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Journal : Elementaria: Journal of Educational Research

Research Trends on Leadership in Indonesian Schools: Bibliometric Analysis (2008-2024) Brilliant Dwi Izzulhaq; Gunawan, Resky Nuralisa; Zafrullah, Zafrullah; Ayuni, Rizki Tika; Ramadhani, Atika Miftah; Fitria, Rani Laylatul
Elementaria: Journal of Educational Research Vol. 2 No. 1 (2024): Advanced Educational and Moral Learning
Publisher : Penerbit Hellow Pustaka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61166/elm.v2i1.51

Abstract

This research aims to analyze research trends regarding leadership in Indonesian schools on the Scopus database. Using the PRISMA method, the author analyzed documents to obtain 111 documents which were analyzed using the R Program and Vosviewer. From the results of the analysis that has been carried out, it can be concluded that research on Leadership in Indonesian schools started from 2008 to 2024, with an 8-fold increase in the last six years. Malang State University ranks first with the highest contribution in research on leadership in Indonesian schools, producing 45 publications or 40.54% of the total. Cakrawala Pendidikan, published by Yogyakarta State University, holds the top position with an h-index of 3, signifying its significant impact in the field of educational research. Maulana Amirul Adha from Jakarta State University holds the top position with an h-index of 4, reflecting his significant impact in educational research. The highest citation obtained by the article (Wiyono, 2018) with a total of 47 citations. The results obtained are 20 keywords with five groups, with the words “School Principal,” “Teacher,” and “Servant Leadership” stand out as areas worthy of further research regarding the topic of leadership in Indonesian schools.
Mapping the Evolution of Research Themes on ChatGPT Integration in Education: Thematic and Novelty Keywords Nabilah, Nabilah; Zafrullah, Zafrullah; Nakamo, Sosteness Jerome; Mwakapemba, Morris Leonard
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.v3i1.90

Abstract

Abstract. This study aims to examine the evolution and novelty of keywords in the field of ChatGPT in Education using a bibliometric approach. By applying a predefined set of keywords, the researchers identified 310 publications from the Scopus database, which were then analyzed using R Program. The analysis focused on main information, publication trends, keyword evolution over time, and keywords novelty. This analysis concludes that research on ChatGPT in the field of education within the Scopus database began in 2022 and continued through 2025, with the highest surge in publications occurring in 2024, reaching 171 documents. Overall, the findings reveal that the topic of ChatGPT in Education has experienced significant growth, with several core keywords such as "chatgpt", "ai in education", and "artificial intelligence" remaining dominant over the years. Furthermore, the emergence of new keywords such as "efl learners", "contrastive learning", "online learning", "self-directed learning", "technology", "virtual reality", and "attitude" reflects an increasingly diverse research direction, encompassing technological innovations, learning strategies, and psychological dimensions. Keywords marked in bright yellow indicate a high level of novelty and strong potential for further exploration. However, behind AI’s great potential as an educational technology, it is crucial to recognize that not all aspects of education should be fully run by AI. Ethical considerations must remain a central concern, ensuring that the implementation of AI in education maintains a balanced approach between technological functionality and human values.  
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.