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International Education Trend Issues
Published by PT. BATARI EDU CALYA
ISSN : -     EISSN : 29630878     DOI : https://doi.org/10.56442/ieti
Core Subject : Religion, Humanities, Education,
Religion Humanities Education
International education is facing various challenges and trends that are affecting the way students receive their education and the way institutions provide it. These include globalization and mobility, technology and online learning, cost and accessibility, student safety and security, diversity and inclusion, and cultural, linguistic, and other differences in curricula and support services. These issues and trends continue to evolve as the field develops and changes
Arjuna Subject : Ilmu Sosial - Pendidikan
Articles 104 Documents
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The Relationships Among Curriculum Management, Teacher Professional Development, Educational Technology Integration, and Teaching Effectiveness Sofia Nur; Azhariah Rachman; Gamar Al Haddar; Petrus Jacob Pattiasina
International Education Trend Issues Vol. 4 No. 1 (2026): International Education Trend Issue
Publisher : PT. BATARI EDU CALYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56442/ieti.v4i1.1512

Abstract

This study examined the relationships among curriculum management, teacher professional development, educational technology integration, and teaching effectiveness in contemporary educational settings. A quantitative cross-sectional survey design was employed with 200 primary and secondary school teachers. Data were collected through a structured questionnaire using a five-point Likert scale and analyzed using descriptive statistics, reliability and validity testing, correlation analysis, and multiple regression analysis. The findings indicate that curriculum management, teacher professional development, and educational technology integration each have a positive and significant effect on teaching effectiveness. Teacher professional development emerged as the most influential factor, followed by educational technology integration and curriculum management. Collectively, the three independent variables explained a substantial proportion of the variance in teaching effectiveness, underscoring the importance of an integrated approach. The findings demonstrate that effective curriculum planning, continuous teacher development, and meaningful technology use are essential to strengthening instructional quality. They also provide important implications for educators, school leaders, and policymakers seeking to improve teaching effectiveness and educational outcomes in the context of twenty-first-century learning.
The Influence of Learning Motivation, Vocabulary Mastery, Self-Confidence, and Classroom Interaction on Students' English-Speaking Ability Suhardianto Suhardianto; Evi Martiningsih; Petrus Jacob Pattiasina; Shaumiwaty Shaumiwaty
International Education Trend Issues Vol. 4 No. 1 (2026): International Education Trend Issue
Publisher : PT. BATARI EDU CALYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56442/ieti.v4i1.1513

Abstract

This study examined the influence of learning motivation, vocabulary mastery, self-confidence, and classroom interaction on students' English-speaking ability. A quantitative correlational design was employed. The population comprised junior and senior high school students in Indonesia during the 2025/2026 academic year, from which 96 students were selected through simple random sampling. Data were collected using questionnaires measuring learning motivation, self-confidence, and classroom interaction, a vocabulary mastery test, and a speaking performance assessment. Before analysis, all instruments underwent validity and reliability testing. The data were analyzed using descriptive statistics and multiple linear regression in IBM SPSS Statistics after the assumptions of normality, linearity, multicollinearity, and homoscedasticity had been assessed. The results showed that learning motivation, vocabulary mastery, self-confidence, and classroom interaction each had a positive and statistically significant influence on students' English-speaking ability. Collectively, the four independent variables significantly explained students' speaking performance, with the regression model accounting for 73.5% of the variance in English-speaking ability. Vocabulary mastery was the strongest predictor, followed by classroom interaction, learning motivation, and self-confidence. These findings indicate that improving students' speaking competence requires an integrated instructional approach that promotes vocabulary development, strengthens learning motivation and self-confidence, and facilitates meaningful classroom interaction. The study offers practical implications for English teachers seeking to design more effective communicative language-learning environments.
Analysis of Preferences in Choosing Upper Secondary Schools Among Private MTs Students Using a Multinomial Logistic Regression Model Besse Arnawisuda Ningsi; Sarah Febriyani; Irvana Arofah
International Education Trend Issues Vol. 4 No. 1 (2026): International Education Trend Issue
Publisher : PT. BATARI EDU CALYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56442/ieti.v4i1.1515

Abstract

For MTs students, the selection of higher secondary school (SMA, SMK and MA) is a considerable decision that can be affected by a combination of several academic and non-academic aspect. The purpose of this study is to find out the determinants of higher educational choices in Private MTs students. The analysis method used is multinomial logistic regression to determine the factors that influence the choice of Private MTs students in Pinang District, Tangerang City with a sample of 226 students. Based on the results of the analysis, there is one variable that influences the selection of a top-level advanced school for Private MTs students in Pinang District, Tangerang City, which is tuition fees (P-value < 0.05). Tuition fees affect students' choice between high school and vocational school, and other variables do not show statistically significant effects.
Artificial Intelligence in Educational Administration: A Systematic Evidence Review and Exploratory Meta-Analysis of Empirical Studies, 2020–2025 Matyoqubovich Sobirov
International Education Trend Issues Vol. 4 No. 1 (2026): International Education Trend Issue
Publisher : PT. BATARI EDU CALYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56442/ieti.v4i1.1541

Abstract

Artificial intelligence (AI) is increasingly used to automate administrative work, support institutional decision-making, optimise resources, and improve communication in educational organisations. Yet the empirical evidence remains fragmented, dominated by perception studies, and methodologically heterogeneous. This study synthesised empirical research published from 2020 to 2025 on AI-based educational administration and conducted an exploratory meta-analysis of statistically compatible outcomes. A structured search of scholarly indexes, publisher repositories, and citation networks identified 11 empirical studies covering school and higher-education settings. The narrative corpus represented more than 2,400 respondent- or school-level units and 150 administrative records. Only two studies (combined N = 260) reported sufficiently compatible statistics for standardised effect-size estimation. Using the author-reported pre–post effect, a random-effects model yielded Hedges’ g = 1.00, 95% CI [0.24, 1.77], with substantial heterogeneity (I² = 90.2%). A sensitivity analysis reconstructing the pre–post effect from the reported t statistic produced a more conservative pooled estimate of g = 0.65, 95% CI [0.45, 0.86]. Narrative findings indicated potential improvements in processing time, reporting accuracy, workflow coordination, decision support, and resource allocation. However, most studies were cross-sectional, single-site, perception-based, or lacked control groups, and one effect estimate showed internal statistical inconsistency. The evidence therefore supports a cautiously positive conclusion: AI can enhance educational administration when it is embedded in redesigned workflows, staff development, human validation, and risk-based governance, but the current evidence base is insufficient for strong causal or universal claims. Future research should use controlled multisite designs, standardised administrative outcome measures, longitudinal evaluation, transparent system descriptions, cost-effectiveness analysis, and explicit auditing of privacy, fairness, explainability, and accountability

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