Using Card Sorting Activity as a Strategy for Evaluating Students’ Learning of Computational Thinking Concepts

https://doi.org/10.21585/ijcses.v6i4.215

Authors

  • Yasemin Allsop UCL
  • Filiz Kalelioglu Başkent University
  • Melike Aslan Unlu UCL

Keywords:

Computational thinking, assessment, learning, card sorting activity, teacher training, trainee teachers

Abstract

This study investigated the effectiveness of the ‘Match it’ card sorting activity for evaluating the prospective teachers’ knowledge and understanding of computational thinking (CT) concepts. 146 primary prospective teachers were asked to sort 26 scenarios and words alongside nine images under five main computational concepts: algorithmic thinking, abstraction, decomposition, patterns & generalisation, and evaluation. The study found that the card sorting activity, as a method for assessment was useful, however, the issues around the design and the content of the current card sorting activity were reported by students which suggests that further revisions should be made to improve the effectiveness of the tool.

Downloads

Download data is not yet available.

References

Aho, A. V. (2012). Computation and Computational thinking. The Computer Journal, 55(7), 832-835. DOI: https://doi.org/10.1093/comjnl/bxs074

Allsop, Y. (2019). Assessing computational thinking process using a multiple evaluation approach. International journal of child-computer interaction, 19, 30-55.

Black, P. & Wiliam, D., (1998). Assessment and classroom learning. Assessment in Education: principles, policy & practice, 5(1), 7-74. DOI: https://doi.org/10.1080/0969595980050102

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative research in psychology, 3(2), 77-101. DOI: https://doi.org/10.1191/1478088706qp063oa

Brennan, K., & Resnick, M. (2012). New Frameworks for Studying and Assessing the Development of Computational Thinking. In Proceedings of the 2012 Annual Meeting of the American Educational Research Association, Vancouver, Canada, 1-25.

Cooke, N. J. (1994). Varieties of knowledge elicitation techniques. International journal of human-computer studies, 41(6), 801-849. DOI: https://doi.org/10.1006/ijhc.1994.1083

Cuny, J., Snyder, L., & Wing, J. M. (2010). Demystifying Computational Thinking for Non-Computer Scientists. [Unpublished Manuscript] Retrieved from http://www.cs.cmu.edu/~CompThink/resources/TheLinkWing.pdf Accessed January 21, 2021

Denner, J., Werner, L., Campe, S., & Ortiz, E., (2014). Pair programming: Under what conditions is it advantageous for middle school students? Journal of Research on Technology in Education 46, 277–296. DOI: https://doi.org/10.1080/15391523.2014.888272

Department for Education. (2013). The National Curriculum in England, Framework Document. Retrieved from www.Education.Gov.Uk/Nationalcurriculum Accessed January 21, 2021

Dorn, B. and Guzdial, M., (2010, April). Learning on the job: characterizing the programming knowledge and learning strategies of web designers. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 703-712). DOI: https://doi.org/10.1145/1753326.1753430

Eli, J.A., Mohr-Schroeder, M.J. and Lee, C.W., (2011). Exploring mathematical connections of prospective middle-grades teachers through card-sorting tasks. Mathematics Education Research Journal, 23(3), p.297. DOI: https://doi.org/10.1007/s13394-011-0017-0

Fincher, S. and Tenenberg, J., (2005). Making sense of card sorting data. Expert Systems, 22(3), 89-93. DOI: https://doi.org/10.1111/j.1468-0394.2005.00299.x

Friedrichsen, P.M. and Dana, T.M., (2003). Using a card-sorting task to elicit and clarify science-teaching orientations. Journal of Science Teacher Education, 14(4), 291-309. DOI: https://doi.org/10.1023/B:JSTE.0000009551.37237.b3

Grover, S. & Pea, R., (2013). Computational thinking in K–12: A review of the state of the field. Educational researcher, 42(1), 38-43. DOI: https://doi.org/10.3102/0013189X12463051

Grover, S., Cooper, S., & Pea, R. (2014). Assessing computational learning in K-12. In Proceedings of the 2014 conference on Innovation & technology in computer science education (pp. 57–62). ACM, New York. DOI: https://doi.org/10.1145/2591708.2591713

Grover, S., Pea, R., & Cooper, S. (2015). Systems of assessments” for deeper learning of computational thinking in K-12. In Proceedings of the 2015 annual meeting of the American educational research association (pp. 15-20).

Grover, S., (2017). Assessing algorithmic and computational thinking in K-12: Lessons from a middle school classroom. In Emerging research, practice, and policy on computational thinking, 269-288. DOI: https://doi.org/10.1007/978-3-319-52691-1_17

Haines, S., Krach, M., Pustaka, A., Li, Q., & Richman, L. (2019). The Effects of Computational Thinking Professional Development on STEM Teachers’ Perceptions and Pedagogical Practices. Athens Journal of Sciences, 6 (2), 97-122.

Hattie, J. & Timperley, H., (2007). The power of feedback. Review of educational research, 77(1), 81-112. DOI: https://doi.org/10.3102/003465430298487

Hennissen, P., Beckers, H. and Moerkerke, G., (2017). Linking practice to theory in teacher education: A growth in cognitive structures. Teaching and Teacher Education, 63, 314-325. DOI: https://doi.org/10.1016/j.tate.2017.01.008

Kafai, Y. B., & Burke, Q. (2015). Constructionist Gaming: Understanding the Benefits of Making Games for Learning. Educational Psychologist, 50 (4), 313-334. DOI: https://doi.org/10.1080/00461520.2015.1124022

Kim, B., Kim, T., & Kim, J., (2013). Paper-and-pencil programming strategy toward computational thinking for non-majors: Design your solution. Journal of Educational Computing Research 49, 437–459. DOI: https://doi.org/10.2190/EC.49.4.b

Lu, J. J., & Fletcher, G. H. (2009). Thinking About Computational Thinking. ACM SIGCSE Bulletin, 41(1), 260-264. DOI: https://doi.org/10.1145/1539024.1508959

Meerbaum-Salant, O., Armoni, M., & Ben-Ari, M. (2013). Learning computer science concepts with scratch. Computer Science Education, 23(3), 239–264. DOI: https://doi.org/10.1080/08993408.2013.832022

Moreno-León, J., & Robles, G. (2015). Dr. Scratch: A web tool to automatically evaluate Scratch projects. In Proceedings of the Workshop in Primary and Secondary Computing Education (pp. 132–133). DOI: https://doi.org/10.1145/2818314.2818338

Mühling, A., Ruf, A., & Hubwieser, P. (2015). Design and first results of a psychometric test for measuring basic programming abilities. In Proceedings of the Workshop in Primary and Secondary Computing Education (pp. 2–10). DOI: https://doi.org/10.1145/2818314.2818320

Pagano, R. R. (2010). Understanding statistics in the behavioral sciences (9th ed.). Belmont, CA; Australia: Wadsworth Cengage Learning.

Papert, S. (1980). Mindstorms: Children, Computers and Powerful Ideas. NY: Basic Books.

Rich, P. J., Mason, S. L., & O'Leary, J. (2021). Measuring the effect of continuous professional development on elementary teachers’ self-efficacy to teach coding and computational thinking. Computers & Education, 168, 104196.

Román-González, M., Pérez-González, J. C., & Jiménez-Fernández, C. (2017). Which cognitive abilities underlie computational thinking? Criterion validity of the Computational Thinking Test. Computers in Human Behavior, 72, 678-691. DOI: https://doi.org/10.1016/j.chb.2016.08.047

Rugg, G. and McGeorge, P., (2005). The sorting techniques: a tutorial paper on card sorts, picture sorts and item sorts. Expert Systems, 22(3), pp.94-107. DOI: https://doi.org/10.1111/j.1468-0394.2005.00300.x

Selby, C., & Woollard, J. (2014). ‘Refining an Understanding of Computational Thinking.’ Author's Original, 1-23. Retrieved from https://Eprints.Soton.Ac.Uk/372410/1/372410understdct.Pdf Accessed January 21, 2021

Shute, V.J., Sun, C. & Asbell-Clarke, J., (2017). Demystifying computational thinking. Educational Research Review, 22, 42-158. DOI: https://doi.org/10.1016/j.edurev.2017.09.003

Spencer, D. (2009). Card sorting: Designing usable categories. Rosenfeld Media.

Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., et al., (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology 25 (1), 127–147. DOI: https://doi.org/10.1007/s10956-015-9581-5

Werner, L., Denner, J., Campe, S., & Kawamoto, D. C. (2012). The Fairy Performance Assessment: Measuring Computational Thinking in Middle School. In Proceedings of the 43rd ACM Technical Symposium on Computer Science Education, ACM, pp. 215-220. DOI: https://doi.org/10.1145/2157136.2157200

Werner, L., Denner, J., & Campe, S. (2014). Using computer game programming to teach computational thinking skills. Learning, education and games, 37.

Wiliam, D., & Thompson, M. (2008). Integrating assessment with learning: What will it take to make it work? Routledge.

Wing, J. (2010). Computational Thinking: What and Why? Retrieved from www.Cs.Cmu.Edu/~Compthink/Resources/Thelinkwing.Pdf

Yadav, A., Zhou, N., Mayfield, C., Hambrusch, S., & Korb, J. T. (2011, March). Introducing computational thinking in education courses. In Proceedings of the 42nd ACM technical symposium on Computer science education (pp. 465-470). DOI: https://doi.org/10.1145/1953163.1953297

Yadav, A., Mayfield, C., Zhou, N., Hambrusch, S., Korb, J. T., (2014). Computational thinking in elementary and secondary teacher education. ACM Transactions on Computing Education (TOCE) 14 (1), 1–16. DOI: https://doi.org/10.1145/2576872

Yadav, A., Krist, C., Good, J., & Caeli, E. N. (2018). Computational thinking in elementary classrooms: measuring teacher understanding of computational ideas for teaching science. Computer Science Education, 28(4), 371-400.

Published

2024-11-16

How to Cite

Allsop, Y., Kalelioglu, F., & Aslan Unlu, M. . (2024). Using Card Sorting Activity as a Strategy for Evaluating Students’ Learning of Computational Thinking Concepts. International Journal of Computer Science Education in Schools, 6(4). https://doi.org/10.21585/ijcses.v6i4.215