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Journal : Journal on Mathematics Education

Level of students' proportional reasoning in solving mathematical problems Sari, Riska Novia; Rosjanuardi, Rizky; Isharyadi, Ratri; Nurhayati, Aat
Journal on Mathematics Education Vol. 15 No. 4 (2024): Journal on Mathematics Education
Publisher : Universitas Sriwijaya in collaboration with Indonesian Mathematical Society (IndoMS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22342/jme.v15i4.pp1095-1114

Abstract

This study aimed to evaluate the level of proportional reasoning among middle school students in their ability to solve mathematical problems involving proportions. Proportional reasoning is essential for understanding and mastering various mathematical concepts, serving as a fundamental skill for higher-level mathematics. A qualitative case study design was employed, involving 28 eighth-grade students from a school in Bandung, Indonesia. The participants were assessed using a set of proportion-related problems, including numerical comparison, non-proportional (additive), direct proportion, and inverse proportion tasks. The analysis focused on categorizing the students' problem-solving strategies into distinct levels of proportional reasoning, ranging from non-proportional to formal proportional reasoning. Additionally, three students representing high, moderate, and low mathematical performance were selected for in-depth interviews to explore their reasoning processes when addressing proportion problems. Data analysis included administering tests, reviewing students' problem-solving strategies, conducting in-depth interviews, and evaluating their proportional reasoning abilities. The findings revealed that students with high and moderate mathematical performance exhibited proportional reasoning levels ranging from 0 to 3, whereas low-performing students displayed levels ranging from 0 to 2. Moreover, students generally faced difficulties distinguishing between proportional and non-proportional problems. Even when correct answers were provided, many lacked a deep understanding of direct and inverse proportion concepts. The study also discusses several implications for enhancing students' proportional reasoning skills.
How computational thinking can be integrated in statistical learning: A cuboid framework Irawan, Edi; Rosjanuardi, Rizky; Prabawanto, Sufyani
Journal on Mathematics Education Vol. 16 No. 2 (2025): Journal on Mathematics Education
Publisher : Universitas Sriwijaya in collaboration with Indonesian Mathematical Society (IndoMS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22342/jme.v16i2.pp423-448

Abstract

In the context of an increasingly data-intensive society, the integration of Computational Thinking (CT) into statistics education is essential to prepare students with the analytical and problem-solving competencies required for navigating complex data environments. Despite growing recognition of its importance, existing pedagogical practices frequently lack systematic didactical frameworks that effectively embed CT within statistical learning, particularly in higher education. Addressing this gap, the present study introduces a novel hypothetical didactical design—termed the Cuboid Framework—which systematically integrates CT components into the learning of descriptive statistics using the R programming language in a Google Colab environment. This research employed the Didactical Design Research (DDR) methodology, emphasizing the prospective and metapedadidactic stages to construct and evaluate the framework. Targeted at third-semester undergraduate students enrolled in an introductory statistics course, the Cuboid Framework aligns with learners’ developmental levels in both statistical reasoning and CT proficiency. The model is organized as a 5 × 4 × 4 structure, comprising five core statistical tasks, four structured didactical situations (action, formulation, validation, and institutionalization), and four CT elements (decomposition, pattern recognition, abstraction, and algorithmic thinking). Validation procedures included expert review through focus group discussions (FGDs) and an initial classroom implementation followed by metapedadidactic analysis. Findings reveal that the Cuboid Framework fosters a coherent learning progression, enhances students’ engagement in statistical inquiry, and supports the development of CT competencies. Classroom observations confirmed that the intentional design of didactical situations facilitates students’ cognitive adaptation to computational tasks. While preliminary analyses indicate strong theoretical and practical coherence, further retrospective studies and quantitative evaluations are necessary to ascertain the long-term effects on student learning outcomes. This study contributes a structured and theoretically grounded model for CT integration in statistics education, with implications for improving curriculum design and instructional practice in mathematics education. Future research should aim to test the scalability and efficacy of the Cuboid Framework across diverse educational settings.
Co-Authors Aflich Yusnita Fitrianna Aflich Yusnita Fitrianna Aflich Yusnita Fitrianna Agustian, Muhammad Rifqi Agustian, Muhammad Rifqi Albania, Imam Nugraha Andina Aulia Rachma Anggareni, Peni Ariany, Riva Lesta Aris Hadiyan Wijaksana Aswin Aswin Aziiza, Yushilatu Felayati Azizah, Firda Bilqis Azizah, Firda Bilqis Balkist, Pujia Dadang Juandi Dadang Juandi Darhim Darhim Delsika Pramata Sari Dewi, Reza Farhania DIAN LATIFAH, DIAN Didi Suryadi Didi Suryadi Dika Faiz Himmawan Edi Irawan Elah Nurlaelah Elah Nurlaelah Endang Cahya Mulyaning A. Entit Puspita Entit Puspita Eyus Sudihartinih Fitrianingsih, Ajeng Nur Aulia Harsa Wara Prabawa Imam N Albania Irham Walidaka Ishma Fadlina Urfa, Ishma Fadlina Isnie Yusnitha, Isnie Jarnawi Afgani Dahlan Kadir, Kamaliyah Kertayasa, I Ketut Khusnul Novianingsih Lovitarani, Destiana Lovitarani, Destiana LUKMAN, LUKMAN Maknun, Churun L Maknun, Churun Lu'lu'il Masta, Al Azhary Muhammad Awaludin Nasution Muhammad Fajar Anugrah Muhammad Nur Hidayat Taufiqurrahman Mulyaning Asih, Endang Cahya Mulyono, Budi Mursidah Mursidah Nadia Shabilla, Nadia Nanang Priatna Nunung Nurhidayah, Nunung Nurhayati, Aat Nurhuda Teapon Panjaitan, M. Azhari Prabawa, Harsa Wara Rachma, Andina Aulia Ratri Isharyadi, Ratri Reka Ikraami Kurniawan Rekha Bestari Martista Reni Nuraeni, Reni Rini Marwati Ririn Sispiyati Riska Novia Sari, Riska Novia Riva Lesta Ariany Rizza Lestari Rudi Rudi Rudi Rudi Sardin Solly Aryza Sufyani Prabawanto, Sufyani Sugianto, Andi Suhendra, S Sumanang Muhtar Gozali Surachman, Annisanti Surachman, Annisanti Surya Kurniawan Syafdi Maizora Thesa Kandaga Toto Subroto Wijaksana, Aris Hadiyan Yaya S Kusumah Yaya S. Kusumah Yuliardi, Ricki Yushilatu Felayati Aziiza