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Elementaria: Journal of Educational Research
Published by Penerbit Hellow Pustaka
ISSN : -     EISSN : 29885949     DOI : https://doi.org/10.61166/elm.v1i1.5
Core Subject : Religion, Humanities, Education, Social,
Religion Humanities Education Languange, Linguistic, Communication & Media Social Sciences
Elementaria: Journal of Educational Research aims to provide a forum for original and theoretical studies in education. The journal publishes fully refereed papers which cover applied and theoretical approaches to the study of education. Papers should constitute original research, and should be methodologically sound, theoretically informed and of relevance to an audience. The journal is particularly interested in research that aims to inform educational practice(s) within and/or across sectors. Elementaria: Journal of Educational Research more specifically, accept papers mostly on the subjects listed below: - Curriculum & Program Development in Education - Early Childhood Education - Education & Behavior - Educational Assessment & Evaluation - Educational Economics & Finance - Educational History - Educational Leadership & Management - Educational Philosophy - Educational Policy - Educational Psychology & Counselling - E-Learning - Higher Education - Special Education - Teacher Education & Development
Arjuna Subject : Ilmu Sosial - Pendidikan
Articles 38 Documents
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Enhancing Engagement And Relevance In Introductory Ict Courses For Non-Technical Students In Higher Education Alton Mabina; Amber Mbotho
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.v3i1.84

Abstract

This study investigates the challenges of engagement and relevance in introductory ICT courses for non-technical students, focusing on factors that contribute to student disengagement and strategies to enhance learning outcomes. The research objectives include examining the causes of negative attitudes toward ICT, analysing the disconnect between course content and students’ academic and career needs, and evaluating interdisciplinary teaching approaches that improve engagement. The study employs a mixed-methods approach, incorporating surveys and qualitative analysis of student experiences to assess existing pedagogical challenges. Findings indicate that rigid curricula, theoretical-heavy instruction, and a lack of application-based learning contribute to disengagement. Moreover, the study highlights the effectiveness of practical, interdisciplinary teaching strategies, such as project-based learning, gamification, and adaptive learning technologies, in fostering student interest and participation. The research concludes that aligning ICT education with real-world applications and diverse career pathways enhances student motivation, digital literacy, and employability. The study’s findings provide valuable insights for educators, curriculum developers, and policymakers to design more inclusive and effective ICT courses, ensuring that all students, regardless of their field, acquire essential digital competencies necessary for academic and professional success.
Educational Management Publication Trends In The Scopus Database: An Analysis Of The Evolution Of Research Development Gunawan, Resky Nuralisa; Muhammad Imran Nur; Mar’ah Tusshalihah
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.v3i1.85

Abstract

This analysis aims to see publication trends regarding the use of structural equation modeling in the field of education. By using predetermined keywords, researchers obtained 433 documents that had gone through the PRISMA method and analyzed using the R Program. From the analysis results, it can be concluded that research using the Structural Equation Modeling approach in the field of education shows a positive trend from 1984 to 2024, with an annual growth rate of 11.58%, and the peak publication is expected to occur in 2024 with 80 documents. The country with the highest number of publications is China (Asia), with 54 publications (12.50%) and a total of 1,286 citations (12.27%). Jambi University from Indonesia is ranked first with the highest number of publications, namely 14 publications (3.24%). Sustainability Journal (Switzerland) was ranked first with an h-index of 9, recording 387 citations and 19 publications. Researcher Tsai Chin-Chung from National Taiwan Normal University was ranked first with an h-index of 8. The article with the highest number of citations was (Scherer et al., 2019) with 955 citations. The keyword "Structural Equation Modeling" is the most frequently used in research, with a total of 72 times, while the keywords "Confirmatory Factor Analysis" and "self-regulated learning" are also worthy of being a focus in further research.
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.  
The Role Of Teachers In Implementing Process Of Inclusive Education In Batticaloa District Schools K. Abilash; N. Mahthi Hassan
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.v3i1.91

Abstract

Inclusive education is considered unique in each country. However, implementation of inclusive education and related policies in developing countries like Sri Lanka is difficult. Therefore, this study aims to ensure the quality of teaching in the future by knowing the role of teachers in the implementation of inclusive education, especially in Batticaloa. Explored the strengths, weaknesses and challenges in implementing inclusive education within public schools in Batticaloa District. Among them, 05ADS/ISA(SNE), 05principals, 120class teachers, 300subject teachers, 150students and 75parents were selected based on purposive sampling and stratified random sampling. Questionnaires, interviews and documents were used as data collection tools to get information from them. Also, data was collected through group discussion with subject teachers. Data analysis was done using SPSS software. Reinforcement of appropriate practices, parental support, peer-teacher-student interaction, teacher skills, teaching methods, curriculum adaptation, assessment and student achievement, community and government approach, classroom technique, resource allocation, teacher's role in relation to Individualized Education Plan (IEP) were also discussed. The study also suggested that future research solutions should focus on the role of teachers in school-level IE policy formulation, infrastructure development, financial allocation and resource management.
Learning Model Innovation: A Study of the Use of Computer Supported Collaborative Learning Models in the Context of Higher Education Anastya Nida Alhana; Moch. Farich Alfani
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.v3i1.87

Abstract

One learning approach considered capable of increasing learning motivation in higher education is the Computer Supported Collaborative Learning (CSCL) paradigm. To improve learning efficiency, CSCL still requires innovation. The purpose of this study is to assess the implementation and efficacy of the CSCL learning model in higher education. A descriptive approach is the research methodology used, and secondary data are collected from the literature. The use of the CSCL learning model in higher education institutions will be discussed in this study, along with its definition, collaborative learning models, advantages, and impact on learning outcomes. The research findings indicate that because the Computer Supported Collaborative Learning model encourages a more dynamic learning environment in the classroom, this model is considered more beneficial for students than traditional methods. Students can also collaborate more with their peers, which will increase the effectiveness of the learning process.
Improving Teachers' Teaching Competence Through Training In Educational Media Creation Naufal Ahmad Rijalul Alam; Fajar Rachmadhani
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.v3i1.88

Abstract

This article describes a strategy for improving teachers' competencies through training in the creation of interactive learning media. The research involved 15 teachers from SMA Muhammadiyah Kasihan Bantul as respondents. This evaluative study used pre-test and post-test methods to assess the effectiveness of the training program in creating interactive learning media using the Book Creator and Blooket platforms. The choice of Book Creator and Blooket as learning media was based on their ease of use, which allows for the creation of engaging graphic designs and content that supports interactive and innovative learning. The results of the training activities showed a significant improvement in the teachers' competencies. Before the training, the average knowledge and skills of the teachers in using learning media was only 65%. However, after the workshop, there was a significant increase, with the post-test results showing an average improvement in teacher competencies to 92.5%. Based on these evaluation results, it can be concluded that the training activities were effective in enhancing teachers' competencies, particularly in using interactive media technologies in the learning process. By utilizing platforms like Book Creator, teachers can create more engaging, creative, and student-centered learning materials, thus supporting the achievement of optimal learning outcomes.
Sentiment Analysis and its Application in the Education Sector: A Comprehensive Review Fahima, M.M.F.; Prasanna Sumathipala
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.v3i1.89

Abstract

Sentiment analysis has become an essential tool across various domains, including the education sector, where its application remains relatively underexplored. This study presents a comprehensive review of sentiment analysis in educational contexts, evaluating traditional machine learning models such as Support Vector Machines (SVM) and Naive Bayes, as well as advanced deep learning approaches like Long Short-Term Memory (LSTM) networks and transformer-based models such as BERT. These methods have been applied to analyze student feedback, predict academic performance, and improve teaching strategies. Model performance is assessed using accuracy, precision, recall, and F1-score, though challenges persist related to data quality, annotation consistency, and the contextual complexity of student language. The review identifies significant research gaps, particularly the lack of multilingual and culturally diverse datasets, which limits the generalizability of current models. Furthermore, real-time sentiment tracking and adaptive feedback systems remain underdeveloped. To address these issues, the study proposes the integration of AI-enabled adaptive learning environments capable of dynamically responding to learners’ emotional and cognitive states, thus enhancing personalization and educational effectiveness. Overall, sentiment analysis holds significant promise for transforming educational practices, provided future research focuses on inclusivity, contextual awareness, and scalability.
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.

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