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Integration of Computational Thinking in the Elementary School Curriculum: Teacher Perspectives and Experiences
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- October 2, 2024
Abstract
With the increasing need for computational thinking skills in the digital era, it is important for basic education to start introducing this concept from an early age. This research aims to explore teachers' perspectives and experiences in integrating computational thinking (CT) into the elementary school curriculum. This research uses a mixed approach (mix method), data was collected through questionnaires and distributed to 130 teachers and using in-depth interviews with teachers in several elementary schools. The research results show that most teachers understand the importance of CT and feel that its integration can enrich the learning process. However, there are various challenges faced, including limited resources, lack of training, and resistance to curriculum change. Despite this, some teachers have successfully implemented CT in a variety of subjects through the use of problem-based projects and digital tools. This research concludes that greater support from schools and the provision of ongoing training is needed to optimize the integration of CT in the elementary school curriculum. It is hoped that these findings will provide insight for policy makers and educators to design more effective strategies in developing computational thinking skills at the basic education level.
References
Angeli, C., Voogt, J., Fluck, A., Webb, M., Cox, M., Malyn-Smith, J., & Zagami, J. (2016). computational thinking curriculum framework: Implications for teacher knowledge. Educational Technology & Society, 19(3), 47–57. http://www.jstor.org/stable/jeductechsoci.19.3.47.
Aranda, G., & Ferguson, J. (2018). Unplugged programming: The future of teaching computational thinking? Pedagogika, 63(3), 279–292. https://doi.org/10.14712/23362189.2018.859
Brackmann, C., Román-González, M., Robles, G., Moreno-León, J., Casali, A., & Barone, D. (2017). Development of computational thinking skills through unplugged activities in primary school. Proceedings of the 12th Workshop on Primary and Secondary Computing Education, Netherlands, 65–72. https://doi.org/10.1145/3137065.3137069
Chalmers, C. (2018). Robotics and computational thinking in primary school. International Journal of Child-Computer Interaction, 17, 93–100. https://doi.org/10.1016/j.ijcci.2018.06.005
Chen, G., Shen, J., Barth-Cohen, L., Jiang, S., Huang, X., & Eltoukhy, M. (2017). Assessing elementary students’ computational thinking in everyday reasoning and robotics programming. Computers & Education, 109, 162–175. https://doi.org/10.1016/j.compedu.2017.03.001
Chen, J., Wang, M., Kirschner, P., & Tsai, C. (2018). The role of collaboration, computer use, learning environments, and supporting strategies in CSCL: A meta-analysis. Review of Educational Research, 88(6), 162–175. https://doi.org/10.3102/0034654318791584
Chi, M., Kang, S., & Yaghmourian, D. (2017). Why students learn more from dialogue- than monologue-videos: Analyses of peer interactions. Journal of the Learning Sciences, 26(1), 10–50. https://doi.org/10.1080/10508406.2016.1204546
Chi, M., & Wylie, R. (2014). The ICAP framework: Linking cognitive engagement to active learn- ing outcomes. Educational Psychologist, 49, 219–243. https://doi.org/10.1080/00461520.2014.965823
Conde, M., Fernández-Llamas, C., Rodríguez-Sedano, F., Guerrero-Higueras, Á., & García- Peñalvo, F. (2017). Promoting computationalthinking in K-12 students by applying unplugged methods and robotics. Proceedings of the 5th International Conference on TechnologicalEco- Systems for Enhancing Multiculturality, 1–6. https://doi.org/10.1145/3144826. 3145355
de Araujo, A., Andrade, W., & Serey Guerrero, D. (2016). A systematic mapping study on assessing computational thinking abilities. Proceedings of the 2016 IEEE Frontiers in Education Conference (FIE), 1–9. https://doi.org/10.1109/FIE.2016.7757678
Durak, H. Y. (2020). The effects of using different tools in programming teaching of secondary school students on engagement, computational thinking and reflective thinking skills for problem solving. Technology, Knowledge and Learning, 25(1), 179–195. https://doi.org/10.1007/s10758-018-9391-y
Evans, T., Kensington-Miller, B., & Novak, J. (2021). No TitleEffectiveness, efficiency, engagement: Mapping the impact of pre-lecture quizzes on educational exchange. Australasian Journal of Educational Technology, 37(1), 163–177. https://doi.org/10.14742/ajet.6258
Fredricks, J., Filsecker, M., & Lawson, M. (2016). SE, context, and adjustment: Addressing defi- nitional, measurement, and methodological issues. Learning & Instruction, 43(1), 1–4. https://doi.org/10.1016/j.learninstruc.2016.02.002
Gao, X., & Hew, K. (2021). Toward a 5E-based flipped classroom model for teaching computational thinking in elementary school: Effects on student computational thinking and problem-solving performance. Journal of Educational Computing Research, 59(1), 1–32. https://doi.org/10.1177/07356 331211037757
Henderson, B. (2019). Beyond “active” learning: how the ICAP framework permits more acute examina- tion of the popular peer instruction pedagogy. Harvard Educational Review, 89(4), 611–635. https://doi.org/10.17763/1943-5045-89.4.611.
Kafai, Y., & Vasudevan, V. (2015). Constructionist gaming beyondthe screen: middle school stu- dents’ crafting and computing of touchpads, boardgames, and controllers. In Proceedings of the Workshop in Primary AndSecondary Computing Education (WiPSCE ’15), 49–54. https://doi.org/10.1145/2818314.2818334
Kotsopoulos, D., Floyd, L., Khan, S., Namukasa, I., Somanath, S., & Weber, J. (2017). A pedagogical framework for computational thinking. Digital Experiences in Mathematics Education, 3(2), 154–171. https://doi.org/10.1007/s40751-017-0031-2
Kuo, W., & Hsu, T. (2020). Learning computational thinking without a computer: How computational participation happens in a computational thinking board game. Asia-Pacific Education Research, 29(1), 67–83. https://doi.org/10.1007/s40299-019-00479-9
Lee, S., Shih, M., Liang, J., & Tseng, Y. (2021). Investigating learners’ engagement and science learning outcomes in different designs of participatory simulated games. British Journal of Educational Technology, 52(3), 1197–1214. https://doi.org/10.1111/bjet.13067
Lin, H., Lee, M., Liang, J., Chang, H., Huang, P., & Tsai, C. (2020). A review of using partial least square structural equation modeling in e-learning research. British Journal of Educa- Tional Technology, 51(4), 1354–1372. https://doi.org/10.1111/bjet.12890
Lindberg, R., Laine, T., & Haaranen, L. (2019). Gamifying programming education in K-12: A review of programming curricula in seven countries and programming games. British Journal of Educational Technology, 50(4), 1979–1995. https://doi.org/10.1111/bjet.12685
Looi, C., How, M., Wu, L., Seow, P., & Liu, L. (2018). Analysis of linkages between an unplugged activity and the development of computational thinking. Computer Science Education, 28(3), 255–279. https://doi.org/10.1080/08993408.2018.1533297
Mladenović, M., Boljat, I., & Žanko, Ž. (2018). Comparing loops misconceptions in block-based and text-based programming languages at the K-12 level. Education and Information Technologies, 23(4), 1483–1500. https://doi.org/10.1007/s10639-017-9673-3
Nagy, J. (2018). Evaluation of online video usage and learning satisfaction: an extension of the technol- ogy acceptance model. International Review of Research in Open and Distributed Learning, 19(1), 160–185. https://doi.org/10.19173/irrodl.v19i1.2886
Papadakis, S., Kalogiannakis, M., & Zaranis, N. (2016). Developing fundamental programming concepts and computational thinking with ScratchJr in preschool education: A case study. International Journal of Mobile Learning and Organisation, 10(3), 187–202. https://doi.org/10.1504/IJMLO.2016. 077867
Rodriguez, B., Rader, C., & Camp, T. (2016). Using studentperformance to assess CS unplugged activi- ties in a classroom environment. Proceedings of the 2016 ACM Conference on Innovation and Technologyin Computer Science Education (ITiCSE ’16), Arequipa, Peru, 95–100. https://doi.org/10.1145/2899415.2899465
Saxena, A., Lo, C., Hew, K., & Wong, G. (2019). Designing unplugged and plugged activities to cultivate computational thinking: An exploratory study in early childhood education. Asia Pacific Education Researcher, 29(5), 55–66. https://doi.org/10.1007/s40299-019-00478-w
Sharma, K., Papavlasopoulou, S., & Giannakos, M. (2019). Coding games and robots to enhance computational thinking: How collaboration and engagement moderate children’s attitudes? International Journal of Child-Computer Interaction, 21(5), 65–76. https://doi.org/10.1016/j.ijcci.2019.04.004
Shigen, S., & Yugo, H. (2020). Prompting learnerlearner collaborative learning for deeper interaction: Conversational analysis based onthe ICAP framework. Proceedings of the 28th International Conferenceon Computers in Education, 1–6. https://apsce.net/icce/icce2020/proceedings/paper_156.pdf
Sun, L., Hu, L., Zhou, D., & Yang, W. (2022). Evaluation and developmental suggestions on undergraduates’ computational thinking: a theoretical framework guided by Marzano’s new taxonomy. Interactive Learning Environments, 1–23. https://doi.org/10.1080/10494820.2022.2042311
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