Analysis Of Computational Thinking Abilities Of High School Students Based On Self-Regulated Learning

Nadia Hanifah Sidik; Hikmatul  Khusna

doi:10.47435/jtmt.v5i1.2871

Nadia Hanifah Sidik Universitas Muhammadiyah Prof. DR. HAMKA
Hikmatul Khusna Universitas Muhamamdiyah Prof.Dr. Hamka

DOI: https://doi.org/10.47435/jtmt.v5i1.2871

Keywords: Computational thinking, self-regulated learning, high school students

Abstract

There is a phenomenon where students with moderate ability can achieve the highest rank in the class, while students with high intelligence often have difficulty or failure in their academic achievement. This suggests that students' abilities, no matter how high, will be limited if they are not able to self-regulate their learning. A descriptive qualitative research method was employed in this study, conducted in the XI MIPA class at a public high school in Bekasi. The research subjects were selected based on their SRL levels, categorized as high, medium, and low. Data were collected through interviews and CT tests, using data collection techniques such as observation, tests, and interviews. The results showed that students with high SRL levels excelled in all aspects of computational thinking assessment. Conversely, students with medium SRL levels only demonstrated abilities in three out of four indicators: decomposition, abstraction and generalization, and pattern recognition. Meanwhile, students with low SRL levels only showed abilities in one indicator, which was pattern recognition

Downloads

Download data is not yet available.

References

Ansori, M. (2020). Pemikiran Komputasi (Computational Thinking) dalam Pemecahan Masalah. Dirasah : Jurnal Studi Ilmu Dan Manajemen Pendidikan Islam, 3(1), 111–126. https://doi.org/10.29062/dirasah.v3i1.83

Ariesandi, I., Syamsuri, Yuhana, Y., & Fatah, A. (2021). Analisis kebutuhan pengembangan modul elektronik berbasis inkuiri untuk meningkatkan kemampuan berpikir komputasi pada materi barisan dan deret siswa SMA. Aksioma: Jurnal Matematika Dan Pendidikan Matematika, 12(2), 178–190. http://103.98.176.9/index.php/aksioma/article/view/7793%0Ahttp://103.98.176.9/index.php/aksioma/article/download/7793/4579

Cahdriyana, R. A., & Richardo, R. (2020). Berpikir Komputasi Dalam Pembelajaran Matematika. LITERASI (Jurnal Ilmu Pendidikan), 11(1), 50. https://doi.org/10.21927/literasi.2020.11(1).50-56

Christi, S. R. N., & Rajiman, W. (2023). Pentingnya Berpikir Komputasional dalam Pembelajaran Matematika. 05(04), 12590–12598.

Concannon, J. P., Serota, S. B., Fitzpatrick, M. R., & Brown, P. L. (2019). How Interests, self-efficacy, and self-regulation impacted six undergraduate pre-engineering students’ persistence. European Journal of Engineering Education, 44(4), 484–503. https://doi.org/10.1080/03043797.2017.1422695

Firdaus, S., Rachman, L., & Firmansyah, M. (2020). Analisa Faktor Pengaruh Self-regulated learning Terkait Performance Goals terhadap Prestasi Akademik. Jurnal Kedokteran Komunitas, 8(2), 94–100. http://www.riset.unisma.ac.id/index.php/jkkfk/article/view/8004/6553

Hadin, H., Pauji, H. M., & Aripin, U. (2018). Analisis Kemampuan Koneksi Matematik Siswa Mts Ditinjau Dari Self Regulated Learning. JPMI (Jurnal Pembelajaran Matematika Inovatif), 1(4), 657. https://doi.org/10.22460/jpmi.v1i4.p657-666

Hendrika, D. S. (2022). Gambaran Self Regulated Learning Pada Mahasiswa Di Masa Pandemi Covid-19. Educativo: Jurnal Pendidikan, 1(1), 68–74. https://doi.org/10.56248/educativo.v1i1.10

Jamna, N. D., Hamid, H., & Bakar, M. T. (2022). Analisis Kemampuan berpikir Komputasi Matematis Siswa SMP pada Materi Persamaan Kuadrat. Jurnal Pendidikan Guru Matematika, 2(3). https://doi.org/10.33387/jpgm.v2i3.5149

Lestari, A. C., & Annizar, A. M. (2020). Proses Berpikir Kritis Siswa dalam Menyelesaikan Masalah PISA Ditinjau dari Kemampuan Berpikir Komputasi. Jurnal Kiprah, 8(1), 46–55. https://doi.org/10.31629/kiprah.v8i1.2063

Lestari, Si., & Roesdiana, L. (2023). Analisis Kemampuan Berpikir Komputasional Matematis Siswa Pada Materi Program Linear. RANGE: Jurnal Pendidikan Matematika, 4(3), 178–188.

Litia, N., & Sinaga, B. (2023). Profil Berpikir Komputasi Siswa dengan Menggunakan Model Pembelajaran Problem Based Learning ( PBL ) Ditinjau dari Gaya Belajar di SMA N 1 Langsa. 07(March), 1508–1518.

M. Gunawan Supiarmo, Sholikin, N. W., Harmonika, S., & Gaffar, A. (2022). Implementasi Pembelajaran Matematika Realistik Untuk Meningkatkan Kemampuan Berpikir Komputasional Siswa. Numeracy, 9(1), 1–13. https://doi.org/10.46244/numeracy.v9i1.1750

Nuraisa, D., Saleh, H., & Raharjo, S. (2021). Profile of Students’ Computational Thinking Based on Self-regulated learning in Completing Bebras Tasks. Prima: Jurnal Pendidikan Matematika, 5(2), 40. https://doi.org/10.31000/prima.v5i2.4173

Nuvitalia, D., Saptaningrum, E., Ristanto, S., & Putri, M. R. (2022). Profil Kemampuan Berpikir Komputasional (Computational Thinking) Siswa SMP Negeri Se-Kota Semarang Tahun 2022. Jurnal Penelitian Pembelajaran Fisika, 13(2), 211–218. https://doi.org/10.26877/jp2f.v13i2.12794

Park, Y.-S., & Green, J. (2019). Bringing Computational Thinking into Science Education. Journal of the Korean Earth Science Society, 40(4), 340–352. https://doi.org/10.5467/jkess.2019.40.4.340

Rijal Kamil, M., Ihsan Imami, A., Prasetyo Abadi, A., Matematika, P., & Singaperbangsa Karawang, U. (2021). Analisis kemampuan berpikir komputasional matematis Siswa Kelas IX SMP Negeri 1 Cikampek pada materi pola bilangan. 12(2), 259–270.

Seixas, B. V., Smith, N., & Mitton, C. (2018). The qualitative descriptive approach in international comparative studies: Using online qualitative surveys. International Journal of Health Policy and Management, 7(9), 778–781. https://doi.org/10.15171/ijhpm.2017.142

Silvia, R. D., Siska, P. A., & Nizaruddin, N. (2023). ANALISIS KEMAMPUAN COMPUTATIONAL THINKING SISWA PADA MATERI ALJABAR DITINJAU DARI PEMECAHAN MASALAH MATEMATIS Pendidikan Matematika , Universitas PGRI Semarang Dari studi PISA pada tahun 2018 diketahui bahwa dari 79 negara yang dijadikan objek kajian , ke. 5(2), 176–190.

State, C. R., Offiah, C. I., & State, C. R. (2018). Self-Regulatory Attributes and Academic Performance in Mathematics among Secondary School Students in Enugu Education Zone , Enugu State. 11(September), 455–466.

Supiarmo, M. G., Mardhiyatirrahmah, L., & Turmudi, T. (2021). Pemberian Scaffolding untuk Memperbaiki Proses Berpikir Komputasional Siswa dalam Memecahkan Masalah Matematika. Jurnal Cendekia : Jurnal Pendidikan Matematika, 5(1), 368–382. https://doi.org/10.31004/cendekia.v5i1.516

Tsai, C. W., Shen, P. Di, Tsai, M. C., & Chen, W. Y. (2017). Exploring the effects of web-mediated computational thinking on developing students’ computing skills in a ubiquitous learning environment. Interactive Learning Environments, 25(6), 762–777. https://doi.org/10.1080/10494820.2016.1181093

Vivied Eka Pratiwi, & Ayu Tsurayya. (2023). Analisis Kemampuan Pemahaman Konsep Ditinjau Dari Kecerdasan Logis Matematis Pada Materi Fungsi Komposisi. JTMT: Journal Tadris Matematika, 4(1), 94–102. https://doi.org/10.47435/jtmt.v4i1.1820

Winda, A., & Hendro, U. F. (2022). Analisis Kemampuan Berpikir Kritis Matematis Pada Materi Trigonometri Berdasakan Self-regulated learning. GAUSS: Jurnal Pendidikan Matematika, 5(2), 78–91. https://doi.org/10.30656/gauss.v5i2.5263

Zahary, M. (2015). Meningkatkan Prestasi Belajar Matematika Siswa Melalui Strategi Self Regulated Learning. Seminar Nasional Matematika Dan Pendidikan Matematika Uny, 24(Pasal 3), 163–168.