Implementation of Science Module Integrated with Google Colaboratory to Improve Students’ Computational Thinking Skill. Is it Effective?
Keywords:
Computational thinking skill, google colaboratory, science education, science module
Abstract
Computational thinking skills are one of the supporters of the achievement of 21st century skills. Computational thinking is recognised as the third pillar of science, along with theory and experimentation. This study aims to improve students’ computational thinking skill through implementation science module integrated with Google Colaboratory. Computational thinking skills in students can be improved through learning programming. Students must be guided to connect concepts and activities from students by creating computer programming. This research uses one group pretest-posttest, then the result will be analyzed using N-gain and paired sample test. The object of this research is 36 students in junior high school level. The result of this study shows that the mean of the pre-test score is 27,25 and the mean of the post-test score being 62,36 with the N-gain score is 0,48 in the moderate category. Results of paired sample test show a Sig. (2-tailed) of 0.000, which is smaller than the threshold of 0.05. This result shows that the implementation of the learning module had a significant positive effect on improving computational thinking skills.
References
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Nyutu, E., Cobern, W. W., & Pleasants, B. A.-S. (2020). Correlational Study of Student Perceptions of their Undergraduate Laboratory Environment with respect to Gender and Major. International Journal of Education in Mathematics, Science and Technology, 9(1), 83–102. https://doi.org/10.46328/ijemst.1182
Pérez-Marín, D., Hijón-Neira, R., Bacelo, A., & Pizarro, C. (2020). Can computational thinking be improved by using a methodology based on metaphors and scratch to teach computer programming to children? Computers in Human Behavior, 105, 105849. https://doi.org/10.1016/j.chb.2018.12.027
Rambe, Y. A., Silalahi, A., & Sudrajat, A. (2020). The Effect of Guided Inquiry Learning Model and Critical Thinking Skills on Learning Outcomes. Proceedings of the 5th Annual International Seminar on Transformative Education and Educational Leadership (AISTEEL 2020). https://doi.org/10.2991/assehr.k.201124.033
Ridlo, Z. R. ., Dafik, Waluyo, J. ., & Yushardi. (2024). Exploring the impact of makerspace-based learning materials on students’ computational thinking skills: Using machine learning to address challenges in smart coffee agroforestry. Edelweiss Applied Science and Technology, 8(5), 52–73. https://doi.org/10.55214/25768484.v8i5.1630
Ridlo, Z. R., Supeno, S., Wahyuni, S., Wicaksono, I., & Ulfa, E. M. (2022). Analysis of Implementation Project-Based Learning Model of Teaching Integrated with Computer Programming in Improving Computational Thinking Skills in a Classical Mechanics Course. Jurnal Penelitian Pendidikan IPA, 8(4), 2029–2035. https://doi.org/10.29303/jppipa.v8i4.1789
Romadhona, R. R., & Suyanto, S. (2020). Enhancing integrated science process skills: Is it better to use open inquiry or guided inquiry model?. Biosfer: Jurnal Pendidikan Biologi, 13(2), 307- 319. https://doi.org/10.21009/biosferjpb.v13n2.307-319
Saldo, I. J. P., & Walag, A. M. P. (2020). Utilizing problem-based and project-based learning in developing students’ communication and collaboration skills in physics. American Journal of Educational Research, 8(5), 232-237. https://doi.org/10.12691/education-8-5-1
Siahaan, K. W. A., Lumbangaol, S. T. P., Marbun, J., Nainggolan, A. D., Ritonga, J. M., & Barus, D. P. (2020). Pengaruh Model Pembelajaran Inkuiri Terbimbing dengan Multi Representasi terhadap Keterampilan Proses Sains dan Penguasaan Konsep IPA. Jurnal Basicedu, 5(1), 195–205. https://doi.org/10.31004/basicedu.v5i1.614
Sinaga, A. V. (2023). Peranan teknologi dalam pembelajaran untuk membentuk karakter dan skill peserta didik abad 21. Journal on Education, 6(1), 2836-2846.
Tock, K. (2019). Google CoLaboratory as a platform for Python coding with students. RTSRE Proceedings, 2(1). https://doi.org/10.32374/rtsre.2019.013
Ulfa, E. M., Wahyuni, S., & Ridlo, Z. R. (2023). Development of E-Module-Based PjBL to Develop Computational Thinking Skills Integrategration with CCR Implementation in Science Education. JPPS (Jurnal Penelitian Pendidikan Sains), 12(2), 176–191. https://doi.org/10.26740/jpps.v12n2.p176-191
Wicaksono, I., & Erlina, N. (2024). The Effect of Virtual Science Teaching Model on Scientific Creativity and Learning Outcomes. Jurnal Pendidikan MIPA, 25(1), 440–452. https://doi.org/10.23960/jpmipa/v25i1.pp440-452
Wing, J. (2017). Computational thinking’s influence on research and education for all. Italian Journal of Educational Technology, 25(2), 7-14. https://doi.org/10.17471/2499-4324/922
Wing, J. M. 2006. Computational thinking. Communications of the ACM. 49(3): 33–35. https://doi.org/10.1145/1118178.1118215
Yona Ratri, A., Aristya Putra, P. D., Rusdianto, R., & Nuha, U. (2024). Pengembangan Modul Berbasis Engineering Design Process (EDP) dalam Meningkatkan Keterampilan Berpikir Kreatif Siswa SMP Pada Pembelajaran IPA. Jurnal Sains Dan Edukasi Sains, 7(2), 105–111. https://doi.org/10.24246/juses.v7i2p105-111
Angeli, C., & Giannakos, M. (2020). Computational thinking education: Issues and challenges. Computers in Human Behavior, 105, 106185. https://doi.org/10.1016/ j.chb.2019.106185
Angraini, L. M., Yolanda, F., & Muhammad, Ilham. (2023). Augmented Reality: The Improvement of Computational Thinking Based on Students’ Initial Mathematical Ability. International Journal of Instruction, 16(3), 1033–1054. https://doi.org/10.29333/iji.2023.16355a
Borowczak, M., & Burrows, A. (2019). Ants Go Marching—Integrating Computer Science into Teacher Professional Development with NetLogo. Education Sciences, 9(1), 66. https://doi.org/10.3390/educsci9010066
Carneiro, T., Da Nóbrega, R. V. M., Nepomuceno, T., Bian, G. B., De Albuquerque, V. H. C., & Reboucas Filho, P. P. (2018). Performance analysis of google colaboratory as a tool for accelerating deep learning applications. Ieee Access, 6, 61677-61685. https://doi.org/10.1109/access.2018.2874767
Duda, M., Sovacool, K., Farzaneh, N., Nguyen, V., Haynes, S., Falk, H., Furman, K., Walker, L., Diao, R., Oneka, M., Drotos, A., Woloshin, A., Dotson, G., Kriebel, A., Meng, L., Thiede, S., Lapp, Z., & Wolford, B. (2021). Teaching Python for Data Science: Collaborative development of a modular interactive curriculum. Journal of Open Source Education, 4(46), 138. https://doi.org/10.21105/jose.00138
Guggemos, J. (2021). On the predictors of computational thinking and its growth at the high-school level. Computers & Education, 161, 104060. https://doi.org/10.1016/j.compedu.2020.104060
Hake, R. R. (1998). Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses. American Journal of Physics, 66(1), 64–74. https://doi.org/10.1119/1.18809
Hoppe, H. U. & Werneburg, S. (2019). Computational Thinking—More Than a Variant of Scientific Inquiry! Computational Thinking Education, 13–30. https://doi.org/10.1007/978-981-13-6528-7_2
Ismail, R. N., Mudjiran, & Neviyarni. (2019). Membangun Karakter Melalui Implementasi Teori Belajar Behavioristik Pembelajaran Matematika Berbasis Kecakapan Abad 21. MENARA Ilmu, XIII(11).
Izzah, N. A., Suwaibatulilla, A., Khasfiyatin, S., Jayati, R. T., & Supeno, S. (2023). Profil Computational Thinking Skill Siswa SMP dalam Pembelajaran IPA. Jurnal Paedagogy, 10(4), 1218. https://doi.org/10.33394/jp.v10i4.9193
Kilbane, C . R & Millman, N. B. (2014). Teaching Models : Designing Instruction for 21st Century Learners. New York. Pearson.
Kim, B., & Henke, G. (2021). Easy-to-use cloud computing for teaching data science. Journal of Statistics and Data Science Education, 29(sup1), S103-S111. https://doi.org/10.1080/10691898.2020.1860726
Li, Y., Schoenfeld, A. H., diSessa, A. A., Graesser, A. C., Benson, L. C., English, L. D., & Duschl, R. A. (2020). Computational Thinking Is More about Thinking than Computing. Journal for STEM Education Research, 3(1), 1–18. https://doi.org/10.1007/s41979-020-00030-2
Marchelin, L. E., Hamidah, D., & Resti, N. C. (2022). Efektivitas Metode Scaffolding Dalam Meningkatkan Kemampuan Berpikir Komputasi Siswa Smp Pada Materi Perbandingan. Jurnal Pengembangan Pembelajaran Matematika, 4(1), 16–29. https://doi.org/10.14421/jppm.2022.41.16-29
Mardhiyah, R. H., Aldriani, S. N. F., Chitta, F., & Zulfikar, M. R. (2021). Pentingnya Keterampilan Belajar di Abad 21 sebagai Tuntutan dalam Pengembangan Sumber Daya Manusia. Lectura: Jurnal Pendidikan, 12(1), 29–40. https://doi.org/10.31849/lectura.v12i1.5813
Nelson, M. J., & Hoover, A. K. (2020, June). Notes on using Google Colaboratory in AI education. In Proceedings of the 2020 ACM conference on innovation and Technology in Computer Science Education (pp. 533-534). https://doi.org/10.1145/3341525.3393997
Nyutu, E., Cobern, W. W., & Pleasants, B. A.-S. (2020). Correlational Study of Student Perceptions of their Undergraduate Laboratory Environment with respect to Gender and Major. International Journal of Education in Mathematics, Science and Technology, 9(1), 83–102. https://doi.org/10.46328/ijemst.1182
Pérez-Marín, D., Hijón-Neira, R., Bacelo, A., & Pizarro, C. (2020). Can computational thinking be improved by using a methodology based on metaphors and scratch to teach computer programming to children? Computers in Human Behavior, 105, 105849. https://doi.org/10.1016/j.chb.2018.12.027
Rambe, Y. A., Silalahi, A., & Sudrajat, A. (2020). The Effect of Guided Inquiry Learning Model and Critical Thinking Skills on Learning Outcomes. Proceedings of the 5th Annual International Seminar on Transformative Education and Educational Leadership (AISTEEL 2020). https://doi.org/10.2991/assehr.k.201124.033
Ridlo, Z. R. ., Dafik, Waluyo, J. ., & Yushardi. (2024). Exploring the impact of makerspace-based learning materials on students’ computational thinking skills: Using machine learning to address challenges in smart coffee agroforestry. Edelweiss Applied Science and Technology, 8(5), 52–73. https://doi.org/10.55214/25768484.v8i5.1630
Ridlo, Z. R., Supeno, S., Wahyuni, S., Wicaksono, I., & Ulfa, E. M. (2022). Analysis of Implementation Project-Based Learning Model of Teaching Integrated with Computer Programming in Improving Computational Thinking Skills in a Classical Mechanics Course. Jurnal Penelitian Pendidikan IPA, 8(4), 2029–2035. https://doi.org/10.29303/jppipa.v8i4.1789
Romadhona, R. R., & Suyanto, S. (2020). Enhancing integrated science process skills: Is it better to use open inquiry or guided inquiry model?. Biosfer: Jurnal Pendidikan Biologi, 13(2), 307- 319. https://doi.org/10.21009/biosferjpb.v13n2.307-319
Saldo, I. J. P., & Walag, A. M. P. (2020). Utilizing problem-based and project-based learning in developing students’ communication and collaboration skills in physics. American Journal of Educational Research, 8(5), 232-237. https://doi.org/10.12691/education-8-5-1
Siahaan, K. W. A., Lumbangaol, S. T. P., Marbun, J., Nainggolan, A. D., Ritonga, J. M., & Barus, D. P. (2020). Pengaruh Model Pembelajaran Inkuiri Terbimbing dengan Multi Representasi terhadap Keterampilan Proses Sains dan Penguasaan Konsep IPA. Jurnal Basicedu, 5(1), 195–205. https://doi.org/10.31004/basicedu.v5i1.614
Sinaga, A. V. (2023). Peranan teknologi dalam pembelajaran untuk membentuk karakter dan skill peserta didik abad 21. Journal on Education, 6(1), 2836-2846.
Tock, K. (2019). Google CoLaboratory as a platform for Python coding with students. RTSRE Proceedings, 2(1). https://doi.org/10.32374/rtsre.2019.013
Ulfa, E. M., Wahyuni, S., & Ridlo, Z. R. (2023). Development of E-Module-Based PjBL to Develop Computational Thinking Skills Integrategration with CCR Implementation in Science Education. JPPS (Jurnal Penelitian Pendidikan Sains), 12(2), 176–191. https://doi.org/10.26740/jpps.v12n2.p176-191
Wicaksono, I., & Erlina, N. (2024). The Effect of Virtual Science Teaching Model on Scientific Creativity and Learning Outcomes. Jurnal Pendidikan MIPA, 25(1), 440–452. https://doi.org/10.23960/jpmipa/v25i1.pp440-452
Wing, J. (2017). Computational thinking’s influence on research and education for all. Italian Journal of Educational Technology, 25(2), 7-14. https://doi.org/10.17471/2499-4324/922
Wing, J. M. 2006. Computational thinking. Communications of the ACM. 49(3): 33–35. https://doi.org/10.1145/1118178.1118215
Yona Ratri, A., Aristya Putra, P. D., Rusdianto, R., & Nuha, U. (2024). Pengembangan Modul Berbasis Engineering Design Process (EDP) dalam Meningkatkan Keterampilan Berpikir Kreatif Siswa SMP Pada Pembelajaran IPA. Jurnal Sains Dan Edukasi Sains, 7(2), 105–111. https://doi.org/10.24246/juses.v7i2p105-111
Published
2024-12-20
How to Cite
Ningsih, S., Ridlo, Z., Rusdianto, R., & Dewi, J. (2024). Implementation of Science Module Integrated with Google Colaboratory to Improve Students’ Computational Thinking Skill. Is it Effective?. Pedagogi: Jurnal Ilmu Pendidikan, 24(2). https://doi.org/https://doi.org/10.24036/pedagogi.v24i2.2287
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Article
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