Preservice Teachers’ Use of Computational Thinking to Facilitate Inquiry-based Practical Work in Multiple-deprived Classrooms

Maria Tsakeni

doi:10.29333/ejmste/9574

Full Text (PDF)

Maria Tsakeni ¹ ^*

More Detail

¹ University of the Free State, SOUTH AFRICA^* Corresponding Author

Abstract

Inquiry-based practical work (IBPW) is one of the innovative instructional strategies in science education. Science teacher preparation programmes play a role in preparing preservice teachers to facilitate IBPW in classrooms located in different school settings, including multiple-deprived classrooms. The adverse conditions against the successful implementation of IBPW found in multiple-deprived classrooms provide problems that preservice teachers will have to solve in their future classrooms. It is against this background that this study explored how preservice science teachers used computational thinking as a problem-solving strategy when facilitating IBPW in multiple-deprived classrooms. Using a single-case exploratory study, the experiences of 16 preservice physical sciences teachers were elicited through lesson planning, simulated teaching, and reflection. The data collected were analysed through thematic-content-analysis techniques. Findings indicate how through the use of computational thinking, participants were able to solve problems that had the potential to inhibit the implementation of IBPW.

Keywords

computational thinking
inquiry-based practical work
multiple-deprived classrooms
physical sciences
preservice teachers

License

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

EURASIA J Math Sci Tech Ed, 2021, Volume 17, Issue 1, Article No: em1933

https://doi.org/10.29333/ejmste/9574

Publication date: 16 Jan 2021

Article Views: 2316

Article Downloads: 1469

Open Access Disclosures References How to cite this article

Disclosure

Declaration of Conflict of Interest: No conflict of interest is declared by author(s).

Data sharing statement: Data supporting the findings and conclusions are available upon request from the corresponding author(s).

References

Akuma, F. V., & Callaghan, R. (2019). Teaching practices linked to the implementation of inquiry‐based practical work in certain science classrooms. Journal of Research in Science Teaching, 56(1), 64-90. https://doi.org/10.1002/tea.21469
Andriessen, D. (2007). Combining design-based research and action research to test management solutions. Paper presented at the 7th World Congress Action Learning, Action Research and Process Management, Groningen, 22-24 August, pp. 1-8.
Cheng, P. Y., Talib, O., & Othman, A. (2016). Science teaching: Perceptions, attitudes and instructional practices. Jurnal Pendidikan Sains and Matematik Malaysia, 6(2), 1-17. Retrieved from https://ejournal.upsi.edu.my/index.php/JPSMM/article/view/2163
Chikoko, V. (2018). The nature of the deprived context: Leadership that works in deprived school contexts of South Africa. Nova Science Publishers.
Collato, D. C., Dresch, A., Lacerda, D. P., & Bentz, I. G. (2018). Is action design research indeed necessary? Analysis of synergies between action research and design science research. Syst. Pract. Action Research, 31, 239-267. https://doi.org/10.1007/s11213-017-9424-9
Djambong, T., & Freiman, V. (2016). Task-based assessment of students’ computational thinking skills developed through visual programming or tangible coding environments. 13th International Conference on Cognition and Exploratory Learning in Digital Age (CELDA), Mannheim, Germany, 28-30 October, pp. 41-51.
Dunn, J., & Ramnarain, U. (2020). The effect of simulation-supported inquiry on South African natural sciences learners’ understanding of atomic and molecular structures. Education Science, 10(10), 280. https://doi.org/10.3390/educsci10100280
Hestness, E., Ketelhut, D. J., McGinnis, J. R., & Plane, J. (2018). Professional knowledge building within an elementary teacher professional development experience on computational thinking in science education. Journal of Technology and Teacher Education, 26(3), 411-435. Retrieved from https://www.learntechlib.org/primary/p/181431
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. https://doi.org/10.1016/j.procs.2012.04.056
Kidman, G. (2012). Australia at the crossroads: A review of school science practical work. Eurasia Journal of Mathematics, Science and Technology Education, 8(1), 35-47. https://doi.org/10.12973/eurasia.2012.815a
Kim, M., & Tan, A. L. (2011). Rethinking difficulties of teaching inquiry‐based practical work: Stories from elementary pre‐service teachers. International Journal of Science Education 33(4), 465-486. https://doi.org/10.1080/09500691003639913
Magnusson, S. J., Borko, H., & Krajcik, J. S. (1999). Nature, sources, and development of pedagogical content knowledge for science teaching. In J. Gess-Newsome & N. Lederman (Eds.), Examining pedagogical content knowledge (pp. 95-132). Kluwer Press. https://doi.org/10.1007/0-306-47217-1_4
Maringe, F., Masinire, A., & Nkambule, T. (2015). Distinctive features of schools in multiple deprived communities in South Africa: Implications for policy and leadership. Educational Management Administration and Leadership, 43(3), 363-385. https://doi.org/10.1177/1741143215570303
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. https://doi.org/10.14742/ajet.3521
Mulhall, P. J., Berry, A., & Loughran, J. (2003). Frameworks for representing science teachers’ pedagogical content. Asia-Pacific Forum in Science Learning and Teaching, 4(2), Article 2, 1‑25.
Ndlovu, M., & Meyer, D. (2019). Readiness of teachers to teach mathematics with technology: A case study of a school in Gauteng. The 63^rd ICET World Assembly, Johannesburg, pp. 188‑197.
Noble, M., Zembe, W., Wright, G., & Avenell, D. (2013). Multiple deprivation and income poverty at small area level in South Africa in 2011. SASPRI.
Printy, S. M. (2010). How principals influence instructional practice: Leadership levers. In W.K. Hoy & M. DiPaola (Eds.), Analyzing social contexts: Influences of principals and teachers in service of students (pp. 71-102). Information Age Publishing.
Ramnarain, U., & Hlatswayo, M. (2018). Teacher beliefs and attitudes about inquiry-based learning in a rural school district in South Africa. South African Journal of Education, 38(1), 1-10. https://doi.org/10.15700/saje.v38n1a1431
Reid, N., & Shah, I. (2007). The role of laboratory work in university chemistry. Chemistry Education Research and Practice, 8(2), 172-185. https://doi.org/10.1039/B5RP90026C
Shulman, L. (1987). Knowledge and teaching: Foundations of the new reform. Harvard Educational Review, 57(1), 1-22. https://doi.org/10.17763/haer.57.1.j463w79r56455411
Thanh, N. C., & Thanh, T. T. L. (2015). The interconnection between interpretivist paradigm and qualitative methods in education. American Journal of Educational Science, 1(2), 2015, 24-27.
Tsakeni, M. (2018). Inquiry-based practical work in physical sciences: Equitable access and social justice issues. Issues in Educational Research, 28(1), 187-201. Retrieved from http://www.iier.org.au/iier28/tsakeni.pdf
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. https://doi.org/10.1007/s10956-015-9581-5
Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35. https://doi.org/10.1145/1118178.1118215
Wing, J. M. (2017). Computational thinking’s influence on research and education for all. Italian Journal of Educational Technology, 25(2), 7-14. https://doi.org/10.17471/2499-4324/922
Yadav, A., Mayfield, C., Zhou, N., Hambrusch, S., & Korb, J.T. (2014). Computational thinking in elementary and secondary teacher education. ACM Trans. Comput. Educ., 14(1), Article 5. https://doi.org/10.1145/2576872
Yadav, A., Stephenson, C., & Hong, H. (2017). Computational thinking for teacher education. Communications of the ACM, 60(4), 55-62. https://doi.org/10.1145/2994591

How to cite this article

APA

Tsakeni, M. (2021). Preservice Teachers’ Use of Computational Thinking to Facilitate Inquiry-based Practical Work in Multiple-deprived Classrooms. Eurasia Journal of Mathematics, Science and Technology Education, 17(1), em1933. https://doi.org/10.29333/ejmste/9574

Vancouver

Tsakeni M. Preservice Teachers’ Use of Computational Thinking to Facilitate Inquiry-based Practical Work in Multiple-deprived Classrooms. EURASIA J Math Sci Tech Ed. 2021;17(1):em1933. https://doi.org/10.29333/ejmste/9574

AMA

Tsakeni M. Preservice Teachers’ Use of Computational Thinking to Facilitate Inquiry-based Practical Work in Multiple-deprived Classrooms. EURASIA J Math Sci Tech Ed. 2021;17(1), em1933. https://doi.org/10.29333/ejmste/9574

Chicago

Tsakeni, Maria. "Preservice Teachers’ Use of Computational Thinking to Facilitate Inquiry-based Practical Work in Multiple-deprived Classrooms". Eurasia Journal of Mathematics, Science and Technology Education 2021 17 no. 1 (2021): em1933. https://doi.org/10.29333/ejmste/9574

Harvard

Tsakeni, M. (2021). Preservice Teachers’ Use of Computational Thinking to Facilitate Inquiry-based Practical Work in Multiple-deprived Classrooms. Eurasia Journal of Mathematics, Science and Technology Education, 17(1), em1933. https://doi.org/10.29333/ejmste/9574

MLA

Tsakeni, Maria "Preservice Teachers’ Use of Computational Thinking to Facilitate Inquiry-based Practical Work in Multiple-deprived Classrooms". Eurasia Journal of Mathematics, Science and Technology Education, vol. 17, no. 1, 2021, em1933. https://doi.org/10.29333/ejmste/9574