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All Journal Jurnal Penelitian dan Evaluasi Pendidikan BAREKENG: Jurnal Ilmu Matematika dan Terapan Mathematics Research and Education Journal Elementaria: Journal of Educational Research
Arriza, Lovieanta
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Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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TRENDS IN IMPLEMENTATION OF TECHNOLOGY USE IN MATHEMATICS EDUCATION ON SCOPUS DATABASE: BIBLIOMETRIC ANALYSIS Bin Zabidi, Muhammad Aqil Naim; Bakti, Anugrah Arya; Sultan, Jumriani; Ayuni, Rizki Tika; Arriza, Lovieanta
Mathematics Research and Education Journal Vol. 8 No. 1 (2024): PDF is in the process of uploading
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/mrej.2024.vol8(1).16919

Abstract

This study aims to analyze the trend of technology implementation in mathematics education in the Scopus Database using bibliometric analysis. Using predetermined keywords, researchers analyzed 251 documents using RStudio and Vosviewer. From the analysis conducted, it can be concluded that this study shows an interesting growth pattern in research on the use of technology in mathematics education over the period 1977 to 2024. This pattern changed significantly in the last 15 years, from 2009 to 2024, which is equivalent to four times the previous figure, or 66.13% of the total. The University of Pretoria dominated with the highest number of publications, at 14 articles. The source "Educational Studies in Mathematics" stands out as the best source with the highest h-index, at 5. Marien Alet Graham stands out as the author with the highest h-index, at 3. The paper Drijvers et al. (2010) stands out with the highest number of citations, at 168. There were 46 keywords divided into 6 groups, with the keywords Whatsapp, Geogebra, Science Technologies, and Collaborative Learning potentially being interesting and innovative research subjects related to Technology in Mathematics Education.
Psychometric quality of multiple-choice tests under classical test theory (CTT): AnBuso, Iteman, and R Nurjanah, Siti; Iqbal, Muhammad; Zafrullah, Zafrullah; Mahmud, Muhammad Naim; Seran, D'aquinaldo Stefanus Fani; Suardi, Izzul Kiram; Arriza, Lovieanta
Jurnal Penelitian dan Evaluasi Pendidikan Vol. 28 No. 2 (2024)
Publisher : Graduate School, Universitas Negeri Yogyakarta in cooperation with Himpunan Evaluasi Pendidikan Indonesia (HEPI) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/pep.v28i2.71542

Abstract

Psychometric quality analysis of psychological instruments was important to ensure credible measurement. This study aims to compare the psychometric quality analysis of multiple-choice test items using three different applications to evaluate the advantages and disadvantages of the features provided in supporting classical test theory analysis. This study used a quantitative approach by analysing dichotomous data from 50 participants of a 30-item multiple-choice test. The data were analysed using three applications (AnBuso, Iteman, and R) to compare the statistical output of the main psychometric parameters of the classical test theory, such as difficulty index, discrimination index, and distractor effectiveness. Data analysis was conducted descriptively and quantitatively by comparing the features provided by the application in support of classical test theory analysis to evaluate the advantages and disadvantages of each application. The study found that all three applications produced similar results for the difficulty index, distractor effectiveness, and discrimination index. AnBuso proved user-friendly but limited in capacity, Iteman offered comprehensive output with restricted free functionality, and R provided flexibility but required programming expertise. The application demonstrated unique strengths that are suitable for different research needs and user proficiencies. The choice of application should consider factors such as analysis complexity, sample size, and user expertise. Further research into paid options and diverse test conditions is recommended for a more comprehensive evaluation of these applications in classical test theory analysis.
Research Trends on Deep Learning for Mathematics Learning in Scopus Database: Concept Map & Emerging Themes Using Scopus AI Zafrullah, Zafrullah; Arriza, Lovieanta; Salman Rashid; James Leonard Mwakapemba; Mariano Dos Santos; Usama Rasheed
Elementaria: Journal of Educational Research Vol. 3 No. 1 (2025): Advancements in Educational Technology Research
Publisher : Penerbit Hellow Pustaka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61166/elm.v3i1.93

Abstract

This paper aims to explore the concepts and themes emerging in the literature related to "Deep Learning in Mathematics Learning" in order to understand the direction of development and current trends in the field. To achieve this goal, the study uses the Automatic Systematic Literature Review (SLR) method with the help of Scopus AI, which allows for the automatic identification of concepts and themes through the visualization of concept maps and emerging themes. The database selection focused solely on Scopus due to its high reputation and extensive coverage of high-quality international journals. The keyword used is "deep learning in mathematics learning" with a publication time limit from 2003 to 2025, thus covering early developments to the latest trends. This approach allows for systematic and efficient literature mapping without having to manually review all documents. The analysis reveals that the topic of "Deep Learning in Mathematics Learning" encompasses several emerging themes, including student performance prediction, AI integration in mathematics education, and the adoption of innovative pedagogical practices. Based on the concept map visualization, three main research directions are identified: Learning Environment, Techniques, and Applications. The theme of student performance prediction highlights the use of neural network models such as CNNs and LSTMs to analyze key factors influencing academic outcomes. Meanwhile, AI integration focuses on the development of adaptive learning platforms that personalize instruction and enhance learning effectiveness. Innovative pedagogical practices, including the use of extended reality and machine learning, aim to create immersive and interactive learning experiences. Overall, these findings underscore the significant potential of deep learning to transform mathematics education through intelligent, adaptive, and student-centered approaches.
ITEM ANALYSIS OF HIGH SCHOOL SPECIALIZATION MATHEMATICS EXAM QUESTIONS WITH ITEM RESPONSE THEORY APPROACH Arriza, Lovieanta; Retnawati, Heri; Ayuni, Rizki Tika
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss1pp0151-0162

Abstract

Analysis of item characteristics on test instruments is carried out to determine high-quality items. This study aims to describe the parameters of specialized high school mathematics test items using the IRT approach. It is an exploratory descriptive study employing a quantitative approach. The research subjects were 36 students of grade XI high school who took the specialization mathematics subject. Response data with dichotomous scoring were analyzed using the IRT approach with the R program to obtain information about item parameters and student ability. The results of the model fit test showed that most of the specialization mathematics exam items fit the Rasch model. The results showed that all items met the criteria of good quality because they had good difficulty parameters. Relatively, the test items were suitable for students with abilities between -2.6 and 2.8 logits. This estimation is also supported by the TIF with a maximum value of 3.049 at 0.08 logit ability and SEM of 0.541. Test items that have been proven to be of high quality can be used as examples in both teaching and diagnostic assessments. Further research could consider the discrimination parameter when analyzing the characteristics of the questions.
Co-Authors Ayuni, Rizki Tika Bakti, Anugrah Arya Bin Zabidi, Muhammad Aqil Naim Heri Retnawati James Leonard Mwakapemba Mahmud, Muhammad Naim Mariano Dos Santos Muhammad Iqbal Salman Rashid Seran, D'aquinaldo Stefanus Fani Siti Nurjanah Suardi, Izzul Kiram Sultan, Jumriani Usama Rasheed Zafrullah, Zafrullah