Canva AI: Untuk Mengeksplorasi Computational Thinking Siswa Sekolah Dasar
UNTUK MENGEKSPLORASI COMPUTATIONAL THINKING SISWA SEKOLAH DASAR
DOI:
https://doi.org/10.30587/didaktika.v31i2.10138Keywords:
Computational Thinking, Canva AI, Learning MediaAbstract
Education in the digital era demands that students not only absorb information but also develop higher-order thinking skills to solve problems systematically. One essential skill in this context is Computational Thinking (CT), which includes decomposition, pattern recognition, abstraction, and algorithmic thinking. The Kurikulum Merdeka emphasizes the importance of mastering CT from the elementary school level. However, low levels of digital literacy and systematic thinking among Indonesian students remain a significant challenge in educational practice. This study aims to: (1) describe the use of Canva AI in exploring CT among elementary students, (2) identify the obstacles encountered when using Canva AI as a learning tool, and (3) describe the solutions applied by teachers to overcome these challenges. This research employed a descriptive qualitative approach using a case study method conducted at SD Negeri Karangbong. Data were collected through direct observation, interviews with the teacher, and documentation of student assignments, and then analyzed using the Miles and Huberman interactive model. The findings indicate that Canva AI features, such as Magic Media and Magic Write, significantly support the development of students’ CT skills. Nevertheless, technical challenges were observed, including limited access to devices and educational accounts. The teacher addressed these issues through collaborative learning strategies, organizing students into groups and providing access via personal or school accounts. Overall, Canva AI has proven to be an effective, innovative, and relevant learning medium for 21st-century classroom practices at the elementary school level
References
Angeli, C., & Giannakos, M. (2020). Computational thinking education: Issues and challenges. Computers in Human Behavior, 105. https://doi.org/10.1016/j.chb.2019.106185
Chyalutfa, U., Makki, M., & Syahrul Jiwandono, I. (2022). Pengaruh Penggunaan Media Pohon Literasi Terhadap Hasil Belajar Bahasa Indonesia Siswa. Journal of Classroom Action Research, 4(3), 82–86. https://doi.org/10.29303/jcar.v4i3.1913
Kemendikbud. (2022). Panduan Implementasi Kurikulum Merdeka.
Novianti, N., & Dewi, N. (2023). Upaya Meningkatkan Computational Thinking dalam Pembelajaran IPA melalui Penerapan Aplikasi Canva. Report of Biological Education, 4(1), 32–46.
Saputra, A. G., Rahmawati, T., Andrew, B., & Amri, Y. (2022). Using Canva Application for Elementary School Learning Media. Scientechno: Journal of Science and Technology, 1(1), 46–57. https://doi.org/10.55849/scientechno.v1i1.4
Siahaan, S. M., Sudirman, S., Ariska, M., Desti, M. A., & Sari, M. (2020). Analisis Pendampingan Pembelajaran Inspiratif Secara Online Melalui Media Presentasi Canva Untuk Guru-Guru Mgmp Fisika Kab. Musi Rawas. Wahana Dedikasi : Jurnal PkM Ilmu Kependidikan, 3(2), 29. https://doi.org/10.31851/dedikasi.v3i2.4948
Wiharyanti, N., & Mulyono, R. (2023). Penggunaan Metode Bermain Dengan Kartu Kata Untuk Meningkatkan Kemampuan Membaca Anak. Prima Magistra: Jurnal Ilmiah Kependidikan, 4(3), 229–237. https://doi.org/10.37478/jpm.v4i3.2634
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