The Effect of Computational Thinking and Gender on Social Problem Solving Learning Outcomes
Abstract
Objective: to see the relationship between students level of computational thinking (CT) on learning outcomes in solving social problems. Metode: using descriptive verification method with advanced analysis of K-Means clustering. Finding: Male and female learning outcomes are significantly different, where female students on average have higher learning outcomes. CT Men and Women there is no significant difference. There is a significant relationship between CT variables and learning outcomes to solve problems. The results of the K-Means analysis showed that Cluster 3 was a group of women with moderate CT levels and high learning outcomes, while cluster 4 was a group of men with moderate CT levels and moderate learning outcomes. Consclusion: female students have higher learning outcomes than male students; there is no significant relationship between CT level and gender and the results of the K-Mean clustering analysis found 8 clusters.
Keywords: computational thinking, gender, learning outcomes.
Abstrak: Pengaruh Computational Thinking dan Gender Terhadap Hasil Belajar Pemecahan Masalah Sosial. Tujuan: melihat hubungan antara tingkat computational thinking (CT) mahasiswa terhadap hasil belajar memecahkan masalah sosial. Metode: menggunakan metode deskriptif verifikatif dengan analisis lanjutan clustering K-Means. Temuan: Hasil belajar Pria dan Wanita berbeda secara signifikan, di mana mahasiswa wanita rata-rata memiliki hasil belajar lebih tinggi. CT Pria dan Wanita tidak terdapat perbedaan yang bermakna. Terdapat hubungan signifikan antara variabel CT dengan hasil belajar memecahkan masalah. Hasil analisis K-Means didapatkan Cluster 3 merupakan kelompok wanita dengan tingkat CT sedang dan hasil belajar tinggi, sedangkan cluster 4 merupakan kelompok pria dengan tingkat CT sedang dan hasil belajar sedang. Kesimpulan: mahasiswa wanita memiliki hasil belajar lebih tinggi dari mahasiswa pria; tidak ada hubungan yang signifikan antara tingkat CT dengan jenis kelamin; dan hasil analisis K-Mean clustering ditemukan 8 cluster.
Kata kunci: computational thinking, gender, hasil belajar.
DOI: http://dx.doi.org/10.23960/jpp.v13.i2.202309
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Akbar, B. (2021). Correlation Between Social Attitude and Computational Thinking Ability. Journal of Positive School Psychology, 2022(5), 8965–8974. http://journalppw.com
Anderson, L. W., & Krathwohl, D. R. (2001). A Taxonomy for Learning , Teaching , and Assessing : A Revision of Bloom ’ s Taxonomy of Educational Objectives. Spring.
Angeli, C., & Georgiou, K. (2023). Investigating the effects of gender and scaffolding in developing preschool children’s computational thinking during problem-solving with Bee-Bots. Frontiers in Education, 7(January), 1–12. https://doi.org/10.3389/feduc.2022.757627
Angeli, C., & Valanides, N. (2020). Developing young children’s computational thinking with educational robotics: An interaction effect between gender and scaffolding strategy. Computers in Human Behavior, 105(January), 105954. https://doi.org/10.1016/j.chb.2019.03.018
Avcı, C., & Deniz, M. N. (2022). Computational thinking: early childhood teachers’ and prospective teachers’ preconceptions and self-efficacy. Education and Information Technologies. https://doi.org/10.1007/s10639-022-11078-5
Behlol, M. G., & Dad, H. (2010). Concept of Learning. International Journal of Psychological Studies, 2(2). https://doi.org/10.5539/ijps.v2n2p231
Bell, S. (2010). Project-Based Learning for the 21st Century: Skills for the Future. The Clearing House: A Journal of Educational Strategies, Issues and Ideas, 83(2), 39–43. https://doi.org/10.1080/00098650903505415
Chongo, S., Osman, K., & Nayan, N. A. (2020). Level of Computational Thinking Skills among Secondary Science Student: Variation across Gender and Mathematics Achievement. Science Education International, 31(2), 159–163. https://doi.org/10.33828/sei.v31.i2.4
Espino, E. E. E., & González, C. G. (2016). Gender and computational thinking: Review of the literature and applications. ACM International Conference Proceeding Series, 6–7. https://doi.org/10.1145/2998626.2998665
Fukuda, K. (2020). Science, technology and innovation ecosystem transformation toward society 5.0. International Journal of Production Economics, 220(April), 107460. https://doi.org/10.1016/j.ijpe.2019.07.033
Ghosh, R., Rude-Parkins, C., & Kerrick, S. A. (2012). Collaborative problem-solving in virtual environments: Effect of social interaction, social presence, and sociability on critical thinking. In The Next Generation of Distance Education: Unconstrained Learning. https://doi.org/10.1007/978-1-4614-1785-9_13
Hasan, N., & Bao, Y. (2020). Impact of “e-Learning crack-up” perception on psychological distress among college students during COVID-19 pandemic: A mediating role of “fear of academic year loss.” Children and Youth Services Review, 118(August), 105355. https://doi.org/10.1016/j.childyouth.2020.105355
Heer, R. (2012). A model of learning objectives. In Center for Excellence in Learning and Teaching.
Hsu, P., Van Dyke, M., & Smith, T. J. (2017). The Effect of Varied Gender Groupings on Argumentation Skills among Middle School Students in Different Cultures. Middle Grades Review, 3(2), 1–22. https://doi.org/10.1007/s11307-018-1199-6
Jiang, S., & Wong, G. K. W. (2022). Exploring age and gender differences of computational thinkers in primary school: A developmental perspective. Journal of Computer Assisted Learning, 38(1), 60–75. https://doi.org/10.1111/jcal.12591
Jones, B. D., Epler, C. M., Mokri, P., Bryant, L. H., & Paretti, M. C. (2013). The Effects of a Collaborative Problem-based Learning Experience on Students’ Motivation in Engineering Capstone Courses. Interdisciplinary Journal of Problem-Based Learning, 7(2), 5–16. https://doi.org/10.7771/1541-5015.1344
Korkmaz, Ö., & 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
Korkmaz, Ö., 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
Lodi, M., & Martini, S. (2021). Computational Thinking, Between Papert and Wing. 883–908.
Lundgren, B., Scheckle, E., & Zinn, D. (2015). Teachers’ professional development: Awareness of literacy practices. South African Journal of Education, 35(1), 1–11. https://doi.org/10.15700/201503062347
Moon, J., Do, J., Lee, D., & Choi, G. W. (2020). A conceptual framework for teaching computational thinking in personalized OERs. Smart Learning Environments, 7(1). https://doi.org/10.1186/s40561-019-0108-z
Pritchard, A. (2009). Ways of Learning. In The Lancet (Vol. 246, Issue 6365). https://doi.org/10.1016/S0140-6736(45)91319-5
Riyadi, S., Doewes, R. I., & Gontara, S. Y. (2020). The value of Adobe Flash Player media in the learning of football skills. International Sports Studies, 42(3), 92–96. https://doi.org/10.30819/iss.42-e.10
Rosali, D. F., & Suryadi, D. (2021). An Analysis of Students’ Computational Thinking Skills on The Number Patterns Lesson during The Covid-19 Pandemic. Formatif: Jurnal Ilmiah Pendidikan MIPA, 11(2), 217–232. https://doi.org/10.30998/formatif.v11i2.9905
Santosa, E. B., Degeng, I. N. S., Sulton, & Kuswandi, D. (2020). The effects of mobile computer-supported collaborative learning to improve problem solving and achievements. Journal for the Education of Gifted Young Scientists. https://doi.org/10.17478/jegys.656642
Santosa, E. B., & Sarwanta, S. (2021). Pengaruh Tingkat Internet Self-Efficacy, Pengalaman Mengajar dan Usia Guru Terhadap Peguasaan Komputer dalam Strategi Pembelajaran Daring. Jurnal Pendidikan Edutama, 8(1), 41. https://doi.org/10.30734/jpe.v8i1.1489
Selby, C., & Woollard, J. (2016). The Developing Concept of Computational Thinking. Informatics in Education, October 2018, 1–3. http://eprints.soton.ac.uk/401033/1/161002TableofC%26CT.pdf
Shanmugam, L., & Nadesan, G. (2019). An Innovative Module for Learning Computational Thinking Skills among Undergraduate Students. International Journal of Academic Research in Progressive Education and Development, 8(4), 116–129. https://doi.org/10.6007/ijarped/v8-i4/6440
Sola, E., Hoekstra, R., Fiore, S., & McCauley, P. (2017). An Investigation of the State of Creativity and Critical Thinking in Engineering Undergraduates. Creative Education, 08(09), 1495–1522. https://doi.org/10.4236/ce.2017.89105
Sovey, S., Osman, K., & Matore, M. E. E. M. (2022). Gender differential item functioning analysis in measuring computational thinking disposition among secondary school students. Frontiers in Psychiatry, 13(November), 1–14. https://doi.org/10.3389/fpsyt.2022.1022304
Syafril, S., Rahayu, T., & Ganefri, G. (2022). Advancing students’ computational thinking skills through educational robotics A study on age and gender relevant differencess. Jurnal Pendidikan IPA Indonesia, 11(1), 119–128. https://doi.org/10.15294/jpii.v11i1.33125
Tsai, M. J., Liang, J. C., & Hsu, C. Y. (2021). The Computational Thinking Scale for Computer Literacy Education. Journal of Educational Computing Research, 59(4), 579–602. https://doi.org/10.1177/0735633120972356
Weinberger, A., Fischer, F., & Stegmann, K. (2005). Computer-supported collaborative learning in higher education: Scripts for argumentative knowledge construction in distributed groups. Computer Supported Collaborative Learning 2005: The Next 10 Years - Proceedings of the International Conference on Computer Supported Collaborative Learning 2005, CSCL 2005, 717–726.
Xu, S., Li, Y., & Liu, J. (2021). The Neural Correlates of Computational Thinking: Collaboration of Distinct Cognitive Components Revealed by fMRI. Cerebral Cortex, 31(12), 5579–5597. https://doi.org/10.1093/cercor/bhab182
Yadav, A., Gretter, S., Good, J., & Mclean, T. (2017). Emerging Research, Practice, and Policy on Computational Thinking. Emerging Research, Practice, and Policy on Computational Thinking, November. https://doi.org/10.1007/978-3-319-52691-1
Yuzela, A., Kristiyanto, A., & Riyadi, S. (2023). The Effect of Audio and Audio Visual Imagery Exercises on the Level of Creativity of Aerobic Gymnastics Instructors. International Journal of Human Movement and Sports Sciences, 11(2), 292–298. https://doi.org/10.13189/saj.2023.110205
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