Articles

Access the latest knowledge in applied science, electrical engineering, computer science and information technology, education, and health.

Advanced Search
Filter Icon

Filters article

Years

FAQ Arrow
Single Year
Range Year
0
0

Source Title

FAQ Arrow

Authors

FAQ Arrow

30,895 Article Results

Mapping influential CLIL research in English language teaching: a bibliometric SWOT analysis

10.11591/ijere.v15i4.38986
Lim Seong Pek , Fatin Syamilah Che Yob , Azie Azlina Azmi , Desmond Sandum , Gilbert C. Magulod Jr. , Choiril Anwar
Content and language integrated learning (CLIL) has gained increasing attention in English language teaching (ELT); however, existing reviews often describe trends without critically examining both research impact and developmental challenges. This study addresses this gap by investigating the question: what directions and challenges characterize influential CLIL research in ELT? An integrative approach combining document-level bibliometric performance analysis and strengths, weaknesses, opportunities and threats (SWOT) analysis was employed. Using the Scopus database, the ten most-cited CLIL-related studies published between 2021 and 2025 were identified and systematically analyzed. The findings indicate that influential CLIL scholarship centers on pedagogical scaffolding, teacher cognition, learner motivation, and technology-enhanced learning environments. At the same time, recurring challenges include role ambiguity between content and language teachers, policy-practice misalignment in English-medium instruction (EMI) contexts, and limited longitudinal evidence of language outcomes. The study concludes that while CLIL research is increasingly shaped by digital innovation, sustainable implementation depends on pedagogical clarity, teacher preparation, and institutional alignment. By integrating bibliometric evidence with critical qualitative synthesis, this study provides theoretical and practical insights to guide future research, teacher education, and policy development aligned with sustainable development goal 4 (quality education).
Volume: 15
Issue: 4
Page: 3015-3024
Publish at: 2026-08-01

Digital ecopedagogy-based counseling for cyberbullying prevention among vocational high school students

10.11591/ijere.v15i4.39314
Nina Permata Sari , Hendro Yulius Suryo Putro , Muhammad Andri Setiawan
Cyberbullying has become a growing concern among adolescents in vocational high schools, particularly in Indonesian contexts where conventional counseling often struggles to address online aggression effectively. This study evaluated the effectiveness of digital ecopedagogy-based counseling (DEBC), a structured digital counseling intervention that combines interactive online modules, ecological reflection tasks, peer mentoring, and counselor-guided discussions, in preventing cyberbullying among vocational high school students in South Kalimantan, Indonesia. A quasi-experimental design involved 180 students and six school counselors from three vocational schools, with an eight-week intervention for the experimental group and conventional face-to-face counseling for the control group. Data were collected through pre-test and post-test cyberbullying behavior scales, supported by interviews, focus group discussions, and observations. The experimental group showed significantly greater reductions in cyberbullying behavior (N-Gain=0.45–0.67, p
Volume: 15
Issue: 4
Page: 3497-3507
Publish at: 2026-08-01

Procrastination trap: how personality traits fuel generative artificial intelligence over-reliance and erode academic performance

10.11591/ijere.v15i4.39382
Mohamad Rizal Abdul Hamid , Chen Jung Ku , Anath Rau Krishnan , Imran Mehboob Shaikh , Yoke Lian Lau , Mohd Zulkifli Muhammad , Saiful Bahri
This study investigates how long-term personality traits contribute to generative artificial intelligence (GenAI) use and whether these traits have an impact on academic procrastination and performance. The Big five personality model was used for this investigation, and a quantitative methodology was employed to analyze data from 200 undergraduate students in East Malaysia via partial least squares structural equation modeling (PLS-SEM). Findings indicated that while neuroticism and openness were associated with increased levels of GenAI use, conscientiousness was found to be a protective factor against GenAI dependency. In addition, results showed that when students excessively utilize GenAI, they experience increased levels of procrastination which leads to longer procrastination periods and decreased levels of deep learning engagement. Finally, procrastination was identified as a partial mediator between GenAI use and poor academic performance. Thus, GenAI dependency produces a ‘competence illusion’, causing a decline in students’ academic abilities over time. Ultimately, this study supports the need for interventions designed to help students learn self-regulation and develop critical AI literacy skills to enable technology to serve as a cognitive scaffold as opposed to a replacement for students’ own cognitive efforts.
Volume: 15
Issue: 4
Page: 3362-3374
Publish at: 2026-08-01

Moral disengagement, character strengths, and maladaptive behavior among university students: a structural equation modeling approach

10.11591/ijere.v15i4.38470
Akhmad Syahri , Nimatul Dinawisda , Sri Afsinatun
The increasing integration of digital technology in higher education has raised concerns about students’ maladaptive behaviors (MB), including academic dishonesty and cyber aggression. This study aims to examine the structural relationships among moral disengagement (MD), character strengths (CS), and MB, as well as the mediating role of CS in digitally mediated learning environments. A cross-sectional quantitative design was employed using data collected from 500 undergraduate students at a State Islamic University in Indonesia through purposive sampling. Data were analyzed using partial least squares structural equation modeling (PLS-SEM). The results indicate that MD significantly predicts MB (β=0.830, p
Volume: 15
Issue: 4
Page: 3049-3059
Publish at: 2026-08-01

Reframing teacher evaluation in higher education: a three-pillar framework from Assam

10.11591/ijere.v15i4.40024
Arabinda Rajkhowa , Munmi Dutta
Teacher evaluation shapes the quality of classroom instruction and, through it, student learning outcomes; yet in Indian higher education the dominant single-source model, student feedback channeled through the internal quality assurance cell (IQAC), is widely critiqued as ritualistic and developmentally inert. To the authors’ knowledge, no prior study has integrated student feedback, structured self-evaluation, and peer review into a coherent operational framework for regional Global South contexts. Drawing on primary data collected between 2009 and 2025 from approximately 200 undergraduate arts and science students, principally at North Lakhimpur College (now North Lakhimpur University) and other institutions across Assam, this study employs a qualitative-descriptive design with thematic analysis and triangulation of open-ended questionnaires and semi-structured interviews. Two contributions emerge. First, it yields a culturally grounded fivefold taxonomy of good teaching from Assamese student articulations, including culturally distinctive expectations: the teacher’s public moral role in the community and the obligation of intellectual life beyond the syllabus, that standardized student evaluation of teaching (SET) instruments routinely miss. Second, it proposes a developmental three-pillar framework integrating reformed student feedback, disciplined teacher self-evaluation, and structured peer review to restore the formative function of evaluation and improve student learning outcomes. Both the taxonomy and the framework are scalable across comparable institutions in the Global South.
Volume: 15
Issue: 4
Page: 2840-2851
Publish at: 2026-08-01

Immersive technology in English language learning: a bibliometric analysis

10.11591/ijere.v15i4.37947
Zhou Bo , Lim Seong Pek , Nahdia Kabir , Mohamed Bouteraa , Asna Asna
This bibliometric analysis, drawing on data from the Web of Science (WoS) core collection, explores the expanding role of immersive technologies in English language education. Virtual reality (VR) and augmented reality (AR) have shown strong potential to improve learner motivation, engagement, and communicative competence, yet their integration into formal English language settings remains uneven. By analyzing 248 peer-reviewed articles published between 2021 and 2025, this study finds significant trends, influential contributors, and emerging areas of interest within the field. The findings show a steady increase in publications and citations, reflecting growing recognition of the educational value of immersive environments. Prominent themes include emotional engagement, lowered language anxiety, and improved performance in vocabulary, speaking, listening, and cultural understanding. Much of the literature underlines authentic and situated learning, VR-based interactive environments, VR-supported problem-based learning, and AR-assisted vocabulary development. The analysis also identifies leading countries, with China and the United States producing the largest share of research, a pattern supported by strong institutional participation worldwide. These insights help guide educators and policymakers as they consider how to bring immersive technologies into English instruction. The study also establishes a foundation for future research on effective, engaging, and sustainable immersive language learning practices. Overall, these findings clarify how research on immersive technologies in English language education has evolved between 2021 and 2025 and identify influential studies and key contributors. They also point to persisting gaps, such as equity, teacher readiness, and cognitive-load–informed design, that warrant further investigation.
Volume: 15
Issue: 4
Page: 3623-3635
Publish at: 2026-08-01

Exploring the association among trait resilience, well-being, and coping strategies in Sicilian teenagers

10.11591/ijere.v15i4.37761
Sagone Elisabetta , Indiana Maria Luisa
Resilience is a personality trait strictly influenced by several protective and risk individual factors and analysis of its strengthness is useful to enhance the psychological well-being of teenagers. The aim of this quantitative cross-sectional study was to explore the relationships among resilience in terms of personality trait, psychological well-being, and coping strategies in a large group of Sicilian teenagers. We hypothesized that: the more the teenagers used functional coping strategies (e.g., active and supportive coping strategies), the more they were highly resilient, and they scored higher in dimensions of psychological well-being; the more the teenagers showed high levels of psychological well-being, the more they were highly resilient. The sample consisted of 467 teenagers (age-range: 11–13), 235 girls and 232 boys, randomly recruited from two state junior schools in Catania, Sicily (Southern Italy). For data collection, we used comprehensive inventory of thriving (CIT) for psychological well-being, resilience scale, and children’s coping strategies checklist-R1. Results indicated that there were statistically significant correlations between resilience and dimensions of psychological well-being, as well as between resilience and coping strategies. In addition, multiple regression analyses showed that the use of functional coping strategies and high values of psychological well-being had a positive impact on resilience of teenagers. Future research will compare these findings with those deriving from samples of children to highlight the presence of similarities or differences in the use of coping strategies.
Volume: 15
Issue: 4
Page: 3038-3048
Publish at: 2026-08-01

Enhancing students’ holistic reading through locally-enriched learning materials

10.11591/ijere.v15i4.39293
Husni Mubarok , Haryanto Haryanto , Harun Joko Prayitno , Anam Sutopo , Miftachul Huda
Learning materials that are suitable for the learning environment and resonate with students’ experiences play a crucial role in helping them learn English. A major obstacle in learning English is the scarcity of learning resources that incorporate local content, resulting in low holistic reading skills. This study aims to examine the effectiveness of locally-enriched learning materials on students’ holistic reading and to explore their responses. This study uses a mixed-method approach with a sample of 136 seventh-grade students in Indonesia. Data were gathered using tests, observation, and questionnaires, and analyzed using t-tests and descriptive statistics. The findings indicate that locally-enriched learning materials effectively enhance students’ holistic reading. This improvement is achieved by incorporating oral and written language skills, integrating local culture and daily activities into text discourse, and improving reading comprehension through vocabulary mastery, identifying main ideas, accuracy in grammar, and scanning. Learning enhancement was reflected in stages in English language teaching (ELT), the use of locally-enriched learning materials, material variations, teaching approach, participation and reading skill. Future research should concentrate on predicting text content and skimming in holistic reading. This study recommends the stakeholders to make policies in promoting local content as supporting learning materials in ELT.
Volume: 15
Issue: 4
Page: 3264-3278
Publish at: 2026-08-01

Learning across ages: the role of intergenerational engagement in elderly education

10.11591/ijere.v15i4.40178
Rita Wong Mee Mee , Muhammad Fairuz Abd Rauf , Rasithra Ravichandran , Mohd Fahmi Mohamad Amran , Khairul Annuar Abdullah , Zuraidy Adnan , Muhammad Farhan Nordin
Intergenerational learning (IGL) has gained increasing attention as a strategy to address the limited effectiveness of elderly education, particularly in the context of digital literacy and lifelong learning. Despite growing research, the field remains fragmented, with limited synthesis translating evidence into actionable educational strategies. This study aims to systematically examine how IGL enhances elderly learning ability and to identify strategic directions for its implementation. A bibliometric-driven analytical approach was employed using Scopus-indexed publications from 2021 to 2025. The top ten most-cited articles were identified through performance analysis and subsequently analyzed using a strengths, weaknesses, opportunities, and threats (SWOT) framework. The findings reveal that IGL significantly improves digital literacy, cognitive engagement, and social well-being among elderly learners. However, challenges such as internalized ageism, low learning confidence, and the absence of structured and scalable frameworks remain critical barriers. The study also highlights opportunities for integrating IGL into formal education and community-based programs, while identifying threats related to technological change and policy limitations. This study contributes a bibliometric-informed strategic synthesis that advances understanding of IGL and provides actionable insights for educators, program designers, and policymakers in elderly education.
Volume: 15
Issue: 4
Page: 3086-3098
Publish at: 2026-08-01

Exploring the relationship between teacher work engagement and organizational citizenship behavior in early childhood education

10.11591/ijere.v15i4.39029
Yixuan Zhao , Connie Shin
The role of teacher work engagement (TWE) is very important in creating positive organizational citizenship behavior (OCB) within the early childhood education (ECE) context. This study hypothesizes the use of TWE structural equation modeling (SEM) with advanced logistic regression (ALR) (TWE-SEM-ALR) model and predict the occurrence of OCB among teachers. When 250 early childhood educators in both public and privates collected a teacher-based questionnaire data, it was observed that the information was gathered in questionnaires. Evaluation was done through experimental means, where an 80:20 train-test splitting was used. The model with the suggested accuracy of 92.4 and precision of 0.91, recall as 0.93, F1-score as 0.92, and area under the curve (AUC) of 0.95 was better than models based on logistic regression, support vectors machines, and SEM-only models. The error analysis and the ablation studies also served to validate the role of every model component, as it was shown that the combination of SEM and ALR greatly minimizes the error in predictions and enhances classification stability. The findings of the effectiveness of the proposed framework in explaining complex engagements-behavior relationships and it has rich implications to educational administrators who wish to improve teacher performance and organizational performance.
Volume: 15
Issue: 4
Page: 3310-3321
Publish at: 2026-08-01

A model for flexible learning in graduate teacher education programs

10.11591/ijere.v15i4.39252
Marilyn U. Balagtas , Adonis P. David , Erminda C. Fortes , Arceli M. Amarles , Alvin B. Barcelona , Marla C. Pampango , Marjorie Naquita
This study aimed to develop a model for flexible learning (FL) appropriate to graduate teacher education programs (GTEP) based on the different practices of the graduate faculty and students in a teacher education institution (TEI) before and during the COVID-19 pandemic. A multimethods approach was employed, utilizing survey questionnaires, semi-structured interviews, and focus group discussions (FGD). Data were collected from 215 graduate students and 43 graduate faculty members who were selected through convenience sampling. The study resulted in the development of a model of FL for GTEP (MFL-GTEP), reflected in an outcome-based syllabus that highlights 10 areas of FL, all beginning with P: purpose, process, pedagogy, platform, people, place, pace, performance, product, and policy of learning. The MFL-GTEP promotes self-agency, self-regulation, and self-determination among education professionals pursuing GTEP. The challenges that graduate faculty and students experience in the implementation of FL are addressed in the (MFL-GTEP) to make the model more relevant, inclusive, and sustainable in a graduate teacher education program.
Volume: 15
Issue: 4
Page: 3193-3203
Publish at: 2026-08-01

Developing a 2-DOF robotic arm kit for embodied AI learning in middle school technology education

10.11591/ijere.v15i4.39254
Dasol Kim , Sooin Kim
Artificial intelligence (AI) literacy is increasingly emphasized in technology education, yet many middle-school classroom activities remain screen-based and offer limited opportunities to experience the full AI pipeline in an authentic design context. To address this gap, this study developed a low-cost, classroom-ready 2-degree-of-freedom (2-DOF) robotic arm kit and an eight-lesson AI-integrated instructional unit in which students assembled the robot arm, collected and labeled image data, trained and improved a classification model, and applied model outputs to robot-arm control. A quasi-experimental pretest–posttest control-group design was employed with 98 ninth-grade students in four intact classes (experimental group, n=46; comparison group, n=52). Quantitative data were analyzed using ANCOVA with pretest scores as covariates, and qualitative data from student reflection reports were analyzed thematically. The experimental group significantly outperformed the comparison group on value of AI, efficacy of AI, AI literacy, and total scores. Qualitative findings further showed that students recognized both benefits and risks of AI and proposed multi-layered safety strategies involving physical safeguards, operational rules, and data/model management. These findings suggest that embedding the full AI pipeline in a tangible engineering-design task can support embodied, responsibility-oriented AI learning in middle school technology education.
Volume: 15
Issue: 4
Page: 3060-3074
Publish at: 2026-08-01

A study on exploring the effects of the school climate and teacher’s accountability on academic performance of students in early childhood care and education

10.11591/ijere.v15i4.36631
Kalpana Nagar , G. S. Prakasha
This study investigates parental perceptions of school climate, teachers’ accountability, and students’ academic performance, as well as the relationship among these three factors. The descriptive research uses the demographic background of parents as a stratified sampling method to collect primary data. The statistical procedure shows that Pearson’s product-moment correlations between school climate and teachers’ accountability affect the academic achievement, with effect sizes of r=0.632, r=.646, which significantly correlate with each other. Regression analysis reveals the variability of the effect sizes of school climate and teachers’ accountability on academic achievement, with the values of β=0.070 and β=0.115. The independent variable, school climate and teachers’ accountability, explains 45.4% of the variability of academic performance of the students in early childhood care and education. The present study recommends that training teachers would link their accountability and measures to track the supportive climate of school to improve the student’s academic performance. Future research should conduct longitudinal studies to examine how relationships between school climates and teachers’ accountability affect different student populations and their academic performance.
Volume: 15
Issue: 4
Page: 2883-2890
Publish at: 2026-08-01

Competency-based evaluation of scientific-pedagogical master’s programs

10.11591/ijere.v15i4.37191
Nurzada Kozhamberdiyeva , Aliya Kudaibergenova , Bakytgul Imanbekova , Sarash Konyrbayeva , Zhanar Bekturganova , Yücel Gelişli
The goal of this study is to conduct a comprehensive evaluation of the master’s degree programs at the Faculty of Philosophy and Political Science of Al-Farabi Kazakh National University from the perspective of the competency-based approach. The study involves a targeted sample of 120 participants directly involved in the implementation and evaluation of scientific and pedagogical master’s programs: 70 master’s students, 20 teachers, 20 graduates, and 10 employers. The study employs a mixed-method approach, including surveys of master’s degree students, faculty members, graduates, and employers, as well as qualitative analysis of interviews with participants. Course relevance received the highest rating. Faculty members positively evaluate the alignment of the programs with the competency-based approach. Graduates emphasize the applicability of their knowledge, while employers express satisfaction with the graduates’ level of preparation. Kruskal–Wallis test analysis does not reveal statistically significant differences between groups for most indicators, confirming a consistent perception of educational quality. The interviews reveal a generally positive attitude toward the programs but highlighted several shortcomings, such as uneven competency development, insufficient practical focus, and limited engagement with the professional environment. The novelty of the work lies in the comprehensive empirical evaluation of master’s programs based on a competency-based approach from the perspectives of students, teachers, graduates, and employers. The practical significance of the findings lies in justifying the need for stronger integration of theory and practice, greater transparency in competency assessment, and expanded collaboration with employers to enhance the quality of master’s degree training.
Volume: 15
Issue: 4
Page: 3375-3391
Publish at: 2026-08-01

Teachers’ perspectives on pedagogical challenges of AI integration in English language teaching

10.11591/ijere.v15i4.39226
Parthiban Ganesan , Karthikeyan Padmanathan , Thiyagu Kaliappan , Raja Kumar Subburaj , Durgaprasad Sahoo
Artificial intelligence (AI) tools are rapidly being integrated into English language teaching (ELT). However, limited empirical evidence exists regarding the pedagogical challenges teachers encounter during classroom implementation. This study investigates whether demographic variables influence ELT teachers’ perceptions of AI effectiveness and related pedagogical challenges. A quantitative survey design was employed, involving 200 ELT teachers with prior AI exposure. Data were collected using a validated Likert-scale instrument (α=0.81) and analyzed using independent samples t-tests, one-way ANOVA with Tukey post hoc analysis, and Chi-square (χ²) tests. Results revealed significant gender differences in perceived effectiveness (t=2.504, p=0.044) and pedagogical challenges (t=2.627, p=0.018), with female teachers reporting higher mean scores. Locality differences were significant only for perceived effectiveness (F=4.610, p0.05) or teaching experience (χ²=4.266, p>0.05). Educational level taught was significantly associated with perceived effectiveness (χ²=13.816, p
Volume: 15
Issue: 4
Page: 3439-3450
Publish at: 2026-08-01
1 2 3
...
2059 2060
Show 12 of 2060

Discover Our Library

Embark on a journey through our expansive collection of articles and let curiosity lead your path to innovation.

Explore Now
Library 3D Ilustration