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Jurnal Riset Pendidikan dan Inovasi Pembelajaran Matematika (JRPIPM)
Published by Universitas Negeri Surabaya
ISSN : -     EISSN : 25810480     DOI : -
Core Subject : Education, Social,
Education Mathematics Social Sciences
Jurnal Riset Pendidikan dan Inovasi Pembelajaran Matematika (JRPIPM) is a peer-refereed open-access journal which has been established for the dissemination of state-of-the-art knowledge in the field of mathematics education both theory and practice. This Journal is published periodically twice a year (April and September) by Universitas Negeri Surabaya with E-ISSN:2581-0480.
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 175 Documents
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Identification of Computational Thinking Patterns in Students’ Mathematical Problem Solving: Empirical Evidence from Algebra Learning Activities Qolfathiriyus Firdaus, Ahmad; Suryanti, Sri; Hadi, Fais Nurul
Jurnal Riset Pendidikan dan Inovasi Pembelajaran Matematika Vol. 10 No. 1 (2026): JRPIPM APRIL 2026
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jrpipm.v10n1.p22-32

Abstract

Computational thinking (CT) is increasingly recognized as a core competency in STEM education, yet little empirical evidence exists on how CT patterns naturally emerge in algebraic reasoning outside programming contexts. This study investigates how secondary students demonstrate CT components during algebra problem-solving. A mixed-methods design was applied with 120 students completing algebra tasks. Data were collected through assessments, interviews, and classroom observations. The elements of CT, namely pattern recognition, decomposition, abstraction, and algorithmic reasoning, are systematically coded and analyzed using qualitative and quantitative approaches. Findings revealed that pattern recognition (80%) and decomposition (70%) were widely observed across achievement levels. In contrast, abstraction (45%) and algorithmic reasoning (35%) appeared more frequently among high-achieving students. Statistical analysis confirmed significant differences in CT sophistication across achievement groups, highlighting progression from basic recognition to advanced reasoning. The novelty of this study lies in its empirical demonstration of CT within algebraic problem-solving, independent of programming environments. Unlike prior research emphasizing coding, it shows how CT components naturally emerge in mathematics tasks. By analyzing achievement-level differences, it provides fresh evidence of developmental trajectories in CT. These results position algebra as a strategic entry point for CT development, bridging mathematical reasoning and computational approaches. They suggest that intentional pedagogical design can foster advanced CT skills in conventional classrooms, offering practical guidance for curriculum innovation in mathematics education.
Applying Binary Logistic Regression to Map Cognitive Styles Based on Students’ Errors in Algebraic Thinking Generalization Problems According to Newman’s Theory Rizki, Nanda Arista; Cahyaningrum, Gyta Krisdiana; Mumtaza, Mutiara
Jurnal Riset Pendidikan dan Inovasi Pembelajaran Matematika Vol. 10 No. 1 (2026): JRPIPM APRIL 2026
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jrpipm.v10n1.p48-58

Abstract

Algebraic generalization problems pose a significant challenge, requiring teachers to recognize influencing factors like Field Independent (FI) and Field Dependent (FD) cognitive styles. The purpose of this study was to apply binary logistic regression to map students' cognitive styles, either FI or FD, based on their error patterns when solving algebraic thinking generalization problems. These errors were classified using the five categories of Newman’s Theory: Reading (R), Comprehension (C), Transformation (T), Process Skill (S), and Encoding (E). This exploratory correlational study involved 40 tenth-grade students from SMA IT Granada Samarinda. Cognitive style (the dependent variable) was measured using the GEFT, while the Newman error categories (the independent variables) were identified from a generalization instrument adopted from TIMSS (2003–2019). The results found that 23 out of 40 students made mistakes, consisting of 9 FI students and 31 FD students. The binary logistic regression results showed that the Process Skill (S) error was the strongest predictor for the FI style, with an odds ratio of 18.025. This means that students who make an S error are 18 times more likely to be classified as FI. This finding leads to the conclusion that FI students struggle with the details of procedural implementation, despite possessing a strong strategic understanding. Binary logistic regression proved effective as a diagnostic tool to support more personalized mathematics learning strategies.
Analytic Reasoning Process of High School Students In Solving Quadratic Equation Problems Based on Computational Thinking Skills Lestari, Ayu Chinintya; Fatoni, Yusril Achmad; Nusantara, Toto; Musar, Makbul
Jurnal Riset Pendidikan dan Inovasi Pembelajaran Matematika Vol. 10 No. 1 (2026): JRPIPM APRIL 2026
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jrpipm.v10n1.p59-73

Abstract

Analytical reasoning and computational thinking are two essential skills in mathematics education, especially in solving complex problems such as quadratic equations. This study aims to describe the analytical reasoning process of high school students in solving quadratic equation problems based on computational thinking skills. This study employs a descriptive qualitative approach, with data collected through tests and interviews with 30 students at a high school in Jember, categorized into three levels of computational thinking skill: high (S1), moderate (S2), and low (S3). One subject from each category was selected as a representative for in-depth analysis based on analytical reasoning indicators adapted from Fisher (2011), namely: problem identification, relationship analysis, strategy formulation, and solution evaluation and justification. The research results indicate that S1 demonstrates coherent and flexible analytic reasoning, characterized by precise problem identification, accurate model formation, adaptive strategy use, and implicit verification of results. S2 showed generally systematic reasoning, especially in translating contextual information into algebraic models and performing procedural operations. However, their analytic reasoning tended to rely on fixed procedures, with limited evaluative judgment or strategic adaptation. In contrast, S3 exhibited fragmented reasoning, difficulties in constructing symbolic models, and minimal solution validation, often caused by challenges in decomposing information and analyzing relational structures. These findings provide insights that can help teachers design more adaptive and effective learning strategies to encourage higher-order thinking skills in students.
The Impact of Ethnomathematics Approach on Numeracy and Mathematical Reasoning Skills of Elementary School Students: A Systematic Literature Review Utami, Nia Diyawati; Mariana, Neni; Ekawati, Rooselyna
Jurnal Riset Pendidikan dan Inovasi Pembelajaran Matematika Vol. 10 No. 1 (2026): JRPIPM APRIL 2026
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jrpipm.v10n1.p74-89

Abstract

This systematic literature review examines the effects of ethnomathematics-based approaches on numeracy and mathematical reasoning skills among elementary school students. The review analyzed 18 empirical studies and meta-analyses published between 2022 and 2025 to capture recent evidence aligned with contemporary educational contexts and pedagogical practices. Using PRISMA guidelines, quantitative and qualitative findings from quasi-experimental, mixed-method, and meta-analytic studies were synthesized. This review addresses a notable research gap, as recent literature has not comprehensively examined the combined impact of ethnomathematics on both numeracy and mathematical reasoning at the elementary level. The findings consistently demonstrate that ethnomathematics-based instruction significantly improves students’ numeracy achievement and mathematical reasoning abilities. Meta-analytic results indicate strong to very strong effect sizes (ES = 1.22–1.42) on mathematical achievement. Culturally contextualized learning also enhances conceptual understanding, critical thinking, collaboration skills, and learning motivation. Positive effects are reported across grade levels and cultural contexts, with moderate to high improvements in numeracy outcomes. Various implementation modalities, including interactive digital media, traditional games, STEAM-oriented instruction, and culturally relevant learning modules, show high instructional validity and effectiveness. However, several studies exhibit methodological limitations, such as small sample sizes, limited use of control groups, and insufficient longitudinal analysis. Future research should prioritize large-scale and longitudinal studies, alongside systematic teacher professional development, to support the sustainable integration of ethnomathematics in elementary mathematics education.
A Phenomenological Study of Pre-service Teachers’ Readiness in Integrating Digital Literacy for Mathematics Assessment Hanifah, Umi; Masriyah; Sari, Ayu Silvi Lisvian; Saadah, Nurus; Cahyani, Jessica Dwi Nur
Jurnal Riset Pendidikan dan Inovasi Pembelajaran Matematika Vol. 10 No. 1 (2026): JRPIPM APRIL 2026
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jrpipm.v10n1.p90-102

Abstract

Digital literacy has become an essential competence for mathematics educators, particularly in the domain of assessment. This study aims to explore the lived experiences and readiness of pre-service mathematics teachers in integrating digital literacy into mathematics assessment practices. The research employed a transcendental phenomenological approach to capture the essence of participants’ experiences in designing and implementing digital-based assessments. The participants consisted of six final-year pre-service mathematics teachers from two Indonesian universities who had experience developing digital assessment tasks during their teaching practice. Data were collected through semi-structured interviews, classroom observations, and analysis of digital assessment artifacts, including GeoGebra-based activities and Quizizz assessments. The data were analyzed using a phenomenological reduction process involving epoché, horizonalization, clustering of meaning units, and synthesis of the essence of the phenomenon. The findings reveal that although pre-service teachers demonstrate strong operational skills in using digital tools, their readiness to design meaningful digital mathematics assessments varies. Three main themes emerged from the analysis: technological fluency, pedagogical considerations in digital assessment design, and alignment between digital tools and assessment rubrics. The results indicate that readiness to integrate digital literacy in mathematics assessment involves not only technical competence but also the integration of pedagogical reasoning and assessment literacy. These findings highlight the importance of integrating digital assessment training within teacher education programs to better prepare future mathematics teachers for technology-supported assessment practices.

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