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All Journal Jurnal Infinity at-tamkin: Jurnal Pengabdian kepada Masyarakat Alifmatika: Jurnal Pendidikan dan Pembelajaran Matematika INSECTA: Integrative Science Education and Teaching Activity Journal InEJ: Indonesian Engagement Journal Jurnal Kolaboratif Sains Teknikom: Teknologi Informasi, Ilmu Komputer dan Manajemen JIPI (Jurnal Ilmiah Pendidikan Islam) Jurnal Edukasi Pengabdian Masyarakat: EDUABDIMAS Journal of Elementary School Jurnal Infinity
Moh Khoridatul Huda, Moh Khoridatul
Universitas Islam Raden Rahmat Malang
Religion Agriculture, Biological Sciences & Forestry Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Health Professions Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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A learning trajectory for developing computational thinking in prospective mathematics teachers through Python programming in Google Colab Irawan, Edi; Huda, Moh. Khoridatul; Purwasih, Ratni
Alifmatika (Jurnal pendidikan dan pembelajaran Matematika) Vol 7 No 1 (2025): Alifmatika - June
Publisher : Fakultas Tarbiyah Universitas Ibrahimy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/alifmatika.2025.v7i1.34-52

Abstract

Computational thinking (CT) is a fundamental skill that needs to be developed by prospective mathematics teachers to improve problem-solving and logical reasoning. Integrating programming into mathematics learning is an effective approach to training this skill. This study aimed to design a hypothetical learning trajectory (HLT) for developing CT using Python programming on Google Colab. This study used a didactical design research (DDR) framework consisting of three stages: prospective analysis, metapedadidactic analysis, and retrospective analysis. The research participants were prospective mathematics teacher students enrolled in a computer programming course. Data were collected through observation, code artefacts, and reflective interviews. The results showed that HLT, designed in stages, improved the four main components of CT: decomposition, abstraction, pattern recognition, and algorithmic thinking. The students experienced improvements in breaking down problems, devising more efficient solutions, recognising patterns in code structures, and systematically designing algorithms. In addition, Google Colab supports learning by providing a collaborative and accessible programming environment. However, minor syntax errors and lack of attention to indentation were found. This study recommends using structured debugging strategies and project-based learning in optimizing CT development. The findings indicate that the integration of programming into the education of prospective mathematics teachers can equip them with essential CT skills to support technology-based mathematics teaching.
Co-Authors Dewi Erla Mahmudah Dewi Erla Mahmudah, Dewi Erla Dwi Candra Setiawan Edi Irawan Fidia Deny Tisna Amijaya Firdausi, Rofiqoh Hadi Jayusman Imam, Atim Nurchoirul Iza, Belgis Ainatul Jamaliatul Badriyah Janah, Siska Maghfirotul Laili Kartika, amalia Khusniyah, Lailatul Nurul Laili Ratna Dwi Christyanti, Ratna Dwi Ratni Purwasih, Ratni Rian Ardianto Rohman, Ahmad Fiki Fatkur Rosyid Ridlo Al-Hakim Saifuddin Salsabila, Zulfa Qomariyah Usman