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Al-Jabar : Jurnal Pendidikan Matematika
Published by Universitas Islam Negeri Raden Intan Lampung
ISSN : -     EISSN : 25407562     DOI : 10.24042
Core Subject : Education,
Education Mathematics
Al-Jabar : Jurnal Pendidikan Matematika, with registered number p-ISSN: 2086-5872 (print), e-ISSN: 2540-7562 (online), is a scientific journal published by Mathematics Education IAIN Raden Intan Lampung. The aim of this journal publication is to disseminate new theories and research results that have been achieved in the area of mathematics education. Al-Jabar: Jurnal Pendidikan Matematika, particularly focuses on the main issues in the development of the sciences of mathematics education, mathematics education, and applied mathematics. Al-Jabar, has been published since 2010, and starting from 2015, has been published online. Al-Jabar: Jurnal Pendidikan Matematika published twice a year, the period from January to June and July to December. This publication is available online via open access.
Arjuna Subject : -
Articles 446 Documents
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ImageStat EDU: Developing an interactive digital image-based tool for statistical visualization and learning Ruslau, Maria Fransina Veronica; Nurhayati, Nurhayati; Pratama, Rian Ade; Kamariah, Kamariah
Al-Jabar: Jurnal Pendidikan Matematika Vol 17 No 3 (2026): Al-Jabar : Jurnal Pendidikan Matematika
Publisher : Universitas Islam Raden Intan Lampung, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/

Abstract

Purpose: This study aimed to develop and preliminarily evaluate ImageStat EDU, an interactive digital image-based tool designed to support statistical visualization and learning, particularly in descriptive statistics, histogram interpretation, and introductory probability distributions.Method: The study employed a Research and Development approach using the ADDIE model. Product evaluation involved three expert validators representing mathematics/statistics content, instructional media and ICT, and pedagogy, followed by a small-scale implementation with 15 undergraduate mathematics education students enrolled in a statistics course. Data were collected using expert validation sheets, a user response questionnaire, and pretest–posttest assessments. Expert and student responses were analyzed descriptively, while changes in student performance were examined using a paired-sample t-test, a Wilcoxon signed-rank test, and Cohen’s.Findings: Expert evaluation showed substantial improvement following prototype revision, with the final overall evaluation reaching 96.67%. Students also reported high perceived practicality and usefulness, with an overall response of 92.00%. The mean score increased from 36.88 on the pretest to 65.17 on the posttest, with a large within-participant effect size ( ). Parametric and nonparametric analyses consistently indicated higher posttest performance. However, these findings represent preliminary changes within a small, uncontrolled sample and should not be interpreted as evidence of causal effectiveness.Significance: ImageStat EDU demonstrates the potential of using image-derived pixel data to connect visual information, numerical summaries, histograms, and distributional representations within an interactive statistics learning environment. The study provides preliminary evidence supporting further investigation of image-based statistical exploration in mathematics teacher education using larger and comparative research designs.
Designing 'Matcuher' android-based learning media integrating the sedekah bumi tradition to support students’ critical thinking skills Muhtarom, Muhtarom; Masayu Amalia, Yulianti; Rejeki, Sri
Al-Jabar: Jurnal Pendidikan Matematika Vol 17 No 3 (2026): Al-Jabar : Jurnal Pendidikan Matematika
Publisher : Universitas Islam Raden Intan Lampung, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ajpm.v17i3.31264

Abstract

Purpose: This study aims to develop and evaluate the potential of 'Matcuher,' an Android-based learning media integrating the local Sedekah Bumi tradition, to support students' critical thinking skills in curved-surface solids. Method: Employing the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) model, this Research and Development (R&D) study utilised a one-group pretest-posttest design. The participants were 33 ninth-grade students in Semarang City, selected through convenience sampling. Data were collected through expert validation sheets, an empirically validated critical-thinking test, and student response questionnaires. Findings: The results indicate that Matcuher media was rated highly valid and feasible across both the material and design aspects. It also showed potential to enhance students’ critical thinking skills and received positive feedback. Following the intervention, students showed a preliminary improvement in critical thinking, with a paired-samples t-test indicating significant differences and an N-Gain score of 0.59 (moderate improvement). Matcuher provides an interactive learning experience by transforming cultural elements into formal mathematical models. Students also responded positively to the media's practicality. Significance: Matcuher media on curved-surface solid geometry using the Ethno-RME approach proved to be valid, practical, and effective in enhancing students’ critical thinking skills.
Path analysis of AI-based assessment use in higher education: The roles of self-efficacy, digital literacy, and perceived academic  performance Widyawati, Santi; Widada, Wahyu; Yensi, Nurul Asuti
Al-Jabar: Jurnal Pendidikan Matematika Vol 17 No 3 (2026): Al-Jabar : Jurnal Pendidikan Matematika
Publisher : Universitas Islam Raden Intan Lampung, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ajpm.v17i3.31588

Abstract

Purpose: The growing adoption of artificial intelligence (AI)-based assessment in higher education has created new opportunities to enhance learning evaluation. However, empirical evidence explaining how students’ digital literacy and self-efficacy relate to AI-based assessment use and perceived academic performance remains limited, particularly in developing higher education contexts. This study examined the structural relationships among digital literacy, self-efficacy, AI-based assessment use, and perceived academic performance among university students.Method: A quantitative cross-sectional survey was conducted using purposive sampling involving 100 undergraduate students from five teacher education programs at Universitas Nahdlatul Ulama Lampung, Indonesia. Data were collected through a structured questionnaire comprising multi-item measures of digital literacy, self-efficacy, AI-based assessment use, and perceived academic performance. The proposed structural relationships were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM).Findings: The results indicated that digital literacy was positively associated with self-efficacy and AI-based assessment use. Self-efficacy showed a significant positive relationship with perceived academic performance and emerged as the strongest predictor of this construct. In contrast, AI-based assessment use and digital literacy were not directly associated with perceived academic performance. These findings suggest that students’ psychological readiness plays a more important role than technology use alone in explaining perceived academic performance within AI-supported assessment environments.Significance: Unlike previous studies that primarily emphasize technology acceptance or technological effectiveness, this study integrates digital literacy and self-efficacy within a structural model of AI-based assessment use to explain students’ perceived academic performance in an Indonesian higher education context. The findings provide practical implications for higher education institutions seeking to strengthen students’ digital competencies and self-efficacy to support the effective implementation of AI-based assessment.
Number Sense and Self-Efficacy Beliefs in Problem Solving Among Integrated Islamic Elementary School Students Rochaminah, Sutji; Rohmah, Zakiah; Lefrida, Rita; Badjeber, Rafiq; Nursupiamin, Nursupiamin
Al-Jabar: Jurnal Pendidikan Matematika Vol 17 No 3 (2026): Al-Jabar : Jurnal Pendidikan Matematika
Publisher : Universitas Islam Raden Intan Lampung, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ajpm.v17i3.31881

Abstract

Purpose: This study examined the relationship between whole-number sense and mathematics self-efficacy among Grade IV students in an Integrated Islamic Elementary School (Sekolah Dasar Islam Terpadu, SDIT). It addressed the limited evidence regarding whether students' confidence in mathematics is associated with their foundational numerical competence. Method: A quantitative correlational design was employed involving 126 Grade IV students selected through total sampling. Whole-number sense was measured using a researcher-developed test, while mathematics self-efficacy was assessed through a validated questionnaire. Data were analyzed using descriptive statistics and Spearman's rank-order correlation. Findings: The analysis revealed no statistically significant relationship between whole-number sense and mathematics self-efficacy. These findings indicate that students' confidence in solving mathematical problems was not directly associated with their conceptual understanding of whole numbers in the present sample. Significance: This study extends previous research by examining mathematics self-efficacy in relation to whole-number sense rather than general mathematics achievement. The findings contribute to a more nuanced understanding of the relationship between cognitive and affective dimensions of mathematics learning and suggest that conceptual numerical competence and mathematics self-efficacy should be fostered through complementary instructional approaches in elementary education.
Generation Z Prefers Teacher-Assisted over Artificial Intelligence-Assisted Mathematics Learning: A Self-Determination Theory Analysis Arwadi, Fajar; Lam, Toh Tin; Qalbi, Nurfitri
Al-Jabar: Jurnal Pendidikan Matematika Vol 17 No 3 (2026): Al-Jabar : Jurnal Pendidikan Matematika
Publisher : Universitas Islam Raden Intan Lampung, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/

Abstract

Purposes:  The rapid integration of artificial intelligence (AI) in education has reinforced techno-optimistic assumptions that algorithmic efficiency can support increasingly autonomous learning. This study examined Generation Z students’ preferences for AI-assisted and teacher-assisted mathematics learning through the lens of Self-Determination Theory (SDT). Method: A quantitative within-subject comparative design was employed to collect data from 481 students in South Sulawesi, Indonesia. Participants evaluated both learning conditions using a 4-point Likert-scale questionnaire covering six dimensions: Concept Clarity, Feedback, Motivation, Learning Mode, Trust, and Comfort in Asking Questions. Paired-sample t-tests were used to compare students’ evaluations across the two conditions. Findings: Students rated teacher-assisted learning significantly higher than AI-assisted learning across all six dimensions (p < .001). The largest mean differences were observed in Concept Clarity and Trust, while the smallest occurred in Comfort in Asking Questions. Teacher-assisted learning was also rated more favorably in Learning Mode, despite the flexibility commonly associated with AI-based learning. Although AI-assisted learning received moderately positive evaluations, the overall pattern suggests that students placed greater value on the conceptual and relational support associated with teacher assistance. Significance: The findings suggest that technological flexibility alone may not be associated with stronger student preference for mathematics learning. Within this context, AI may be better positioned as a complementary instructional resource rather than a replacement for teacher assistance. Because the study relied on self-reported perceptions, the findings should not be interpreted as evidence of comparative instructional effectiveness.
Learning styles and mathematical representation abilities in complex analysis: A canonical correlation analysis Ihsanudin; Herlina, Lina; Karlina, Lina; Ruhiat, Yayat
Al-Jabar: Jurnal Pendidikan Matematika Vol 17 No 3 (2026): Al-Jabar : Jurnal Pendidikan Matematika
Publisher : Universitas Islam Raden Intan Lampung, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/

Abstract

Purpose: This study examined the canonical relationship between learning styles and mathematical representation abilities among Mathematics Education students in the context of Complex Analysis. It also aimed to identify the learning-style dimension that contributed most strongly to the canonical function and determine which mathematical representation dimensions were most strongly associated with students’ learning styles.Method: A quantitative correlational design was employed involving 60 fourth-semester Mathematics Education students enrolled in a Complex Analysis course. Learning styles were examined through visual, auditory, and kinesthetic dimensions, while mathematical representation abilities comprised symbolic, visual, and verbal dimensions. Data were collected using a learning-style questionnaire and a mathematical representation assessment and analyzed using Canonical Correlation Analysis with IBM SPSS Statistics 27 after preliminary assumption testing.Findings: The analysis identified a strong dominant canonical relationship between the two variable sets, with the first canonical function yielding . A weaker but statistically significant second function was also identified ( ), whereas the third function contributed negligibly. Within the dominant function, kinesthetic (.753) and visual (.722) tendencies showed the strongest structure coefficients among learning styles. Symbolic representation (.902) contributed most strongly within the representation set, followed by visual (.831) and verbal (.788) representation.Significance: The findings demonstrate that learning styles and mathematical representation abilities are related through a multidimensional structure rather than simple one-to-one correspondences. The study supports multimodal and representation-rich instruction in Complex Analysis while positioning learning styles as flexible tendencies rather than fixed determinants of mathematical performance.

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