Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal HISTORICAL: Journal of History and Social Sciences Elementaria: Journal of Educational Research
James Leonard Mwakapemba
Unknown Affiliation
Religion Humanities Education Languange, Linguistic, Communication & Media Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Trends in the Implementation of Algorithmic Thinking in Social Sciences Research in the Scopus Database: Bibliometric Analysis (1982-2024) Zafrullah, Zafrullah; Ghany Desti Laksita; Weni Dwi Susanti; Fini Rezy Enabela Novilanti; Resty Aulia; James Leonard Mwakapemba
HISTORICAL: Journal of History and Social Sciences Vol. 3 No. 4 (2024): History and Cultural Innovation
Publisher : Perkumpulan Dosen Fakultas Agama Islam Indramayu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58355/historical.v3i4.142

Abstract

This study aims to look at research trends with the topic of Algorithmic Thinking conducted using bibliometric analysis. By using predetermined keywords, 158 documents in the Scopus database were analyzed using R Program and VOSviewer. From the results of the analysis that has been carried out, it can be concluded that this study covers the period 1982 to 2024, which covers a span of 42 years. Korea University and National Taiwan Normal University based in Seoul and Taipei topped the list with the same number of publications at 8 publications. Chung-Yuan Hsu from Taiwan's National Pingtung University of Science and Technology tops the list with an h-index of 2, supported by a total of 63 citations and 3 publications. The journal “Educational and Information Technology”, ranked second with an h-index of 6, supported by a total of 274 citations and 13 publications. Grover et al. (2015) is the source with the highest citations, with 235 citations. There are 28 keywords grouped into four clusters, with the keywords Arduino, Computational Thinking Skills, Early Childhood, Mathematics, and Curriculum used as recommendations for further research related to Algorithmic Thinking.
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.
Co-Authors Arriza, Lovieanta Fini Rezy Enabela Novilanti Ghany Desti Laksita Mariano Dos Santos Resty Aulia Salman Rashid Usama Rasheed Weni Dwi Susanti Zafrullah, Zafrullah