.12.2004.Google ScholarGoogle Scholar
  36. Shulman, L. S. 1986. Those Who Understand: Knowledge Growth in Teaching. Educational Researcher 15, 2, 4--14.Google ScholarGoogle ScholarCross RefCross Ref
  37. Shulman, L. S. 1987. Knowledge and teaching: Foundations of the new reform. Harvard Educational Review, Feb., 1--22.Google ScholarGoogle Scholar
  38. Terhart, E. 2002. Standards für die Lehrerbildung. Eine Expertise für die Kultusministerkonferenz. Zfl-Text 24. Inst. für Schulpädag. und Allgemeine Didaktik Univ. Münster, Münster.Google ScholarGoogle Scholar
  39. The Royal Society. 2012. Shutdown or Restart. The way forward for computing in UK schools. http://royalsociety.org/uploadedFiles/Royal_Society_Content/education/policy/computing-in-schools/2012-01--12-Computing-in-Schools.pdf. Accessed 12 November 2012.Google ScholarGoogle Scholar
  40. Uljens, M. 1997. School didactics and learning. A school didactic model framing an analysis of pedagogical implications of learning theory. Psychology Press, Hove.Google ScholarGoogle Scholar
  41. Weinert, F. E. 2001. Concept of Competence: A conceptual clarification. In Defining and Selecting Key Competencies, D. S. Rychen and L. Salganik, Eds. Hogrefe and Huber, Seattle.Google ScholarGoogle Scholar

Index Terms

  1. Towards a conceptualization of pedagogical content knowledge for computer science

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      ICER '13: Proceedings of the ninth annual international ACM conference on International computing education research
      August 2013
      202 pages
      ISBN:9781450322430
      DOI:10.1145/2493394

      Copyright © 2013 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 12 August 2013

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article

      Acceptance Rates

      ICER '13 Paper Acceptance Rate22of70submissions,31%Overall Acceptance Rate189of803submissions,24%

      Upcoming Conference

      ICER 2024
      ACM Conference on International Computing Education Research
      August 13 - 15, 2024
      Melbourne , VIC , Australia

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader