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Anggun Badu Kusuma
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AlphaMath: Journal of Mathematics Education
Published by Universitas Muhammadiyah Purwokerto
ISSN : 2477409X     EISSN : 25499084     DOI : https://doi.org/10.30595/alphamath
Core Subject : Education,
Mathematics
AlphaMath: Journal of Mathematics Education adalah jurnal pendidikan matematika yang menyajikan artikel hasil pemikiran dan penelitian serta perkembangan mutakhir. Alphamath merupakan jurnal peer reviewed dan open access. Alphamath diterbitkan oleh Prodi Pendidikan Matematika Universitas Muhammadiyah Purwokerto. Alphamath mengundang para guru/pendidik matematika di sekolah, dosen, pengamat, dan peneliti pendidikan matematika di seluruh dunia untuk bertukar pikiran dan memajukan keilmuan di bidang pendidikan matematika. Cakupan dan lingkup penelitian meliputi: kurikulum pendidikan matematika, pembelajaran matematika yang inovatif dan kreatif, media pembelajaran matematika, penilaian dan evaluasi pembelajaran matematika, lesson study, kemampuan berpikir matematis, dan ICT dalam pembelajaran matematika.
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 193 Documents
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Mathematical Literacy Assessment: A Scalable Mobile Adaptive Blueprint for Mapping Proficiency Across PISA Domains Falani Falani; Syamsir Sainuddin
AlphaMath : Journal of Mathematics Education Alphamath: Vol. 12, No. 1, May 2026
Publisher : Department of Mathematics Education, Universitas Muhammadiyah Purwokerto, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/alphamath.v12i1.30279

Abstract

Indonesian students continue to struggle with mathematical literacy, as demonstrated across several cycles of PISA assessments. This study addresses this gap by applying a Rasch-based diagnostic approach to map patterns of item difficulty and examine how students across different grade levels engage with key indicators and content domains. A total of 271 students in Grades VII to IX from Indonesian public schools completed a 32-item multiple-choice test aligned with the PISA indicators of Formulating, Employing, Interpreting, and Reasoning. The instrument was specifically designed to capture different cognitive levels and situational contexts within the mathematical literacy framework. Rasch analysis was used to evaluate person ability, item difficulty, model fit, and measurement assumptions. The model showed strong empirical evidence, with a person reliability of 0.85, item reliability of 0.98, and infit/outfit MNSQ values within the acceptable range (0.5 to 1.5), and no significant Differential Item Functioning was found across grade levels. Formulating was the most difficult indicator, while Interpreting was the easiest. Among the content domains, Space and Shape posed the greatest challenge, whereas Quantity was the most accessible domain. Grade VIII students demonstrated the highest mean ability, producing a non-linear pattern across grade levels, likely due to a shift in Grade IX toward procedural exam-oriented instruction that narrows the focus on high-order modeling skills. Findings suggest that difficulties in modelling and spatial reasoning arise from deeper conceptual issues rather than grade progression alone. These results highlight the need for instructional practices that place greater emphasis on modelling processes and spatial reasoning.
A Cognitive Cascade Analysis of High School Students’ Problem-Solving Difficulties in Algebraic Derivatives Yuliani Yuliani; Sudianto Sudianto; Mohamad Gilar Jatisunda
AlphaMath : Journal of Mathematics Education Alphamath: Vol. 12, No. 1, May 2026
Publisher : Department of Mathematics Education, Universitas Muhammadiyah Purwokerto, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/alphamath.v12i1.30312

Abstract

Mathematics instruction at the high school level generally continues to emphasize procedural mastery, so students’ problem-solving abilities are often assessed based on the accuracy of their final answers. Previous studies have tended to focus on procedural errors or students’ success rates, while studies that reveal the complete and meaningful process of students’ mathematical problem solving remain limited. Therefore, this study aims to explore students’ mathematical problem-solving processes in the topic of algebraic derivatives. This study employed a qualitative case study design with 32 twelfth-grade students. Data were collected through a written mathematical problem-solving test administered to all participants, followed by semi-structured interviews with a purposively selected group of students representing different problem-solving profiles. The data were analyzed thematically using NVivo to identify patterns in problem interpretation, mathematical modeling, solution strategies, mathematical communication, and the meaningful use of mathematics. The results showed that students’ main difficulty occurred at the mathematical modeling stage, where many students were unable to translate contextual information into appropriate algebraic representations before applying differentiation procedures. This difficulty triggered a chain reaction in subsequent stages, leading to the use of mechanical problem-solving strategies and affecting students’ mathematical communication and meaningful use of mathematics. This study confirms that mastery of derivative procedures does not guarantee meaningful problem solving. The findings imply the need for learning approaches that emphasize conceptual understanding, mathematical modeling, and reflection. They also open opportunities for further research based on learning interventions.
Revealing Students’ Computational Thinking Error Patterns in Solving Two-Variable Linear Inequality Systems Israil Sitepu; Delvi Kristiani Jaluhu; Sinta Dameria Simanjuntak; Ribka Kariani br Sembiring
AlphaMath : Journal of Mathematics Education Alphamath: Vol. 12, No. 1, May 2026
Publisher : Department of Mathematics Education, Universitas Muhammadiyah Purwokerto, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/alphamath.v12i1.30386

Abstract

This study aims to identify and describe patterns of students’ computational thinking errors in solving systems of linear inequalities in two variables. Specifically, it examines errors occurring at each stage of computational thinking, such as problem decomposition, pattern recognition, abstraction, and algorithm construction, as well as the underlying factors contributing to these errors. A qualitative descriptive approach was employed. The participants consisted of 36 tenth-grade students. Data were collected through written tests, observation, and semi-structured interviews to explore students’ cognitive processes in depth. The data were analyzed through data reduction, data display, and conclusion drawing. The findings indicate that students experienced errors at all stages of computational thinking. Students encountered difficulties identifying relevant information during problem decomposition, recognizing conceptual relationships during pattern recognition, transforming problems into appropriate mathematical representations during abstraction, and constructing systematic solution procedures during algorithm construction. These errors were primarily attributed to insufficient conceptual understanding, difficulties in interpreting problem statements, and limitations in formulating effective problem-solution strategies. These findings provide valuable insights into students’ learning difficulties and may serve as a foundation for designing more effective instructional strategies to enhance students’ computational thinking skills.

Page 20 of 20 | Total Record : 193

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