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    • Computational Thinking Skills Indicators in Number Patterns | Helsa | Jurnal Pendidikan Matematika

    Computational Thinking Skills Indicators in Number Patterns

    Yullys Helsa, Dadang Juandi, Turmudi Turmudi

    Abstract


    This research aims to examine a) what computational thinking indicators have been developed by researchers, b) what computational thinking indicators can be used in learning mathematics appropriately, and c) how to describe the development of student computational thinking indicators from the answers of computational thinking tests. This research is a qualitative descriptive study through a process of collecting data from literature reviews, integrated computational thinking math tests, and interviews. Data collection instruments used research notes, interview sheets, and CT question sheets. The results showed that a) 20 computational thinking indicators had been studied by researchers, b) computational thinking indicators that could be used in learning mathematics include problem decomposition, abstraction, pattern recognition, procedural algorithms, and generalizations, and c) From the student answers, five proposed computational thinking indicators can be developed even though they were not perfect. The general implication of this research is that there are five indicators of computational thinking skills that can be used in mathematics learning, specifically in number patterns, which include problem decomposition, abstraction, pattern recognition, pattern recognition, procedural algorithm, and generalization. The researchers developed all five computational thinking skills indicators in the instructional designs of not only the number pattern concept but also combination, geometry, combinatorics, etc.


    Keywords


    Indicators; Computational Thinking Skills; Learning Mathematics; Number Pattern

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    References


    Acevedo-Borrega, J., Valverde-Berrocoso, J., & Garrido-Arroyo, M. D. C. (2022). Computational thinking and educational technology: A scoping review of literature. Education Sciences, 12(1). https://doi.org/10.3390/educsci12010039.

    Angeli, C., Voogt, J., Fluck, A., Webb, M., Cox, M., Malyn-Smith, J., & Zagami, J. (2016). A K-6 computational thinking curriculum framework: Implications for teacher knowledge. Educational Technology and Society, 19(3), 47–57. Retrieved from https://www.jstor.org/stable/jeductechsoci.19.3.47 .

    Anwar, V. N., & Herman, T. (2022). Bibliometric Analysis of publication trends stem approach based on computational thinking in learning mathematics [in Bahasa]. JPMI, 5(5), 1387–1396. https://doi.org/10.22460/jpmi.v5i5.1387-1396.

    Asbell-Clarke, J., Rowe, E., Almeda, V., Edwards, T., Bardar, E., Gasca, S., Baker, R. S., & Scruggs, R. (2021). The development of students’ computational thinking practices in elementary and middle-school classes using the learning game, Zoombinis. Computers in Human Behavior, 115. https://doi.org/10.1016/j.chb.2020.106587.

    Babazadeh, M., & Negrini, L. (2022). How is computational thinking assessed in European K-12 education? A systematic review. International Journal of Computer Science Education in Schools, 5(4), 3–19. https://doi.org/10.21585/ijcses.v5i4.138.

    Basu, S., Biswas, G., Sengupta, P., Dickes, A., Kinnebrew, J. S., & Clark, D. (2016). Identifying middle school students’ challenges in computational thinking-based science learning. Research and Practice in Technology Enhanced Learning, 11(1). https://doi.org/10.1186/s41039-016-0036-2.

    Blokhuis, D., Csizmadia, A., Millican, P., Roffey, C., Schijvers, E., & Sentence, S. (2017). UK Bebras Computational Thinking Challenge. UK Bebras. http://www.bebras.uk/answer-booklets.%0Ahtml.

    Blokhuis, D., Millican, P., Roffey, C., Schrijvers, E., & Sentance, S. (2015). UK Bebras Computational Thinking Challenge. UK Bebras. http://www.bebras.uk/answer-booklets.html.

    Bocconi, S., Chioccariello, A., Dettori, G., Ferrari, A., Engelhardt, K., Kampylis, P., & Punie, Y. (2016). Developing Computational Thinking in Compulsory Education - Implications for policy and practice. In Joint Research Centre (JRC) (Issue June). https://doi.org/10.2791/792158.

    Cansu, F. K., & Cansu, S. K. (2019). An overview of computational thinking. International Journal of Computer Science Education in Schools, 3(1), 17–30. https://doi.org/10.21585/ijcses.v3i1.53.

    Creswell, J. W., & Clark, V. L. P. (2018). Designing and Conducting Mixed Methods Research. SAGE Publications. Retrieved from https://us.sagepub.com/en-us/nam/designing-and-conducting-mixed-methods-research/book241842.

    Csizmadia, A., Standl, B., & Waite, J. (2019). Integrating the constructionist learning theory with computational thinking classroom activities. Informatics in Education, 18(1), 41–67. https://doi.org/10.15388/infedu.2019.03.

    Cutumisu, M., Adams, C., & Lu, C. (2019). A scoping review of empirical research on recent computational thinking assessments. Journal of Science Education and Technology, 28(6), 651–676. https://doi.org/10.1007/s10956-019-09799-3.

    Dede, C., Mishra, P., & Voogt, J. (2013). Working Group 6: Advancing computational thinking in 21. International Summit on ICT in Education, 1–6. https://ris.utwente.nl/ws/files/6168377/Advancing_computational_thinking_in_21st_century_learning.pdf.

    Fagerlund, J., Hakkinen, P., Vesisenaho, M., & Viiri, J. (2020). assessing 4th grade students’ computational thinking through scratch programming projects. Informatics in Education, 19(4), 611–640. https://doi.org/10.15388/INFEDU.2020.27.

    Fagerlund, J., Häkkinen, P., Vesisenaho, M., & Viiri, J. (2021). Computational thinking in programming with Scratch in primary schools: A systematic review. Computer Applications in Engineering Education, 29(1), 12–28. https://doi.org/10.1002/cae.22255.

    Fronza, I., El Ioini, N., & Corral, L. (2017). Teaching computational thinking using agile software engineering methods: A framework for middle schools. ACM Transactions on Computing Education, 17(4), 1–27. https://doi.org/10.1145/3055258.

    Goodson, B., Sarna, M., & Associates, A. (2020). Measuring Computational Thinking and Computer Science Outcomes. Education Innovation and Research (EIR) Project Directors and Evaluators Technical Assistance Meeting. https://oese.ed.gov/files/2021/03/CSCTOutcomes_508.pdf.

    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.

    Guggemos, J. (2021). On the predictors of computational thinking and its growth at the high-school level. Computers and Education, 161, 104060. https://doi.org/10.1016/j.compedu.2020.104060.

    Guggemos, J., Seufert, S., & Román-González, M. (2019). Measuring computational thinking - Adapting a performance test and a self-assessment instrument for German-speaking countries. 16th International Conference on Cognition and Exploratory Learning in Digital Age, CELDA 2019, Celda, 183–191. https://doi.org/10.33965/celda2019_201911l023.

    Hadad, R., Thomas, K., Kachovska, M., & Yin, Y. (2020). Practicing formative assessment for computational thinking in making environments. Journal of Science Education and Technology, 29. https://doi.org/10.1007/s10956-019-09796-6.

    Helsa, Y., Suparman, Juandi, D., & Turmudi. (2023). A meta-analysis of the utilization of computer technology in enhancing computational thinking skills: Direction for mathematics learning. International Journal of Instruction. https://doi.org/10.29333/iji.2023.16239a.

    Kang, C., Liu, N., Zhu, Y., Li, F., & Zeng, P. (2022). Developing college students’ computational thinking multidimensional test based on life story situations. Education and Information Technologies. https://doi.org/10.1007/s10639-022-11189-z.

    Kemendikbudristek. (2022). Learning outcomes in early childhood, elementary education, and secondary education in the independent curriculum [in Bahasa]. https://kurikulum.kemdikbud.go.id/wp-content/unduhan/CP_2022.pdf.

    Khosrow-Pour, M. (2018). Encyclopedia of Information Science and Technology, Fourth Edition (Fourth). IGI Global. https://doi.org/10.4018/978-1-5225-2255-3.ch417.

    Kidd, T., R, L., & Morris, J. (2017). Handbook of Research on Instructional Systems and Educational Technology. IGI Global. http://dx.doi.org/10.4018/978-1-5225-2399-4.

    Kong, S. C., & Wang, Y. Q. (2021). Item response analysis of computational thinking practices: Test characteristics and students’ learning abilities in visual programming contexts. Computers in Human Behavior, 122. https://doi.org/10.1016/j.chb.2021.106836.

    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.

    Lee, I., Martin, F., Denner, J., Coulter, B., Allan, W., Erickson, J., Malyn-Smith, J., & Werner, L. (2011). Computational thinking for youth in practice. ACM Inroads, 2(1), 32–37. https://doi.org/10.1145/1929887.1929902.

    Martínez, V., Mon, M. A., Álvarez, M., Fueyo, E., & Dobarro, A. (2020). E -Self-Assessment as a Strategy to Improve the Learning Process at University. Education Research International, 2020. https://doi.org/10.1155/2020/3454783.

    Morze, N., Barna, O., & Boiko, M. (2022). The relevance of training primary school teachers computational thinking. CEUR Workshop Proceedings, 3104(Icteri 2021), 141–153. Retrieved from https://ceur-ws.org/ .

    Nurwita, F., Kusumah, Y. S., & Priatna, N. (2022). Exploring students’ mathematical computational thinking ability in solving pythagorean theorem problems. 13(2), 273–287. https://doi.org/10.24042/ajpm.v13i2.12496.

    Polat, E., Hopcan, S., Kucuk, S., & Sisman, B. (2021). A comprehensive assessment of secondary school students’ computational thinking skills. British Journal of Educational Technology, 52(5), 1965–1980. https://doi.org/10.1111/bjet.13092.

    Putra, Z. H., Ramiati, R., Zufriady, Z., Hidayat, R., Jismulatif, J., Hermita, N., & Sulistiyo, U. (2022). Development of computational thinking tasks based on Riau Malay culture for primary school. 1–23. https://doi.org/10.1080/03004279.2022.2150063.

    Relkin, E., de Ruiter, L., & Bers, M. U. (2020). TechCheck: Development and validation of an unplugged assessment of computational thinking in early childhood education. Journal of Science Education and Technology, 29(4), 482–498. https://doi.org/10.1007/s10956-020-09831-x.

    Rey, Y. A. R. del, Cambinda, I. N. C., Deco, C., Bender, C., Avello-Martínez, R., & Villalba-Condori, K. O. (2020). Developing computational thinking with a module of solved problems. Computer Application in Engineering Education, 29(3), 506–516. https://doi.org/10.1002/cae.22214.

    Rodríguez-Martínez, J. A., González-Calero, J. A., & Sáez-López, J. M. (2020). Computational thinking and mathematics using Scratch: an experiment with sixth-grade students. Interactive Learning Environments, 28(3), 316–327. https://doi.org/10.1080/10494820.2019.1612448.

    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.

    Seiter, L., & Foreman, B. (2013). Modeling the learning progressions of computational thinking of primary grade students. ICER 2013 - Proceedings of the 2013 ACM Conference on International Computing Education Research, 59–66. https://doi.org/10.1145/2493394.2493403.

    Selby, C., Dorling, M., & Woollard, J. (2015). Evidence of assessing computational thinking. IFIP TC3 Working Conference: A New Culture of Learning: Computing and Next Generations, 232–242. http://www.ifip2015.mii.vu.lt/file/repository/IFIP_Proceedings.pdf.

    Selby, C., Dorling, M., & Woollard, J. (2014). Evidence of assessing computational thinking. IFIP TC3 Working Conference: A New Culture of Learning: Computing and Next Generations, 232–242. http://www.ifip2015.mii.vu.lt/file/repository/IFIP_Proceedings.pdf.

    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.

    Sondakh, D. E., Osman, K., & Zainudin, S. (2020). A proposal for holistic assessment of computational thinking for undergraduate: Content validity. European Journal of Educational Research, 9(1), 33–50. https://doi.org/10.12973/eu-jer.9.1.33.

    Suharto, H. (2022). Systematic literature review (SLR) computational thinking learning science in the period 2012 - 2021. International Journal of Educational Technology and Instruction, 1(1), 1–13. https://ijeti-edu.org/index.php/ijeti/article/view/1.

    Tang, X., Yin, Y., Lin, Q., Hadad, R., & Zhai, X. (2020). Assessing computational thinking: A systematic review of empirical studies. Computers and Education, 148(Mc 147). https://doi.org/10.1016/j.compedu.2019.103798.

    Tim Penyusun Materi ITB. (2020). Computational thinking in primary and secondary education [in Bahasa]. Lembaga Penelitian dan Pengabdian Kepada Masyarakat. Retrieved from https://www.researchgate.net/profile/Ginar-Niwanputri/publication/350383897_Computational_Thinking_Learning_and_Teaching_Guide_for_Primary_and_Secondary_Schools_in_Indonesia/links/605cc073458515e8346fdb11/Computational-Thinking-Learning-and-Teaching-Guide-for-Primary-and-Secondary-Schools-in-Indonesia.pdf.

    Van Borkulo, S., Chytas, C., Drijvers, P., Barendsen, E., & Tolboom, J. (2021). Computational thinking in the mathematics classroom: Fostering algorithmic thinking and generalization skills using dynamic mathematics software. ACM International Conference Proceeding Series. https://doi.org/10.1145/3481312.3481319.

    Veerasamy, A. K., Laakso, M. J., & D’Souza, D. (2022). Formative assessment tasks as indicators of student engagement for predicting at-risk students in programming courses. Informatics in Education, 21(2), 375–393. https://doi.org/10.15388/infedu.2022.15,

    Waterman, K. P., Goldsmith, L., & Pasquale, M. (2020). Integrating computational thinking into elementary science curriculum: An examination of activities that support students’ computational thinking in the service of disciplinary learning. Journal of Science Education and Technology, 29(1), 53–64. https://doi.org/10.1007/s10956-019-09801-y.

    Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25(1), 127–147. https://doi.org/10.1007/s10956-015-9581-5.

    Weintrop, D., Rutstein, D. W., Bienkowski, M., & McGee, S. (2021). Assessing computational thinking: An overview of the field. Computer Science Education, 31(2), 113–116. https://doi.org/10.1080/08993408.2021.1918380.

    Wing, J. M. (2006). Computational thinking. Researchgate.Net, 3–3. https://doi.org/10.1109/vlhcc.2011.6070404.

    Wing, J. M. (2011). Research Notebook: Computational thinking -what and why? The Link Magazine. Retrieved from https://www.cs.cmu.edu/link/research-notebook-computational-thinking-what-and-why.

    Wing, J. M., & Stanzione, D. (2016). Progress in computational thinking, and expanding the HPC community. Communications of the ACM, 59(7), 10–11. https://doi.org/10.1145/2933410.

    Wu, W. R., & Yang, K. L. (2022). The relationships between computational and mathematical thinking: A review study on tasks. Cogent Education, 9(1). https://doi.org/10.1080/2331186X.2022.2098929.

    Yadav, A, Krist, C., Good, J., & Caeli, E. N. (2018). Computational thinking in elementary classrooms: measuring teacher understanding of computational ideas for teaching science. Computer Science Education, 1–30. https://doi.org/10.1080/08993408.2018.1560550.

    Yadav, A, Stephenson, C., & Hong, H. (2017). Computational thinking for teacher education. Communications of the ACM, 60(4), 55–62. Retrieved from https://edtechbooks.org/-TN/.

    Yadav, Aman, Hong, H., & Stephenson, C. (2016). Computational thinking for All: Pedagogical approaches to embedding 21st century problem solving in K-12 classrooms. TechTrends, 60(6), 565–568. https://doi.org/10.1007/s11528-016-0087-7.

    Yadav, Aman, Mayfield, C., Zhou, N., Hambrusch, S., & Korb, J. T. (2014). Computational thinking in elementary and secondary teacher education. ACM Transactions on Computing Education, 14(1), 1–16. https://doi.org/10.1145/2576872.

    Yambi, T. de A. C. (2020). Assessment and Evaluation in Education EDUC 540 Spring 2020. Researchgate, Retrieved from https://www.researchgate.net/publication/342918149_ASSESSMENT_AND_EVALUATION_IN_EDUCATION.

    Zoud, R., & Namukasa, I. (2023). Computational thinking workshop: A new way to learn and teach mathematics. journal of research in science, Mathematics and Technology Education, 6(2), 99-119. https://doi.org/10.31756/jrsmte.624.




    DOI: https://doi.org/10.22342/jpm.17.2.20042.167-188

    Jurnal Pendidikan Matematika
    Department of Master Program on Mathematics Education
    Faculty of Teacher Training and Education
    Sriwijaya University, Palembang, Indonesia
    Kampus FKIP Bukit Besar
    Jl. Srijaya Negara, Bukit Besar
    Palembang - 30139 Indonesia
    email: jpm@unsri.ac.id
    p-ISSN: 1978-0044; e-ISSN: 2549-1040

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