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All Journal Journal of Didactic Mathematics JUPIKA: JURNAL PENDIDIKAN MATEMATIKA Plusminus: Jurnal Pendidikan Matematika International Journal of Progressive Mathematics Education Journal of Mathematics Instruction, Social Research and Opinion JNPM (Jurnal Nasional Pendidikan Matematika) Riemann : Research of Mathematics and Mathematics Education International Journal of Didactic Mathematics in Distance Education Indonesian Journal of Applied Mathematics and Statistics Jurnal Matematika Ilmiah Universitas Muhammadiyah Kuningan
Prihandhika, Aditya
Universitas Singaperbangsa Karawang
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Languange, Linguistic, Communication & Media Mathematics Public Health Social Sciences Other

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Procedural Dominance in Students’ Reasoning on the Limit Definition: Insights from a Ways of Thinking Framework Prihandhika, Aditya; Sopiany, Hanifah Nurus
Journal of Mathematics Instruction, Social Research and Opinion Vol. 4 No. 4 (2025): December
Publisher : MASI Mandiri Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58421/misro.v4i4.776

Abstract

This study explores university students’ ways of thinking about the limit concept in differential calculus and uncovers how they construct the meaning of the limit definition through their reasoning. Data were collected from 28 students in mathematics education at a university in West Java, Indonesia, through written tasks and semi-structured interviews. Thematic analysis identified dominant reasoning patterns, revealing that 71% of students exhibited procedural reasoning, 18% demonstrated conceptual reasoning, and 11% displayed formal reasoning. Based on a systematic data reduction process, these patterns were categorized into procedural, conceptual, and formal ways of thinking, and six representative participants were purposively selected for in-depth analysis. The findings show that students predominantly exhibited procedural reasoning, relying heavily on algorithmic manipulation and symbolic recall rather than conceptual understanding or formal justification. This pattern indicates that many students have not yet internalized the formal meaning of the limit definition, resulting in mechanical rather than reflective reasoning. These findings highlight the need for instructional designs that promote conceptual reflection and formal reasoning in calculus learning, enabling students to move beyond procedural competence toward a more integrated understanding of the limit concept.
Interpreting the ε–δ Definition: Hermeneutic Insights into Students’ Ways of Thinking Prihandhika, Aditya; Ramadani, Iqbal
Riemann: Research of Mathematics and Mathematics Education Vol. 8 No. 1 (2026): EDISI APRIL
Publisher : Program Studi Pendidikan Matematika Universitas Katolik Santo Agustinus Hippo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38114/riemann.v8i1.154

Abstract

This study aims to reveal the hermeneutic insight in the formation of students’ ways of thinking (WoT) toward the precise meaning of the limit concept in differential calculus. Formally, the concept of limit is defined through the relationship between ε (epsilon) and δ (delta), namely that for every ε > 0, there exists a δ > 0 such that if 0 < |x − a| < δ, then |f(x) − L| < ε, expressing a precise dependency between function values and domain values. However, students often interpret this definition in ways that do not fully capture its relational meaning. This qualitative case study involved 28 undergraduate students and used written tasks, interviews, and classroom observations to collect data. The analysis integrates the WoT framework, which consists of empirical, procedural, and theoretical ways of thinking, with a hermeneutic perspective to explore how students construct meaning. The findings show that most students’ reasoning is dominated by empirical and procedural ways of thinking of the ε–δ, reflected in substitution, approximation, and symbolic manipulation. From a hermeneutic perspective, these patterns indicate that students interpret limit within restricted interpretative horizons. Only a few students demonstrate theoretical reasoning, suggesting an emerging integration between prior understanding and formal structure. These findings suggest that students’ difficulties with limits are not only cognitive but also interpretative, highlighting the importance of supporting meaning-making in calculus learning.
Early Dyslexia Detection Using Deep Learning: Classifying Children's Handwriting with Convolutional Neural Networks Muhammad Imamul Caesar; Aditya Prihandhika; Jasem Al Tamar
Indonesian Journal of Applied Mathematics and Statistics Vol. 3 No. 1 (2026): Indonesian Journal of Applied Mathematics and Statistics (IdJAMS)
Publisher : PT Anugrah Teknologi Kecerdasan Buatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71385/idjams.v3i1.34

Abstract

This study investigates the development of an automated handwriting-based dyslexia classification model using a Convolutional Neural Network (CNN). The dataset comprises scanned handwriting samples from children diagnosed with dyslexia and those without learning difficulties. Prior to model training, the images were resized to a uniform dimension, converted to grayscale, and normalized to standardize pixel intensity values. Data augmentation techniques, including rotation, scaling, and horizontal shifting, were applied to increase data diversity and reduce overfitting. A lightweight CNN architecture was then employed to perform binary classification between dyslexic and non-dyslexic handwriting samples. Experimental results indicate that the proposed model achieved an accuracy of 51%, with a precision of 0.51 and a recall of 0.42, suggesting that its current predictive performance remains limited. These findings highlight the challenges of dyslexia classification using handwriting features alone, particularly when constrained by model simplicity and data resolution. Nevertheless, this study serves as an exploratory step toward automated dyslexia screening and provides insights for future work, where performance may be improved through the use of deeper network architectures, such as ResNet-18, and higher-resolution handwriting representations.
Co-Authors Ade Evi Fatimah Aiyub Aiyub Didi Suryadi Hanifah Nurus Sopiany Iqbal Ramadani Jasem Al Tamar Krisna Satrio Perbowo Muhammad Imamul Caesar Nur Azizah Sessu , Andi Sufyani Prabawanto, Sufyani Sujata, Tatang Supriadi, Edi