1,738
Views
3
CrossRef citations to date
0
Altmetric
Articles

Pedagogical content knowledge in computing education: a review of the research literature

Pages 117-135 | Received 28 Feb 2018, Accepted 28 Jul 2018, Published online: 22 Aug 2018

References

  • Abell, S. K. (2008). Twenty years later: does pedagogical content knowledge remain a useful idea? International Journal of Science Education, 30(10), 1405–1416.
  • Anderson, L. W., & Krathwohl, D. R. (2001). A taxonomy for learning, teaching, and assessing: A revision of bloom’s taxonomy of educational objectives. New York, NY: Addison Wesley Longman, Inc.
  • Angeli, C., Voogt, J., Fluck, A., Webb, M., Cox, M., Malyn-Smith, J., & Zagami, J. (2016). A K-6 Computational thinking curriculum framework: implications for teacher knowledge. Journal of Educational Technology & Society, 19(3), 47–57.
  • Armoni, M. (2011). Looking at secondary teacher preparation through the lens of computer science. Transactions Computation Education, 11(4), 23:1–23: 38.
  • Baxter, J. A. (1987). Teacher explanations in computer programming: A study of knowledge transformation (Doctoral dissertation). Stanford University, CA, United States.
  • Baxter, J. A., & Lederman, N. G. (1999). Assessment and measurement of pedagogical content knowledge. In J. Gess-Newsome & N. G. Lederman (Eds.), Examining pedagogical content knowledge (pp. 147–161). Springer.
  • Bender, E., Hubwieser, P., Schaper, N., Margaritis, M., Berges, M., Ohrndorf, L., … Schubert, S. (2015). Towards a competency model for teaching computer science. Peabody Journal of Education (0161956X), 90(4), 519–532.
  • Blömeke, S., & Delaney, S. (2012). Assessment of teacher knowledge across countries: a review of the state of research. .ZDM Mathematics Education, 44(3), 223–247. doi:10.1007/s11858-012-0429-7
  • Blömeke, S., & Paine, L. (2008). Getting the fish out of the water: Considering benefits and problems of doing research on teacher education at an international level. Teaching and Teacher Education, 24(8), 2027–2037.
  • Buchholz, M., Saeli, M., & Schulte, C. (2013). PCK and reflection in computer science teacher education. In M. Caspersen, M. Knobelsdorf, & R. Romeike (Eds.), WiPSE'13. Proceedings of the 8th workshop in primary and secondary computing education (pp. 8–16). New York, NY: ACM. doi:10.1145/2532748.2532752
  • Carpenter, T. P., Fennema, E., Peterson, P. L., & Carey, D. A. (1988). Teachers’ pedagogical content knowledge of students’ problem solving in elementary arithmetic. Journal for Research in Mathematics Education, 19(5), 385–401. doi: 10.2307/749173
  • Depaepe, F., Verschaffel, L., & Kelchtermans, G. (2013). Pedagogical content knowledge: A systematic review of the way in which the concept has pervaded mathematics educational research. Teaching and Teacher Education, 34, 12–25.
  • Fincher, S., & Petre, M. (2004). Part one: The field and the endeavor. In S. Fincher & M. Petre (Eds.), Computer science education research (pp. 1–81). Taylor and Francis.
  • Gess-Newsome, J. (2015). A model of teacher professional knowledge and skill including PCK: Results of the thinking from the PCK summit. In A. Berry, P. Friedrichsen, & J. Loughran (Eds.), Re-examining pedagogical content knowledge in science education (pp. 28–42). New York, NY: Routledge.
  • Giannakos, M. N., Doukakis, S., Crompton, H., Chrisochoides, N., Adamopoulos, N., & Giannopoulou, P. (2014). Examining and mapping CS teachers’ technological, pedagogical and content knowledge (TPACK) in K-12 schools. In M. Cardella, R. Meier, & A. Pears (Eds.), FIE 2014. 2014 IEEE Frontiers in Education Conference (FIE) proceedings (pp. 1–7). Los Alamitos, CA: IEEE Computer Society. doi:10.1109/FIE.2014.7044406
  • Goldsmith, L., Doerr, H., & Lewis, C. (2014). Mathematics teachers’ learning: A conceptual framework and synthesis of research. Journal of Mathematics Teacher Education, 17(1), 5–36.
  • Griffin, J., Pirmann, T., & Gray, B. (2016, March). Two teachers, two perspectives on CS principles. In M. Caspersen & S. Edwards (Eds.), SIGCSE'16. Proceedings of the 47th ACM technical symposium on computing science education. (pp. 461–466). New York, NY: ACM. doi:10.1145/2839509.2844630
  • Grossman, P. L., & Stodolsky, S. S. (1995). Content as context: The role of school subjects in secondary school teaching. Educational Researcher, 24(8), 5–23.
  • Hashweh, M. (2005). Teacher pedagogical constructions: A reconfiguration of pedagogical content knowledge. Teachers and Teaching, 11(3), 273–292.
  • Hashweh, M. (2013). Pedagogical content knowledge: Twenty-five years later. Advances in Research on Teaching, 19, 115–140.
  • Hazzan, O., Lapidot, T., & Ragonis, N. (2015). Guide to teaching computer science: An activity-based approach (2nd ed. 2014 edition ed.). London: Springer.
  • Holmboe, C., McIver, L., & George, C. (2001, April). Research agenda for computer science education. In G.Kadoda (Ed.), PPIG 13. Proceedings of the 13th annual workshop of the psychology of programming interest group. (pp. 207-223). Psychology of Programming Interest Group.
  • Hubbard, A. (2017). Learning to teach computer science: Qualitative insights into secondary teachers’ pedagogical content knowledge. Evanston, IL: Northwestern University.
  • Hubwieser, P., Berges, M., Magenheim, J., Schaper, N., Bröker, K., Margaritis, M., … Ohrndorf, L. (2013a, November). Pedagogical content knowledge for computer science in German teacher education curricula. In M. Caspersen, M. Knobelsdorf, & R. Romeike (Eds.), WiPSE'13. Proceedings of the 8th workshop in primary and secondary computing education. (pp. 95–103). New York, NY: ACM. doi:10.1145/2532748.2532753
  • Hubwieser, P., Giannakos, M. N., Berges, M., Brinda, T., Diethelm, I., Magenheim, J., … Jasute, E. (2015, July). A global snapshot of computer science education in K-12 schools. In N. Ragonis & P. Kinnunen (Eds.), ITiCSE'15. Proceedings of the 2015 ITiCSE on working group reports. (pp. 65–83). New York, NY: ACM. doi:10.1145/2858796.2858799
  • Hubwieser, P., Magenheim, J., Mühling, A., & Ruf, A. (2013b, August). Towards a conceptualization of pedagogical content knowledge for computer science. In B. Simon, A. Clear, & Q. Cutts (Eds.), ICER'13. Proceedings of the ninth annual international ACM conference on International computing education research (pp. 1–8). New York, NY: ACM.doi:10.1145/2493394.2493395
  • Joy, M., Sinclair, J., Sun, S., Sitthiworachart, J., & López-González, J. (2008). Categorising computer science education research. Education and Information Technologies, 14(2), 105–126.
  • Koppelman, H. (2008, June). Pedagogical content knowledge and educational cases in computer science: An exploration. In InSITE 2008. Proceedings of the Informing Science & IT Education Joint Conference 2008 (pp. 125-133). Santa Rosa, CA: Informing Science Institute. doi:10.28945/3228.
  • Lapidot, T. (2005). Computer science teachers’ learning during their everyday work (Doctoral dissertation). Technion University, Israel.
  • Liberman, N., Kolikant, Y. B.-D., & Beeri, C. (2012). “Regressed experts” as a new state in teachers’ professional development: Lessons from computer science teachers’ adjustments to substantial changes in the curriculum. Computer Science Education, 22(3), 257–283.
  • Loughran, J., Gunstone, R., Berry, A., Milroy, P., & Mulhall, P. (2000). Science cases in action: Developing an understanding of science teachers’ pedagogical content knowledge. Retrieved from https://eric.ed.gov/?id=ED442630
  • Loughran, J., Mulhall, P., & Berry, A. (2004). In search of pedagogical content knowledge in science: Developing ways of articulating and documenting professional practice. Journal of Research in Science Teaching, 41(4), 370–391.
  • Margaritis, M., Magenheim, J., Hubwieser, P., Berges, M., Ohrndorf, L., & Schubert, S. (2015, March). Development of a competency model for computer science teachers at secondary school level. In T. Rüütmann & M. Auer (Eds.), EDUCON 2015. Proceeedings of the 2015 IEEE Global Engineering Education Conference (pp. 211–220). Los Alamitos, CA: IEEE Computer Society. doi:10.1109/EDUCON.2015.7095973
  • Matthews, M. E. (2013). The influence of the pedagogical content knowledge framework on research in mathematics education: A Review across Grade Bands. Journal of Education, 193(3), 29–37.
  • Menekse, M. (2015). Computer science teacher professional development in the United States: A review of studies published between 2004 and 2014. Computer Science Education, 25(4), 325–350.
  • Ohrndorf, L., & Schubert, S. (2013, November). Measurement of pedagogical content knowledge: Students’ knowledge and conceptions.  In M. Caspersen, M. Knobelsdorf, & R. Romeike (Eds.), WiPSE'13. Proceedings of the 8th Workshop in Primary and Secondary Computing Education (pp. 104–107). New York, NY: ACM. doi:10.1145/2532748.2532758
  • Ohrndorf, L., & Schubert, S. (2014, November). Students’ Cognition: Outcomes from an Initial Study with Student Teachers. In C. Shulte, M. Caspersen & J. Gal-Ezer (Eds.), WiPSE'14. Proceedings of the 9th Workshop in Primary and Secondary Computing Education (pp. 112–115). New York, NY: ACM. doi:10.1145/2670757.2670758
  • Park, S., & Oliver, J. S. (2008). Revisiting the conceptualisation of pedagogical content knowledge (PCK): PCK as a conceptual tool to understand teachers as professionals. Research in Science Education, 38(3), 261–284.
  • Park, S., Suh, J., & Seo, K. (2017). Development and validation of measures of secondary science teachers’ PCK for teaching photosynthesis. Research in Science Education, 1–25. doi:10.1007/s11165-016-9578-y
  • Ragonis, N. (2009). Computing pre-university: Secondary level computing curricula. In B. Wah (Ed.). Wiley encyclopedia of computer science and engineering (pp. 632-648). John Wiley & Sons, Inc. doi:10.1002/9780470050118.ecse974
  • Ragonis, N., & Hazzan, O. (2009). Integrating a tutoring model into the training of prospective computer science teachers. Journal of Computers in Mathematics and Science Teaching, 28(3), 309–339.
  • Randolph, J. J. (2009). A guide to writing the dissertation literature review. Practical Assessment, Research & Evaluation, 14(13), 1–13.
  • Saeli, M., Perrenet, J., Jochems, W., & Zwaneveld, B. (2010). Portraying the pedagogical content knowledge of programming—The technical report. Retrieved from https://www.tue.nl/fileadmin/content/universiteit/Over_de_universiteit/Eindhoven_School_of_Education/Onderzoek/Projecten_promovendi/Mara_Saeli_SPJZ_Technical_Report.pdf
  • Saeli, M., Perrenet, J., Jochems, W. M. G., & Zwaneveld, B. (2012a). Pedagogical content knowledge in teaching material. Journal of Educational Computing Research, 46(3), 267–293.
  • Saeli, M., Perrenet, J., Jochems, W. M. G., & Zwaneveld, B. (2012b). Programming: Teachers and Pedagogical Content Knowledge in the Netherlands. Informatics in Education, 11(1), 81–114.
  • Schmidt, D. A., Baran, E., Thompson, A. D., Mishra, P., Koehler, M. J., & Shin, T. S. (2009). Technological Pedagogical Content Knowledge (TPACK). Journal of Research on Technology in Education, 42(2), 123–149.
  • Schneider, R. M., & Plasman, K. (2011). Science teacher learning progressions: A review of science teachers’ pedagogical content knowledge development. Review of Educational Research, 0034654311423382. doi:10.3102/0034654311423382
  • Schulte, C. (2008, September). Block model: An educational model of program comprehension as a tool for a scholarly approach to teaching. In C. Shulte (Ed.), ICER'08. Proceedings of the fourth international workshop on computing education research (pp. 149–160). New York, NY: ACM. doi:10.1145/1404520.1404535
  • Settlage, J. (2013). On acknowledging PCK’s shortcomings. Journal of Science Teacher Education, 24(1), 1–12.
  • Shavelson, R. J., Ruiz-Primo, M. A., & Wiley, E. W. (2005). Windows into the mind. Higher Education, 49(4), 413–430.
  • Shulman, L. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher, 15, 4–14.
  • Shulman, L. (1987). Knowledge and teaching: Foundations of the new reform. Harvard Educational Review, 57(1), 1–23.
  • Shulman, L. (2015). PCK: Its genesis and exodus. In A. Berry, P. Friedrichsen, & J. Loughran (Eds.), Re-examining pedagogical content knowledge in science education (pp. 3–13). New York, NY: Taylor & Francis. doi:10.4324/9781315735665
  • Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25(1), 127–147.
  • Wing, J. (2006). Computational thinking. Communications of the ACM, 49, 33–35.
  • Woollard, J. (2005). The implications of the pedagogic metaphor for teacher education in computing. Technology, Pedagogy and Education, 14(2), 189–204.
  • Yadav, A., Mayfield, C., Zhou, N., Hambrusch, S., & Korb, J. T. (2014). Computational thinking in elementary and secondary teacher education. Transactions Computation Education, 14(1), 5:1–5: 16.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.