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All Journal Educate: Journal of Community Service in Education Cognitive Development Journal
Muhammad Zain Musa
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Computer Science & IT Education Languange, Linguistic, Communication & Media Social Sciences Other

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Cybernetic-Based Numeracy Empowerment for Secondary Mathematics Teachers: A Community Engagement Perspective Exacta, Annisa Prima; Muhammad Zain Musa; Erika Laras Astutiningtyas; Andhika Ayu Wulandari; Krisdianto Hadiprasetyo
Educate: Journal of Community Service in Education Vol 4 No 2 (2024): December
Publisher : Universitas Veteran Bangun Nusantara

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Abstract

This article presents a community engagement-based research initiative aimed at enhancing numeracy competence among senior high school teachers in Indonesia through a cybernetic pedagogy framework. Conducted at SMA Negeri 1 Nguter, the program combined theoretical workshops, digital tool integration, and cross-disciplinary lesson design to empower teachers in embedding numeracy across various subjects. A mixed-methods approach—comprising pre- and post-tests, structured mentoring, classroom observations, and reflective journals—revealed significant improvements in teachers' conceptual understanding, pedagogical confidence, and instructional practices. The findings demonstrate that cybernetic-based teaching fosters interactive, data-driven learning environments and supports numeracy as a transversal 21st-century skill. This study contributes empirical insights into scalable, cross-national professional development models that can be adapted in resource-constrained educational contexts
Pre-Service Teachers and Computational Thinking: Designing Meaningful Learning in Higher Education Krisdianto Hadiprasetyo; Exacta, Annisa Prima; Muhammad Zain Musa; Salvador V. Briones II
Cognitive Development Journal Vol. 2 No. 2 (2024): Cognitive Development Journal
Publisher : Edutech Publishing Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32585/cognitive.v2i2.48

Abstract

This study aims to understand the students’ computational thinking skills in statistics. The type of research is descriptive with a qualitative approach. The data collection techniques in this study include 1) Tests; 2) Interviews; 3) Documentation; and 4) Validation Sheets. The data analysis in this study involves: 1) Data condensation; 2) Data presentation; 3) Verification; and 4) Conclusion drawing. The validity of the data in this study is ensured using the technique of triangulation. Subjects were selected using purposive sampling. The instruments used were two statistical problem-solving questions. The results showed that in solving the first and second questions, the respondents could address the problems using the components of Computational Thinking, starting with decomposition, abstraction, and algorithm tasks. However, the pattern recognition component was not evident in the problem-solving process, even though some respondents gave incorrect answers. This was because the respondents did not fully understand the questions. They only read the questions once or twice, so the information was not fully comprehended. Additionally, the respondents only considered the simplest path and overlooked more complex paths in solving the second question. Students can carry out abstraction and algorithmic tasks, but they still struggle with decomposition and pattern recognition. Keywords: student, mathematics, statistics, computational thinking, ability
Co-Authors Andhika Ayu Wulandari Erika Laras Astutiningtyas Exacta, Annisa Prima Hadiprasetyo, Krisdianto Salvador V. Briones II