The effects of a progressive scaffolding approach on middle school students'computational thinking skills and self-efficacy
Pages 107 - 112
Abstract
Computational thinking (CT) is considered a necessary skill for the 21st century. Researchers have increasingly focused on how to effectively enhance students’ CT in programming courses. This study proposes a progressive scaffolding approach with flowcharts and visual programming codes applied to a visual programming course based on an open-source hardware platform to improve CT skills and self-efficacy in middle school students. Forty-five middle school students in grades 7 and 8 participated in this study. Both quantitative and qualitative data were collected by using CT tests, scales, and semi-structured interviews. A repeated measures analysis of variance (ANOVA) examined differences in CT skills and self-efficacy on the pre-test, mid-test, and post-test. The results indicated that the progressive scaffolding approach significantly improved middle school students’ CT skills and self-efficacy. These results reveal the effectiveness of the progressive scaffolding approach in improving the computational thinking of middle school students in a visual programming course with an open-source hardware platform, which helps to extend the design of progressive scaffolding.
References
[1]
Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35. https://doi.org/10.1145/1118178.1118215
[2]
Saidin, N. D., Khalid, F., Martin, R., Kuppusamy, Y., & Munusamy, N. A. (2021). Benefits and Challenges of Applying Computational Thinking in Education. International Journal of Information and Education Technology, 11(5), 248–254. https://doi.org/10.18178/ijiet.2021.11.5.1519
[3]
Hsu, T. C., Chang, S. C., & Hung, Y. T. (2018). How to learn and how to teach computational thinking: Suggestions based on a review of the literature. Computers & Education, 126, 296–310. https://doi.org/10.1016/j.compedu.2018.07.004
[4]
Xu, E., Wang, W., & Wang, Q. (2022). A meta-analysis of the effectiveness of programming teaching in promoting K-12 students’ computational thinking. Education and Information Technologies, 28(6), 6619–6644. https://doi.org/10.1007/s10639-022-11445-2
[5]
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
[6]
Yang, K., Liu, X., & Chen, G. (2020). The Influence of Robots on Students’ Computational Thinking: A Literature Review. International Journal of Information and Education Technology, 10(8), 627-631. https://doi.org/10.18178/ijiet.2020.10.8.1435
[7]
Florez, F., Casallas, R., Hern ́ andez, 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. https://doi.org/10.3102/0034654317710096.
[8]
Chen, C. H., Liu, T. K., & Huang, K. (2021). Scaffolding vocational high school students’ computational thinking with cognitive and metacognitive prompts in learning about programmable logic controllers. Journal of Research on Technology in Education, 55(3), 527–544. https://doi.org/10.1080/15391523.2021.1983894
[9]
Andrzejewska, M., & Stolinska, A. (2022). Do Structured Flowcharts Outperform Pseudocode? Evidence From Eye Movements. IEEE Access, 10, 132965–132975. https://doi.org/10.1109/access.2022.3230981
[10]
Peng, J., Wang, M., Sampson, D., & Van Merriënboer, J. J. G. (2019). Using a visualisation-based and progressive learning environment as a cognitive tool for learning computer programming. Australasian Journal of Educational Technology, 35(2). https://doi.org/10.14742/ajet.4676
[11]
Zhang, J. H., Meng, B., Zou, L. C., Zhu, Y., & Hwang, G. J. (2021). Progressive flowchart development scaffolding to improve university students’ computational thinking and programming self-efficacy. Interactive Learning Environments, 1-18. https://doi.org/10.1080/10494820.2021.1943687
[12]
Román-González, M., Pérez-González, J., Moreno-León, J., & Robles, G. (2018). Extending the nomological network of computational thinking with non-cognitive factors. Computers in Human Behavior, 80, 441–459.
[13]
Brennan, K., & Resnick, M. (2012). New frameworks for studying and assessing the development of computational thinking. Proceedings of the 2012 Annual Meeting of the American Educational Research Association (pp. 1–25), Vancouver, Canada.
[14]
Merino-Armero, J. M., González-Calero, J. A., & Cózar-Gutiérrez, R. (2021). Computational thinking in K-12 education. An insight through meta-analysis. Journal of Research on Technology in Education. https://doi.org/10.1080/15391523.2020.1870250
[15]
Ezeamuzie, N. O., & Leung, J. S. C. (2021, July 27). Computational Thinking Through an Empirical Lens: A Systematic Review of Literature. Journal of Educational Computing Research, 60(2), 481–511. https://doi.org/10.1177/07356331211033158
[16]
CSTA, & ISTE (2011). Operational Definition of Computational Thinking for K-12 Education. http://www.iste.org/docs/pdfs/Operational-Defnition-of-Computational-Thinking.pdf. Accessed 2 Aug 2019.
[17]
Kalelioglu, F., Gülbahar, Y., & Kukul, V. (2016). A framework for computational thinking based on a systematic research review. Baltic Journal of Modern Computing, 4(3), 583–596.
[18]
Spangsberg, T. H., & Brynskov, M. (2018). The Nature of Computational Thinking in Computing Education. International Journal of Information and Education Technology, 8(10), 742–747. https://doi.org/10.18178/ijiet.2018.8.10.1132
[19]
Wang, C., Shen, J., & Chao, J. (2022). Integrating Computational Thinking in STEM Education: A Literature Review. International Journal of Science and Mathematics Education, 20(8), 1949–1972. https://doi.org/10.1007/s10763-021-10227-5
[20]
Yin, Y., Hadad, R., Tang, X., & Lin, Q. (2020). Improving and assessing computational thinking in maker activities: The integration with physics and engineering learning. Journal of Science Education and Technology, 29(2), 189–214.
[21]
Harrison, A., Hulse, T., Manzo, D., Micciolo, M., Ottmar, E., & Arroyo, I. (2018). Computational thinking through game creation in STEM classrooms. Paper presented at the 19th International Conference on Artificial Intelligence in Education, 2018, London, UK.
[22]
Korkmaz, Z., Çakir, R., & Özden, M. Y. (2017). A validity and reliability study of the computational thinking scales (CTS). Computers in Human Behavior, 72, 558-569. https://doi.org/10.1016/j.chb.2017.01.005
[23]
Ma, H., Zhao, M., Wang, H. Promoting pupils’ computational thinking skills and self-efficacy: a problem-solving instructional approach. Education Tech Research Dev 69, 1599–1616 (2021). https://doi.org/10.1007/s11423-021-10016-5
[24]
Wood, D., Bruner, J. S., & Ross, G. (1976). The role of tutoring in problem solving. Journal of Child Psychology and Psychiatry, 17(2), 89–100. https://doi.org/10.1111/j.1469-7610.1976.tb00381.x
[25]
Sun, J. C. Y., & Hsu, K. Y. C. (2019). A smart eye-tracking feedback scaffolding approach to improving students’ learning self-efficacy and performance in a C programming course. Computers in Human Behavior, 95, 66–72. https://doi.org/10.1016/j.chb.2019.01.036
[26]
Tikva, C., & Tambouris, E. (2023). The effect of scaffolding programming games and attitudes towards programming on the development of Computational Thinking. Education and Information Technologies, 28(6), 6845-6867. https://doi.org/10.1007/s10639-022-11465-y
[27]
Chen, C. H., Hwang, G. J., & Tsai, C. H. (2014). A Progressive Prompting Approach to Conducting Context-Aware Learning Activities for Natural Science Courses. Interacting With Computers, 26(4), 348–359. https://doi.org/10.1093/iwc/iwu004
[28]
Shuell T. J. (1990). Phases of meaningful learning. Review of Educational Research, 60(4), 531–547.
[29]
Zhong, B., & Si, Q. (2021). Troubleshooting to Learn via Scaffolds: Effect on Students’ Ability and Cognitive Load in a Robotics Course. Journal of Educational Computing Research, 59(1), 95–118. https://doi.org/10.1177/0735633120951871
[30]
Korkmaz, Z., & Bai, X. (2019). Adapting Computational Thinking Scale (CTS) for Chinese High School Students and Their Thinking Scale Skills Level. Participatory Educational Research, 6(1), 10–26. https://doi.org/10.17275/per.19.2.6.1
[31]
Chong, S. L., & Choy, M. (2004). Towards a progressive learning environment for programming courses. In New Horizon in web-based learning, 200-205. https://doi.org/10.1142/9789812702494_0024
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September 2023
532 pages
ISBN:9798400709111
DOI:10.1145/3629296
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Published: 15 January 2024
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ICETC 2023
ICETC 2023: The 15th International Conference on Education Technology and Computers
September 26 - 28, 2023
Barcelona, Spain
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