Computational thinking on concept pattern number: A study learning style Kolb
DOI:
https://doi.org/10.29408/jel.v10i1.23056Keywords:
computational thinking, number pattern, learning style KolbAbstract
This research aimed to determine how the number pattern concept's computational thinking characteristic picture was reviewed from the Kolb model's learning style. The research method used in this study is qualitative descriptive. The research was conducted at one of the state's small schools in Bandung. The research subjects consisted of 29 students in the ninth grade. One of the 29 study issues is selected with assimilator learning styles. The data-gathering techniques used are questionnaire tests, test instruments, and interviews. Angket is used to group subjects into four groups of learning style types. The test instrument was used to describe the computational thinking characteristics of high school students on the concept of number patterns, and the interview was used to strengthen the test summary results of the subject. The results of this study show that the characteristics of computational thinking that each type of learning style dominates are different. Computational thinking students with an assimilator learning style in solving mathematical problems of number patterns can solve issues by involving decomposition, pattern identification, abstraction and generalization, and algorithms. They can generalize patterns using accurate, thorough, complete, and systematic problem-solving strategies.References
Amin, A., & Suardiman, S. P. (2016). Perbedaan prestasi belajar matematika siswa ditinjau dari gaya belajar dan model pembelajaran [Differences in student mathematics learning achievement judging from learning styles and learning models]. Jurnal Prima Edukasia, 4(1), 12-19. https://doi.org/10.21831/jpe.v4i1.7688
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. https://doi.org/10.1016/j.chb.2019.03.018.
Angeli, C., Voogt, J., Fluck, A., Webb, M., Cox, M., Malyn-Smith, J., & Zagami, J. (2016). International forum of educational technology & society A K-6 computational thinking curriculum framework: Implications for teacher knowledge. Journal of Educational Technology & Society, 19(3), 47-57. https://pure.uva.nl/ws/files/8964271/A_K_6_Computational_Thinking_Curriculum_Framework.pdf
Anwar, A., Turmudi, T., Juandi, D., Saiman, S., & Zaki, M. (2023). Level of visual geometry skill towards learning style Kolb in junior high school. Jurnal Elemen, 9(2), 542–557. https://doi.org/10.29408/jel.v9i2.15121
Beaty, E., Dall’Alba, G., & Marton, F. (1997). The personal experience of learning in higher education: Changing views and enduring perspectives. In Adult Learning: A reader.
Beijaard, D., Verloop, N., & Vermunt, J. D. (2000). Teachers’ perceptions of professional identity: an exploratory study from a personal knowledge perspective. Teaching and Teacher Education, 16(7), 749–764. https://doi.org/10.1016/S0742-051X(00)00023-8
Bishop, J. (2000). Linear geometric number patterns: Middle school students’ strategies. Mathematics Education Research Journal, 12(2), 107–126. https://doi.org/10.1007/BF03217079
Bower, M., Wood, L. N., Lai, J. W. M., Howe, C., & Lister, R. (2017). Improving the computational thinking pedagogical capabilities of school teachers. Australian Journal of Teacher Education, 42(3), 53–72. https://doi.org/10.14221/ajte.2017v42n3.4
Cassidy, S. (2004). Learning styles: An overview of theories, models, and measures. Educational Psychology, 24(4), 419–444. https://doi.org/10.1080/0144341042000228834
Cetin, H. (2019). Explaining the concept and operations of integer in primary school mathematics teaching: Opposite model sample. Universal Journal of Educational Research, 7(2), 365–370. https://doi.org/10.13189/ujer.2019.070208
Choi, J., Lee, Y., & Lee, E. (2017). Puzzle Based Algorithm Learning for Cultivating Computational Thinking. Wireless Personal Communications, 93(1), 131–145. https://doi.org/10.1007/s11277-016-3679-9
Cohen, L., Manion, L., & Morrison, K. (2017). Research methods in education. In Research Methods in Education. https://doi.org/10.4324/9781315456539
Curzon, P., Selby, C., & Woollard, J. (2014). Developing computational thinking in the classroom: a framework ! http://www.digitalschoolhouse.org.uk
Danindra, L. S., & Masriyah. (2020). Proses berpikir komputasi siswa dalam memecahkan masalah pola bilangan ditinjau dari perbedaan jenis kelamin [Students' computational thinking process in solving number pattern problems given gender differences]. MATHEdunesa, 9(1), 95-103. https://doi.org/10.26740/mathedunesa.v9n1.p95-103
Delyana, H. (2015). Peningkatan kemampuan pemecahan masalah matematika siswa kelas VII melalui penerapan pendekatan open ended [Improving class VII students' mathematical problem-solving abilities through implementing an open-ended approach]. Lemma, 2(2). https://doi.org/10.24114/jh.v2i2.2029
Grover, S., & Pea, R. (2021). Computational thinking: A competency whose time has come. Computer Science Education, December. https://doi.org/10.5040/9781350057142.ch-003.
James, W. B., & Gardner, D. L. (1995). Learning styles: Implications for distance learning. New Directions for Adult and Continuing Education, 1995(67), 2365-2387. https://doi.org/10.1002/ace.36719956705
Kolb, D. A. (2014). Experiential learning: Experience as the source of learning and development .[Kindle version]. Retrieved from Amazon. Com.(Original Work Published. https://www.researchgate.net/publication/235701029_Experiential_Learning_Experience_As_The_Source_Of_Learning_And_Development.
Larsson, M., & Ryve, A. (2011). Effective teaching through problem-solving by sequencing and connecting student solutions. Proceedings of NORMA11: The Sixth Nordic Conference on Mathematics Education in Reykjavik, May 11-14 2011 / [Ed] G. H. Gunnarsdóttir, F. Hreinsdóttir, G. Pálsdóttir, M. Hannula, M. Hannula-Sormunen, E. Jablonka, U. T. Jankvist, A. Ryve, P. Valero, & K. Wa. https://mdh.diva-portal.org/smash/record.jsf?pid=diva2%3A562445&dswid=-7507.
Lee, T. Y., Mauriello, M. L., Ahn, J., & Bederson, B. B. (2014). CTArcade: Computational thinking with games in school age children. International Journal of Child-Computer Interaction, 2(1), 26-33. https://doi.org/10.1016/j.ijcci.2014.06.003
Lestari, I., Kesumawati, N., & Ningsih, Y. L. (2020). Mathematical representation of grade 7 students in set theory topics through problem-based learning. Infinity Journal, 9(1), 103–110. https://doi.org/10.22460/infinity.v9i1.p103-110.
M Ghufron Nur, R. R. (2013). Gaya belajar: Kajian teoritik [Learning styles: A theoretical study]. Pustaka Pelajar. https://repository.iainkediri.ac.id/583/
Mgova, Z. (2018). Computational thinking skills in education curriculum. https://erepo.uef.fi/bitstream/handle/123456789/19416/urn_nbn_fi_uef-20180343.pdf?sequence=1&isAllowed=y.
Presmeg, N. (2006). Research on visualization in learning and teaching mathematics. Handbook of Research on the Psychology of Mathematics Education: Past, Present and Future, 205–235. https://doi.org/10.1163/9789087901127_009.
Purwasih, R., Turmudi, & Dahlan, J. A. (2023). Analisis semiotik siswa SMP dalam menyelesaikan masalah geometri [Semiotic Analysis of Middle School Students in Solving Geometry Problems.]. Jurnal Cendekia: Jurnal Pendidikan Matematika, 7(2), 1182–1191. https://doi.org/10.31004/cendekia.v7i2.2237
Quinnell, L., & Carter, M. L. (2012). Greek or not: The use of symbols and abbreviations in mathematics. Autralian Mathematics Teacher, 68(2), 34–41. https://researchers.cdu.edu.au/en/publications/greek-or-not-the-use-of-symbols-and-abbreviations-in-mathematics
Rivera, F. D. (2010). Visual templates in pattern generalization activity. Educational Studies in Mathematics, 73(3), 297-328. https://doi.org/10.1007/s10649-009-9222-0
Selby, C., & Woollard, J. (2016). The developing concept of “computational thinking.” October 2018. http://eprints.soton.ac.uk/401033/1/161002TableofC%26CT.pdf.
Skemp, R. R. (2012). The psychology of learning mathematics (p. : Expanded American edition. Routledge). https://www.routledge.com/The-Psychology-of-Learning-Mathematics-Expanded-American-Edition/Skemp/p/book/9780805800586
Steiner, M., & Resnik, M. (2000). Mathematics as a science of patterns. The Philosophical Review, 109(1), 115-118. https://doi.org/10.2307/2693566
Suntusia, Dafik, & Hobri. (2019). The effectiveness of research based learning in improving students’ achievement in solving two-dimensional arithmetic sequence problems. International Journal of Instruction, 12(1), 17-32. https://doi.org/10.29333/iji.2019.1212a
Vale, I., & Barbosa, A. (2015). Mathematics creativity in elementary teacher training. Journal of the European Teacher Education Network, 10(July), 101–109. https://etenjournal.com/2020/02/08/mathematics-creativity-in-elementary-teacher-training/
Wicaksono, A. B., Chasanah, A. N., & Sukoco, H. (2021). Kemampuan pemecahan masalah geometri berbasis budaya ditinjau dari gender dan gaya belajar [Culture-based geometry problem solving ability in view of gender and learning style]. AKSIOMA: Jurnal Program Studi Pendidikan Matematika, 10(1), 240-251. https://doi.org/10.24127/ajpm.v10i1.3256
Wing, J. M. (2008). Computational thinking and thinking about computing. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 366(1881), 3717–3725. https://doi.org/10.1098/rsta.2008.0118
Wing, J. M. (2017). Computational thinking’s influence on research and education for all Influenza del pensiero computazionale nella ricerca e nell’educazione per tutti. Italian Journal of Educational Technology, 25(2), 7–14. https://doi.org/10.17471/2499-4324/922
Yilmaz, R., & Argun, Z. (2018). Role of visualization in mathematical abstraction: The case of congruence concept. International Journal of Education in Mathematics, Science and Technology, 6(1).
Zhong, B., Wang, Q., Chen, J., & Li, Y. (2016). An exploration of three-dimensional integrated assessment for computational thinking. Journal of Educational Computing Research, 53(4), 562–590. https://doi.org/10.1177/0735633115608444
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