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International Journal of Evaluation and Research in Education (IJERE)
Published by Institute of Advanced Engineering and Science
ISSN : 22528822     EISSN : 26205440     DOI : -
Core Subject : Education,
Education
The International Journal of Evaluation and Research in Education (IJERE) is an interdisciplinary publication of original research and writing on education which publishes papers to international audiences of educational researchers. The IJERE aims to provide a forum for scholarly understanding of the field of education and plays an important role in promoting the process that accumulated knowledge, values, and skills are transmitted from one generation to another; and to make methods and contents of evaluation and research in education available to teachers, administrators and research workers. The journal encompasses a variety of topics, including child development, curriculum, reading comprehension, philosophies of education and educational approaches, etc.
Arjuna Subject : -
Articles 2,356 Documents
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Beyond narrative: a pedagogical, cultural, and psychological analysis of Saken Zhunusov’s Amanai and Zamanai for higher education Tokzhan Igenbay; Gauhar Baltabaeva; Amangaisha Bolsynbayeva; Gulnara Apeyeva; Sarash Konyrbayeva
International Journal of Evaluation and Research in Education (IJERE) Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v15i4.38486

Abstract

This study offers a comprehensive pedagogical analysis of Saken Zhunusov’s Amanai and Zamanai, demonstrating that the novella functions as a multilayered educational text suitable for literature, cultural studies, teacher education, and psychology-of-literature curricula in higher education. Using qualitative content analysis, the study identifies six interrelated thematic domains; moral education, cultural learning, developmental psychology, folklore pedagogy, narrative methodology, and emotional literacy, through which the novel teaches readers to interpret emotional, ethical, and cultural meanings embedded in the narrative. The data consisted of the full text of Saken Zhunusov’s Amanai and Zamanai, analyzed using qualitative content analysis. Findings reveal that the text models moral dilemmas, cultivates empathy, preserves Kazakh cultural knowledge, exposes structural inequalities, and illustrates childhood cognition and trauma through symbolic and myth-infused storytelling. The study connects these themes to established theoretical perspectives including Vygotsky’s symbolic mediation, Bruner’s narrative cognition, Rosenblatt’s reader–response theory, and cultural-historical views of oral tradition. By developing a detailed codebook and pedagogical framework, the research provides a replicable model for analyzing culturally embedded literature and demonstrates the relevance of Amanai and Zamanai to contemporary Kazakh social issues such as poverty, gendered burden, and generational trauma. The study concludes that the novel offers rich opportunities for interdisciplinary teaching and contributes significantly to the integration of Kazakh literature into modern higher education pedagogy.
Motivational and normative drivers of generative AI substitution in academic work: a mixed-methods study from Saudi higher education Mazin Mansory; Zilal Meccawy
International Journal of Evaluation and Research in Education (IJERE) Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v15i4.38745

Abstract

The rapid integration of generative artificial intelligence (GenAI) in higher education has intensified tensions between legitimate learning support and unauthorized task substitution, particularly where institutional guidance remains ambiguous. This mixed-methods study investigates how attitudes toward AI, moral rationalization strategies, and perceived institutional clarity interact to shape AI-based substitution behavior among 249 undergraduates at a Saudi university. Partial least squares structural equation modeling (PLS-SEM) revealed that positive attitudes and rationalization together explained 46% of the variance in substitution behavior, with perceived clarity of institutional guidance significantly moderating the rationalization–substitution link. Complementary interviews with seven students and ten instructors revealed that linguistic burden, peer norms, and fragmented faculty guidance facilitated boundary crossing from scaffolding to shortcutting. By exploring the relationship between moral neutralization and environmental clarity, this research offers a new approach to evaluating the effectiveness of institutional AI guidance beyond common technology acceptance models. The findings can be used to inform the design of multi-tiered, inclusive AI usage policies, assessments that value process over product, and culturally responsive academic integrity education within a multilingual higher education context.
Improving students’ scientific argumentation through AI-supported feedback Joelash R. Honra; John Lorence A. Villamin
International Journal of Evaluation and Research in Education (IJERE) Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v15i4.38648

Abstract

Scientific argumentation is a core practice in science education, yet many students struggle to construct arguments that effectively integrate claims, evidence, and reasoning. With the growing use of artificial intelligence (AI) in education, AI-supported feedback has emerged as a potential tool to scaffold students’ argumentation processes. This study examined the effects of AI-supported feedback on students’ scientific argumentation using a quasi-experimental, explanatory sequential mixed-methods design. Two intact groups participated: an experimental group receiving AI-supported formative feedback on written arguments and a control group receiving conventional teacher feedback. Quantitative data were collected using a validated rubric based on the claim–evidence–reasoning (CER) framework and Toulmin’s argument pattern (TAP), while qualitative data from student interviews and written responses provided contextual insights. Results showed that the experimental group achieved greater improvements in overall argumentation quality, particularly in evidence use and reasoning. Qualitative findings further indicated that AI feedback supported iterative revision and strengthened students’ understanding of evidence–claim relationships.
Digital ecopedagogy-based counseling for cyberbullying prevention among vocational high school students Nina Permata Sari; Hendro Yulius Suryo Putro; Muhammad Andri Setiawan
International Journal of Evaluation and Research in Education (IJERE) Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v15i4.39314

Abstract

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
Procrastination trap: how personality traits fuel generative artificial intelligence over-reliance and erode academic performance Mohamad Rizal Abdul Hamid; Chen Jung Ku; Anath Rau Krishnan; Imran Mehboob Shaikh; Yoke Lian Lau; Mohd Zulkifli Muhammad; Saiful Bahri
International Journal of Evaluation and Research in Education (IJERE) Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v15i4.39382

Abstract

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.
Learning across ages: the role of intergenerational engagement in elderly education Rita Wong Mee Mee; Muhammad Fairuz Abd Rauf; Rasithra Ravichandran; Mohd Fahmi Mohamad Amran; Khairul Annuar Abdullah; Zuraidy Adnan; Muhammad Farhan Nordin
International Journal of Evaluation and Research in Education (IJERE) Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v15i4.40178

Abstract

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.
Enhancing students’ holistic reading through locally-enriched learning materials Husni Mubarok; Haryanto Haryanto; Harun Joko Prayitno; Anam Sutopo; Miftachul Huda
International Journal of Evaluation and Research in Education (IJERE) Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v15i4.39293

Abstract

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.
Exploring the association among trait resilience, well-being, and coping strategies in Sicilian teenagers Sagone Elisabetta; Indiana Maria Luisa
International Journal of Evaluation and Research in Education (IJERE) Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v15i4.37761

Abstract

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.
Evaluating the methodological admissibility of generative AI tools for linear regression in graduate-level research Valery Okulich-Kazarin; Kanat Kozhakhmet
International Journal of Evaluation and Research in Education (IJERE) Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v15i4.38496

Abstract

With the growing use of generative artificial intelligence (AI) in academia, a key methodological question concerns the statistical correctness of AI-assisted quantitative analysis. This study empirically evaluates the use of generative AI tools for linear regression in graduate-level research. The authors used a methodological approach in which estimates from four AI systems (ChatGPT 4.0, DeepSeek v3.2, Gemini 3 Pro, and Grok 4.1) were compared with estimates obtained using Microsoft Excel (Windows 10). The analysis was performed on five time series using a fixed prompt structure. Comparability was assessed using thresholds for regression coefficients, the coefficient of determination (R²), and predicted results for 2030. The results show that under controlled conditions and within the ordinary least squares (OLS) method, the AI tools generate statistical results with varying degrees of accuracy. However, deviations in coefficients and predictions highlight the need for systematic validation. The study concludes that AI tools can serve as auxiliary methodological support, provided transparency, reproducibility, and threshold-based verification are ensured in graduate research practice.
Ethical and cultural perspectives on ChatGPT use in higher education Masroor Alam; Suchi Dubey
International Journal of Evaluation and Research in Education (IJERE) Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v15i4.37857

Abstract

Academic writing now faces additional challenges because users cannot identify when they use their human abilities instead of ChatGPT generative artificial intelligence (AI) tool assistance. The rapid emergence of generative AI tools such as ChatGPT has raised important ethical and cultural questions in higher education, particularly concerning authorship, originality, and responsible academic practice. The research obtained 55 open-ended survey responses from students who studied at different levels and pursued various subjects across multiple geographic areas. Among these responses, 23 provided sufficiently detailed reflections and were analyzed for qualitative insights. Using a qualitative research design, the research applied Braun and Clarke’s thematic analysis to identify three connected themes which include students’ ethical perceptions of ChatGPT use, perceived benefits and concerns in academic work, and the role of cultural context in shaping AI acceptance. Students acknowledge the helpful features of ChatGPT but they remain unclear about plagiarism rules and academic authenticity standards and institutional policies. The findings indicate that students generally perceive ChatGPT as a supportive learning tool when used responsibly, while also expressing concerns regarding dependency and unclear institutional guidance. Overall, the study highlights the need for clearer institutional policies and culturally informed AI literacy to support responsible use of generative AI in academic writing.

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