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Research Article Open Access

The effect of python programming language teaching on 7th grade students' programming self-efficacy skills

Feryad Doğuş Feryad Doğuş Corresponding Author Kırlı Secondary School, Ministry Of National Education, Ordu, Türkiye ORCID 0009-0005-7900-5270 View Profile , Yasin Özkan Yasin Özkan Department Of Computer Technologies, Zonguldak Bulent Ecevit University, Zonguldak, Türkiye ORCID 0000-0002-2029-0856 View Profile , Sibel Barın Özkan Sibel Barın Özkan Department Of Computer Technologies, Zonguldak Bulent Ecevit University, Zonguldak, Türkiye ORCID 0000-0003-1743-756X View Profile

Abstract

This study aimed to investigate the impact of teaching the Python programming language on the programming self-efficacy of 7th-grade students. A quantitative research design was employed, utilizing a one-group pretest-posttest model. The study sample consisted of 10 students enrolled in the 7th grade at a public school located in a rural district of northern Turkey during the spring semester of the 2023-2024 academic year. These students attended a school affiliated with the Ministry of National Education. The study group was selected using the convenience sampling method, a type of purposive sampling. Data for this research was collected using the Programming Self-Efficacy Scale for Secondary School Students, developed by Kukul, Gökçearslan, and Günbatar (2017). The collected data were analyzed using the Jamovi software. To assess the suitability of the data for normal distribution, skewness and kurtosis coefficients, as well as Shapiro-Wilk test values (a normality test), were examined, alongside an inspection of histogram plots. The results indicated that the data were normally distributed with respect to both research questions. For the first research question, a paired sample t-test was conducted to determine whether there was a statistically significant difference between the pre-test and post-test scores. The analysis revealed that Python instruction did not have a significant effect on the programming self-efficacy of the 7th-grade students. Regarding the second research question, the homogeneity of the data was assessed. Levene's test for equality of variances was performed, confirming that the assumption of homogeneity was met. Consequently, independent sample t-tests were conducted to examine the significance of the difference in pre-test and post-test scores based on gender. The results indicated no statistically significant difference in programming self-efficacy scores between male and female students.
Keywords: Python Programming education Programming self-efficacy

References

Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. In K. W. Spence & J. T. Spence (Eds.), The psychology of learning and motivation, (2), pp. 89-195. Academic Press. https://doi.org/10.1016/S0079-7421(08)60422-3

Bandura, A. (1997). Self-efficacy: The exercise of control. W.H. Freeman and Company.

Futschek, G. (2006). Algorithmic thinking: The key for understanding computer science. In International Conference on Informatics in Secondary Schools – Evolution and Perspectives (pp. 159-168). Springer. https://doi.org/10.1007/11915355_15

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

Guzdial, M. (2015). Learner-centered design of computing education: Research on computing for everyone. Synthesis Lectures on Human-Centered Informatics, 8(6), 1-165. https://doi.org/10.2200/S00684ED1V01Y201511HCI033

Kafai, Y. B., & Burke, Q. (2015). Connected code: Why children need to learn programming. MIT Press. https://doi.org/10.7551/mitpress/9992.001.0001

Kukul, V., Gökçearslan, Ş., & Günbatar, M. S. (2017). Programming self-efficacy scale for middle school students: Development, validity, and reliability. Educational Technology Theory and Practice, 7(1), 158-179.

Luxton-Reilly, A. (2016). Learning to program is easy. Proceedings of the 19th Australasian Computing Education Conference (ACE 2016), 160, 284-293. https://dl.acm.org/doi/10.1145/2899415.2899432

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. https://doi.org/10.1016/j.chb.2014.09.012

McMillan, J. H., & Schumacher, S. (2014). Research in education: Evidence-based inquiry (7th ed.). Pearson Higher Ed.

Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas. Basic Books, Inc.

Piaget, J. (1972). The principles of genetic epistemology. Routledge.

Piaget, J. (1972). The psychology of the child. Basic Books.

Sáez-López, J. M., Román-González, M., & Vázquez-Cano, E. (2016). Visual programming languages integrated across the curriculum in elementary school: A two year case study using “Scratch” in five schools. Computers & Education, 97, 129-141. https://doi.org/10.1016/j.compedu.2016.03.003

Schunk, D. H., & Pajares, F. (2009). Self-efficacy theory. In K. R. Wentzel & A. Wigfield (Eds.), Handbook of motivation at school (pp. 35-53). Routledge.

Shute, V. J., Sun, C., & Asbell-Clarke, J. (2017). Demystifying computational thinking. Educational Research Review, 22, 142-158. https://doi.org/10.1016/j.edurev.2017.09.003

Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press. https://doi.org/10.2307/j.ctvjf9vz4

Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35. https://doi.org/10.1145/1118178.111821