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Ethnomathematics Exploration of Geometry Concepts in Traditional Games in Karanganyar Regency Aulya, Sholihatun Nisa; Exacta, Annisa Prima
Jurnal Pendidikan, Sains Sosial, dan Agama Vol. 11 No. 1 (2025): Jurnal Pendidikan, Sains Sosial, dan Agama Vol 11 No 1
Publisher : STABN RADEN WIJAYA WONOGIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53565/pssa.v11i1.1711

Abstract

The purpose of this study is to describe the concept of geometry concepts contained in traditional games in Karanganyar Regency such as: engklek, kites, and marbles. This research uses qualitative research with an ethnographic approach. The data collection methods used in this research are observation, documentation and interviews. The results of this study indicate that in traditional games in Karanganyar district there is the concept of geometry. The geometry concepts contained are flat shapes (square, rectangle, triangle, kite, semicircle and circle), space shapes (tube and ball), geometry transformation (reflection), and congruence. The concept of geometry is illustrated in the game arena and game tools.
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