Computational Thinking Skill and Mathematics Problem Solving Using Flowgorithm: An Experiment with Eight-Grade Students of Madrasah Tsanawiyah
Keywords:
computational thinking, Flowgorithm, problem-solving, programming, Islamic schoolAbstract
This study aimed to evaluate the effect of using a Flowgorithm on computational thinking and mathematical problem-solving abilities. The research employed a quasi-experimental design with a pre-post test control group. The research was conducted in two phases: the programming phase and the mathematical phase. The research population consisted of all 8th-grade students from Madrasah Tsanawiyah in Bali Province, Indonesia, with sampling conducted using a cluster random sampling technique. The sample size was 34 students (14 students in the control group, 20 students in the experiment group). Data on computational thinking and problem-solving abilities are collected using tests. Data analysis used MANCOVA, followed by a post hoc test, and the effect size was described using the partial eta squared coefficient. The results show that there are significant differences between the two groups. The results of the post hoc test showed that the post hoc test results indicated that mathematics learning assisted by Flowgorithm significantly influenced computational thinking abilities. At the same time, no differences were observed in problem-solving abilities. Although the effect on mathematical problem-solving abilities was not significant, no negative impact was found from integrating Flowgorithm. These findings have implications for integrating computational thinking concepts in the curriculum and/or mathematics learning.
References
Abdullah, A. H., Rahman, S. N. S. A., and Hamzah, M. H. (2017). Metacognitive Skills of Malaysian Students in Non-Routine Mathematical Problem Solving. Bolema Boletim De Educação Matemática, 31(57), 310–322. https://doi.org/10.1590/1980-4415v31n57a15
Brennan, K., & Resnick, M. (2012). New frameworks for studying and assessing the development of computational thinking. In Proceedings of the 2012 annual meeting of the American educational research association, 1, 25). Retrieved from https://scratched.gse.harvard.edu/ct/files/AERA2012.pdf
Cameto, G., Carboni, A., Koleszar, V., Méndez, M., Tejera, G., Viera, M., and Wagner, J. (2019). Using functional programming to promote math learning. Proceedings - 14th Latin American Conference on Learning Technologies, LACLO 2019, 306–313. https://doi.org/10.1109/LACLO49268.2019.00059
Carboni, A., Koleszar, V., Tejera, G., Viera, M., and Wagner, J. (2018). MateFun: Functional Programming and Math with Adolescents. Proceedings - 2018 44th Latin American Computing Conference, CLEI 2018, 849–858. https://doi.org/10.1109/CLEI.2018.00106
Chan, S. W., Looi, C.-K., Ho, W. K., and Kim, M. S. (2022). Tools and Approaches for Integrating Computational Thinking and Mathematics: A Scoping Review of Current Empirical Studies. Journal of Educational Computing Research. https://doi.org/10.1177/07356331221098793
Chiang, F. K., Zhang, Y., Zhu, D., Shang, X., & Jiang, Z. (2022). The influence of online STEM education camps on students’ self-efficacy, computational thinking, and task value. Journal of science education and technology, 31(4), 461-472. https://doi.org/10.1007/s10956-022-09967-y
Costa, E. J. F., Campos, L. M. R. S., and Guerrero, D. D. S. (2017). Computational thinking in mathematics education: A joint approach to encourage problem-solving ability. Proceedings - Frontiers in Education Conference, FIE, 2017-Octob, 1–8. https://doi.org/10.1109/FIE.2017.8190655
Gajewski, R. R., and Smyrnova-Trybulska, E. (2018). Algorithms, programming, flowcharts and flowgorithm. E-Learning and Smart Learning Environment for the Preparation of New Generation Specialists, 393–408. Retrieved from http://www.studio-noa.pl/ig/pub/us/E-l-10/10-393.pdf
Gignac, G. E., and Szodorai, E. T. (2016). Effect size guidelines for individual differences researchers. Personality and Individual Differences, 102, 74–78. https://doi.org/https://doi.org/10.1016/j.paid.2016.06.069
Goldenberg, E. P., & Carter, C. J. (2021). Programming as a language for young children to express and explore mathematics in school. British Journal of Educational Technology, 52(3), 969-985. https://doi.org/10.1111/bjet.13080
Hoyles, C., and Noss, R. (2015). A Computational Lens on Design Research. ZDM, 47, 1039–1045. https://doi.org/10.1007/s11858-015-0731-2
Irawan, E., Rosjanuardi, R., and Prabawanto, S. (2024). Research trends of computational thinking in mathematics learning: A bibliometric analysis from 2009 to 2023. Eurasia Journal of Mathematics, Science and Technology Education, 20(3), em2417. https://doi.org/https://doi.org/10.29333/ejmste/14343
Iwamoto, T., and Matsumoto, S. (2019). Development of Web-Based Programming Learning Support System with Graph Drawing of Mathematics as a Learning Task. Proceedings - 2019 8th International Congress on Advanced Applied Informatics, IIAI-AAI 2019, 302–305. https://doi.org/10.1109/IIAI-AAI.2019.00067
Karaliopoulou, M., Apostolakis, I., and Kanidis, E. (2018). Perceptions of Informatics Teachers Regarding the Use of Block and Text Programming Environments. European Journal of Engineering and Technology Research. https://doi.org/10.24018/ejers.2018.0.cie.638
Maraza-Quispe, B., Sotelo-Jump, A. M., Alejandro-Oviedo, O. M., Quispe-Flores, L. M., Cari-Mogrovejo, L. H., Fernandez-Gambarini, W. C., and Cuadros-Paz, L. E. (2021). Towards the Development of Computational Thinking and Mathematical Logic through Scratch. International Journal Of Advanced Computer Science And Applications, 12(2), 332–338. https://dx.doi.org/10.14569/IJACSA.2021.0120242
Maryati, S., Lestarika, L., Idi, A., and Tri Samiha, Y. (2023). Madrasah as an Institution of Islamic Education and Social Change. Jurnal Konseling Pendidikan Islam, 4(2), 317–326. https://doi.org/10.32806/jkpi.v4i2.11
Miller, J. (2019). STEM education in the primary years to support mathematical thinking: using coding to identify mathematical structures and patterns. ZDM-MATHEMATICS EDUCATION, 51(6), 915–927. https://doi.org/10.1007/s11858-019-01096-y
Miterianifa, M., Ashadi, A., Saputro, S., and Suciati, S. (2021). Higher Order Thinking Skills in the 21st Century: Critical Thinking. https://doi.org/10.4108/eai.30-11-2020.2303766
Montiel, H., & Gomez-Zermeño, M. G. (2021). Educational challenges for computational thinking in k–12 education: A systematic literature review of “scratch” as an innovative programming tool. Computers, 10(6), 69. https://doi.org/10.3390/computers10060069
Park, Y., and Shin, Y. (2022). Text Processing Education Using a Block-Based Programming Language. Ieee Access. https://doi.org/10.1109/access.2022.3227765
Robins, A., Rountree, J., and Rountree, N. (2003). Learning and Teaching Programming: A Review and Discussion. Computer Science Education. https://doi.org/10.1076/csed.13.2.137.14200
Rodríguez-Martínez, J. A., González-Calero, J. A., and 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
Román-González, M., Pérez-González, J. C., & Jiménez-Fernández, C. (2017). Which cognitive abilities underlie computational thinking? Criterion validity of the Computational Thinking Test. Computers in human behavior, 72, 678-691. https://doi.org/10.1016/j.chb.2016.08.047
Selby, C., and Woollard, J. (2014). Refining an understanding of computational thinking. eprints.soton.ac.uk. https://eprints.soton.ac.uk/372410
Sentance, S, and Csizmadia, A. (2017). Computing in the curriculum: Challenges and strategies from a teacher’s perspective. In Education and Information Technologies. Springer. https://doi.org/10.1007/s10639-016-9482-0
Sentance, S, and Csizmadia, A. (2016). Computing in the Curriculum: Challenges and Strategies From a Teacher’s Perspective. Education and Information Technologies, 22(2), 469–495. https://doi.org/10.1007/s10639-016-9482-0
Seehorn, D., Carey, S., Fuschetto, B., Lee, I., Moix, D., O'Grady-Cunniff, D., and Verno, A. (2011). CSTA K--12 Computer Science Standards: Revised 2011. ACM.
Spencer, D., Mark, J., Reed, K., Goldenberg, P., Coleman, K., Chiappinelli, K., and Kolar, Z. (2023). Using Programming to Express Mathematical Ideas. Mathematics Teacher: Learning and Teaching PK-12, 116(5), 322–329. https://doi.org/https://doi.org/10.5951/MTLT.2022.0354
Stephen, J. S., and Rockinson-Szapkiw, A. J. (2021). A high-impact practice for online students: the use of a first-semester seminar course to promote self-regulation, self-direction, online learning self-efficacy. Smart Learning Environments, 8(1), 6. https://doi.org/https://doi.org/10.1186/s40561-021-00151-0
Tsarava, K., Moeller, K., Román-González, M., Golle, J., Leifheit, L., Butz, M. V., and Ninaus, M. (2022). A cognitive definition of computational thinking in primary education. Computers & Education, 179, 104425. https://doi.org/10.1016/j.compedu.2021.104425
Varela, C., Rebollar, C., Garcia, O., Bravo, E., and Bilbao, J. (2019). Skills in computational thinking of engineering students of the first school year. HELIYON, 5(11). https://doi.org/10.1016/j.heliyon.2019.e02820
Weintrop, D. (2015). Comparing Text-Based, Blocks-Based, and Hybrid Blocks/Text Programming Tools. https://doi.org/10.1145/2787622.2787752
Weintrop, D., and Wilensky, U. (2017). Comparing block-based and text-based programming in high school computer science classrooms. ACM Transactions on Computing Education (TOCE), 18(1), 1–25. https://doi.org/https://doi.org/10.1145/3089799
Witherspoon, E. B., Higashi, R. M., Schunn, C. D., Baehr, E. C., and Shoop, R. (2017). Developing Computational Thinking through a Virtual Robotics Programming Curriculum. ACM Transactions on Computing Education, 18(1). https://doi.org/10.1145/3104982
Xu, Z., Ritzhaupt, A. D., Tian, F., and Umapathy, K. (2019). Block-based versus text-based programming environments on novice student learning outcomes: a meta-analysis study. Computer Science Education, 29(2–3), 177–204. https://doi.org/10.1080/08993408.2019.1565233
Yadav, A., Gretter, S., Hambrusch, S., and Sands, P. (2016). Expanding computer science education in schools: understanding teacher experiences and challenges. Computer Science Education, 26(4), 235–254. https://doi.org/10.1080/08993408.2016.1257418
Ye, H., Liang, B., Ng, O. L., and Chai, C. S. (2023). Integration of computational thinking in K-12 mathematics education: A systematic review on CT-based mathematics instruction and student learning. International Journal of STEM Education, 10(1), 3. https://doi.org/10.1186/s40594-023-00396-w
Ye, Huiyan, Ng, O.-L., and Cui, Z. (2023). Conceptualizing Flexibility in Programming-Based Mathematical Problem-Solving. Journal of Educational Computing Research. https://doi.org/10.1177/07356331231209773
Yi, S., and Lee, Y.-J. (2018). An Educational System Design to Support Learning Transfer From Block-Based Programming Language to Text-Based Programming Language. International Journal on Advanced Science Engineering and Information Technology. https://doi.org/10.18517/ijaseit.8.4-2.5735
Yuana, R. A., Faisal, M., Pangestu, D., and Putri, Y. R. L. (2015). Math thematic learning through the introduction of basic science-based programming games virtual robot for high school students. Advanced Science Letters, 21(7), 2235–2238. https://doi.org/10.1166/asl.2015.6318
Zeng, Y., Yang, W., and Bautista, A. (2023). Teaching programming and computational thinking in early childhood education: a case study of content knowledge and pedagogical knowledge. Frontiers in Psychology, 14, 1252718. https://doi.org/10.3389/fpsyg.2023.1252718
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, 31(6), 3792–3809. https://doi.org/10.1080/10494820.2021.1943687
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