A Qualitative Case Study: Pre-service Teachers as Novice Programmers

Year 2024, , 292 - 318, 21.03.2024

Burcu Şener , Duygu Umutlu

https://doi.org/10.18009/jcer.1435182

Abstract

To meet the needs of 21st-century learners in today’s classrooms, it is needed that teachers be familiar with programming and computational thinking. Particularly, subject-area pre-service teachers should be exposed to programming instruction in their teacher education programs. This case study including three participants aims to explore the process of pre-service teachers’ learning of programming while completing CT-oriented tasks through observations and interviews in a 14-week educational technology course at a public university in Turkey. The findings demonstrate that pre-service teachers, being novice programmers, prefer contextualized, structured and visually well-designed programming tasks. They use various strategies to face challenges, and the effort they put into dealing with these challenges enables them to produce higher-quality programs. Accordingly, implications for further research are also discussed in this study.

Keywords

Computer science education, programming skills, teacher education, computational thinking

Ethical Statement

Name of the board that carries out ethical assessment: Boğaziçi University Social and Humanities Scientific Research and Publication Ethics Board The date and number of the ethical assessment decision: 24.01.2023-109746

References

• Albayrak, E., & Ozden, Ş. Y. (2021). Improvement of pre-service teachers’ computational thinking skills through an educational technology course. Journal of Individual Differences in Education, 3(2), 97-112.
• Bal, I. A., Alvarado–Albertorio, F., Marcelle, P., & Oaks–Garcia, C. T. (2022). Pre–service teachers computational thinking (CT) and pedagogical growth in a micro–credential: A mixed methods study. TechTrends, 66(3), 468-482.
• Bers, M. U. (2019). Coding as another language: A pedagogical approach for teaching computer science in early childhood. Journal of Computers in Education, 6(4), 499–528.
• Brennan, K., & Resnick, M. (2012, April). 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 (Vol. 1, p. 25).
• Buitrago Flórez, F., Casallas, R., Hernández, M., Reyes, A., Restrepo, S., & Danies, G. (2017). Changing a generation’s way of thinking: Teaching computational thinking through programming. Review of Educational Research, 87(4), 834-860.
• Butler, D., & Leahy, M. (2021). Developing preservice teachers' understanding of computational thinking: A constructionist approach. British Journal of Educational Technology, 52(3), 1060-1077.
• Cooper, J.E., Brandon, P.R., & Lindberg, M.A. (1998). Evaluators’ use of peer debriefing: Three impressionist tales. Qualitative Inquiry, 4(2), 265-279.
• Creative Computing Lab (2021). Getting unstuck. Harvard Graduate School of Education. Retrieved from https://gettingunstuck.gse.harvard.edu/
• Creswell, J. W. (2013). Qualitative inquiry and research design: Choosing among five approaches (3rd ed.). SAGE Publications.
• Cutumisu, M., Adams, C., Glanfield, F., Yuen, C., & Lu, C. (2021). Using Structural Equation Modeling to Examine the Relationship Between Preservice Teachers’ Computational Thinking Attitudes and Skills. IEEE Transactions on Education, 65(2), 177-183.
• Çiftçi, A., & Topçu, M. S. (2022). Improving early childhood pre-service teachers’ computational thinking teaching self-efficacy beliefs in a STEM course. Research in Science & Technological Education, 41(4), 1215-1241.
• Çoklar, A., N. & Akçay, A. (2018). Evaluating programming self-efficacy in the context of inquiry skills and problem-solving skills: A perspective from teacher education. World Journal on Educational Technology: Current Issues. 10(3), 153-164.
• Denning, P. J. (2017). Remaining trouble spots with computational thinking. Communications of the ACM, 60(6), 33-39.
• Dong, Y., Marwan, S., Catete, V., Price, T., & Barnes, T. (2019, February). Defining tinkering behavior in open-ended block-based programming assignments. In Proceedings of the 50th ACM Technical Symposium on Computer Science Education (pp. 1204-1210).
• Fagerlund, J., Häkkinen, P., Vesisenaho, M., & Viiri, J. (2021). Computational thinking in programming with Scratch in primary schools: A systematic review. Computer Applications in Engineering Education, 29(1), 12-28.
• Flyvbjerg, B. (2011). Case study. In N. K. Denzin & Y. S. Lincoln (Eds.), The Sage handbook of qualitative research (1st ed., p. 301-316). Sage Publications.
• Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field. Educational Researcher, 42(1), 38-43.
• Hanbay-Tiryaki, S., & Balaman, F. (2021). Açık kaynak kodlu yazılımlardan scratch, arduino ve python kullanımı hakkında öğrenci görüşleri. Journal of Computer and Education Research, 9(18), 831-852. https://doi.org/10.18009/jcer.938706
• Ilic, U. (2021). The impact of scratch-assisted instruction on computational thinking (ct) skills of pre-service teachers. International Journal of Research in Education and Science, 7(2), 426-444.
• Instefjord, E. J., & Munthe, E. (2017). Educating digitally competent teachers: A study of integration of professional digital competence in teacher education. Teaching and Teacher Education, 67, 37-45.
• ISTE (2016). ISTE standards for students. Retrieved from https://www.iste.org/standards/standards/for-students-2016
• Jin, H. Y., & Cutumisu, M. (2023). Predicting pre-service teachers’ computational thinking skills using machine learning classifiers. Education and Information Technologies, 28, 11447–11467.
• Kafai, Y., & Burke, Q. (2013). Computer programming goes back to school. Phi Delta Kappan, 95(1), 61–65. https://doi.org/10.1177/003172171309500111
• Kapur, M. (2015). Learning from productive failure. Learning: Research and Practice, 1(1), 51–65.
• Kaya, E., Yesilyurt, E., Newley, A., & Deniz, H. (2019). Examining the impact of a computational thinking intervention on pre-service elementary science teachers’ computational thinking teaching efficacy beliefs, interest and confidence. Journal of Computers in Mathematics and Science Teaching, 38(4), 385-392.
• Kazimoglu, C., Kiernan, M., Bacon, L., & MacKinnon, L. (2012). Learning programming at the computational thinking level via digital game-play. Procedia Computer Science, 9, 522-531.
• Klahr, D., & Nigam, M. (2004). The equivalence of learning paths in early science instruction: Effects of direct instruction and discovery learning. Psychological Science, 15(10), 661–667.
• Lee, D. M. C., Rodrigo, M. M. T., Baker, R. S. D., Sugay, J. O., & Coronel, A. (2011). Exploring the relationship between novice programmer confusion and achievement. In Affective Computing and Intelligent Interaction: 4th International Conference, ACII 2011, Memphis, TN, USA, October 9–12, Proceedings, Part I 4 (pp. 175-184). Springer Berlin Heidelberg.
• Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Sage Publications.
• Lye, S. Y., & Koh, J. H. L. (2014). Review on teaching and learning of computational thinking through programming: What is next for K-12?. Computers in Human Behavior,41, 51-61.
• Maloney, J., Burd, L., Kafai, Y., Rusk, N., Silverman, B., & Resnick, M. (2004). Scratch: A sneak preview [Conference proceeding]. In Proceedings of Second International Conference on Creating, Connecting and Collaborating through Computing. (pp. 104-109). IEEE.
• Merriam, S. B. (2009). Qualitative research: A guide to design and implementation. Jossey-Bass.
• Miyake, N., & Kirschner, P. A. (2014). The social and interactive dimensions of collaborative learning. In K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (pp. 418-438). Cambridge.
• Mouza, C., Yang, H., Pan, Y. C., Ozden, S. Y., & Pollock, L. (2017). Resetting educational technology coursework for pre-service teachers: A computational thinking approach to the development of technological pedagogical content knowledge (TPACK). Australasian Journal of Educational Technology, 33(3), 61-76.
• Mugayitoglu, B. (2016). Attitudes of pre-service teachers toward computational thinking in education. [Doctoral Dissertation, Duquesne University].
• OpenAI. (2022). Whisper [Automatic speech recognition system]. https://openai.com/research/whisper
• Piedade, J., Dorotea, N., Pedro, A., & Matos, J. F. (2020). On teaching programming fundamentals and computational thinking with educational robotics: A didactic experience with pre-service teachers. Education Sciences, 10(9), 214.
• Qualls, J. A., & Sherrell, L. B. (2010). Why computational thinking should be integrated into the curriculum. Journal of Computing Sciences in Colleges, 25(5), 66-71.
• Resnick, M., & Rosenbaum, E. (2013). Designing for tinkerability. In M. Honey (Ed.), Design, make, play: Growing the next generation of STEM innovators (pp. 163-181). Routledge.
• Saldana, J. (2013). The coding manual for qualitative researchers (2nd ed.). Sage.
• Umutlu, D. (2022). An exploratory study of pre-service teachers’ computational thinking and programming skills. Journal of Research on Technology in Education, 54(5), 754-768.
• VERBI Software. (2022). MAXQDA [Computer software]. https://www.maxqda.com/
• Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
• Wakil, K., Khdir, S., Sabir, L., & Nawzad, L. (2019). Student ability for learning computer programming languages in primary schools. International e-Journal of Educational Studies, 3(6), 109-115.
• Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35.
• Yadav, A., Hong, H., & Stephenson, C. (2016). Computational thinking for all: Pedagogical approaches to embedding 21st century problem solving in K-12 classrooms. TechTrends, 60(6), 565–568. https://doi.org/10.1007/s11528-016-0087-7
• 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.
• Yin, R. K. (2009). Case study research: Design and methods (5th ed.). SAGE Publications.