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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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Phono-syntactic error pattern analysis in impromptu speaking among English learners: a content analysis Angelie V. Temario; Harold John U. Mamites; April Jane G. Sales; Marcelina S. Deiparine
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.v15i4.39044

Abstract

Second language learners, particularly Filipino learners of English, often experience linguistic difficulties in producing accurate phonological and syntactic forms, especially during spontaneous speaking tasks. This study examines the dominant phono-syntactic error patterns found in impromptu speaking performances and explores their pedagogical implications using Corder’s error analysis framework. Employing a qualitative descriptive research design, the study analyzed recorded impromptu speaking performances of 36 Bachelor of Arts in English Language (BAEL) students. The analysis revealed that in the phonological aspect, segmental errors were more prevalent than suprasegmental errors, with vowel substitution emerging as the most frequent error type, accounting for 22 errors (57.1%). In the syntactic aspect, misformation was identified as the most dominant error category, with 164 errors (54.88%). These findings suggest that while learners demonstrate emerging grammatical awareness, they still encounter difficulties in maintaining phonological and syntactic accuracy during spontaneous speech production. The study highlights the importance of integrating pronunciation and grammar instruction within communicative speaking activities. Furthermore, impromptu speaking tasks serve as an effective diagnostic tool for identifying learners’ linguistic challenges and guiding instructional strategies aimed at improving spoken language proficiency.
Bridging ethics and performance in engineering education through predictive learning analytics Hamza Abu Owida; Areen Arabiat
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.v15i4.38767

Abstract

This literature review examines the opportunities, implementation challenges, ethical implications, and emerging directions of predictive learning analytics (PLA) in engineering education. Using a structured review of the literature, the study synthesizes evidence from several publications with emphasis on studies examining risk prediction, personalized support, curricular improvement, interpretability, fairness, and intervention design. The review shows that PLA can improve early identification of at-risk students, support adaptive learning pathways, and inform data-driven refinements in engineering curricula; however, its impact depends on data quality, model transparency, institutional capacity, and the availability of timely human support. The analysis further indicates that the most consequential barriers are fragmented data ecosystems, the difficulty of translating predictions into effective interventions, and unresolved ethical concerns related to privacy, bias, consent, and student agency. The article contributes to educational research by offering an integrated synthesis that connects technical development with pedagogical evaluation and ethical governance in engineering education. It concludes by proposing that future PLA adoption should align predictive modeling with explainable artificial intelligence, learning-theory-informed intervention design, and institution-level implementation strategies. Publications were selected for relevance to PLA in engineering education and then synthesized narratively across opportunities, challenges, ethics, and future directions.
Artificial intelligence usage in the teaching-learning process: perception and challenges Ishani Basak; Benny Thomas; Shinto Thomas
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.v15i4.38964

Abstract

Artificial intelligence (AI) has advanced in the post-pandemic era and is unavoidable in teaching and learning. Teachers’ perceptions, as the primary gatekeepers, are essential for ensuring quality education and inclusive classrooms, with AI as a collaborator. While some teachers resist these technological shifts, others are actively adapting an AI-assisted teaching approach. We conducted this study to understand the reasons for teachers’ resistance (challenges and difficulties) and how they perceive the use of AI in the teaching, learning, and assessment process, because the first step in effective incorporation is having a favorable attitude towards it. Hence, this study explored the perceptions of 15 secondary private school teachers, selected through purposive sampling, regarding the incorporation of AI into teaching, learning, and assessment processes, as well as the challenges they faced. The researchers developed an in-depth interview schedule and conducted interviews to understand participants’ perceptions and challenges. The data is analyzed following the thematic analysis steps by Braun and Clarke. Thematic analysis revealed that teachers demonstrated a positive understanding towards the pedagogical relevance of AI, rather than merely having a favorable perception. Furthermore, teachers predominantly viewed AI as an additional tool to enhance the effectiveness of knowledge transactions and instructional design. The challenges include infrastructure accessibility and professional training; time management for preparation, skill updating, and fulfilling varied teaching and other responsibilities; the inability to verify the accuracy of information; and parental mindset. This study offers insights for developing AI-aided teacher training and relevant curricula for schools.
Tutor feedback, simulation-based learning, and AI-aware practice in MSc electrical engineering module: a case study Emad Al-Mahdawi; Nkaepe Olaniyi
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.v15i4.38929

Abstract

Engineering programs routinely collect tutor evaluation data for quality assurance, yet the evidence is often not translated into a transparent, reproducible module enhancement plan that can be audited, monitored, and reported as scholarly work. This paper proposes a tutor feedback-to-enhancement (TFE) framework that transforms a standard tutor feedback worksheet into: i) a coded evidence base; ii) a descriptive closed-item profile; and iii) an evidence-to-action matrix (EAM) that links observed strengths and gaps to targeted interventions and measurable indicators. The framework is demonstrated through a single-module case study (an introductory MSc electrical power engineering systems (EPES) module) using one completed tutor feedback sheet containing closed ratings and open comments. The closed items show uniformly positive evaluations (7/12 items rated excellent and 5/12 rated good; no satisfactory/unsatisfactory responses; one item not applicable). The open-text evidence highlights simulation as a core learning scaffold, the importance of equitable access to laptops and e-learning resources, and a specific curriculum enhancement need for a dedicated lecture on photovoltaic (PV) design and battery energy storage systems (BESS). The main contribution is a practical, low-cost method that operationalizes routine tutor feedback into an auditable enhancement pathway, including an explicit artificial intelligence-aware (AI-aware) practice component that emphasizes verification and engineering judgment.
Modernizing geography teacher education through STEAM integration to enhance geoecological competence Roza Mukhitdinova; Kuat Baymyrzayev; Murat Auyelbek
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.v15i4.39056

Abstract

This study examines the effectiveness of integrating science, technology, engineering, arts, and mathematics (STEAM) into geography teacher education to enhance geoecological competence among prospective teachers. A mixed-methods pedagogical experiment was conducted with 178 undergraduate students from two pedagogical universities in Kazakhstan, including an experimental group (n=90) and a control group (n=88). The intervention involved the integration of interdisciplinary STEAM projects, digital modeling, geographic information systems (GIS), and practice-oriented tasks focused on regional geoecological problems. Data were collected through curriculum analysis, tests, questionnaires, project evaluation, reflective reports, and expert assessment. The results revealed statistically significant improvement in the experimental group across the cognitive, activity-based, value-motivational, and reflective components of geoecological competence compared with the control group (p
A pathway model for physics teachers’ pedagogical philosophy core competency development Ze He; Lumeng Chao; Xiaofei Xue
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.v15i4.39090

Abstract

The implementation of the National Education Development Plan (2024–2035) has propelled Chinese physics education from traditional knowledge transmission toward a core competency-oriented teaching model. This transformation need to impose new demands on educationally underserved central and western regions, how teachers adapt to this shift presents an urgent challenge. This study aims to systematically analyze secondary physics teachers’ cognitive levels regarding core competencies, examine the consistency between teaching philosophies, practices, and focus on how individual teacher characteristics and external support conditions influence professional development. The sample comprised 320 secondary physics teachers from Ulanqab City, selected via stratified random sampling to ensure representativeness, with 48 teachers participated in a quasi-experimental intervention study. Findings indicate that teachers’ overall core literacy cognition levels were moderately high (M=3.86, SD=0.42), though 35.0% reached high levels. Significant differences existed across teaching experience and professional titles (p
The relationship between arithmetic proficiency and artificial intelligence-assisted learning Khalid Marnoufi; Imane Ghazlane; Fatima Zahra Soubhi; Bouzekri Touri
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.v15i4.39461

Abstract

Amidst the rapid developments witnessed in educational environments, this study aims to investigate the dynamic relationship between the desire for artificial intelligence (AI) supported learning and proficiency in mental arithmetic, considering the latter a decisive factor in enhancing cognitive acquisition. The study focused specifically on the academic elite, represented by students in the mathematical sciences track at the qualifying secondary level. To ensure the accuracy of the results, the methodology relied focusing particularly on the arithmetic subtest within the Wechsler intelligence scale for children as an effective tool for measuring logical reasoning and working memory. The target sample consisted solely of adolescents, who were characterized by a similarity and a homogeneity in their developmental stages and ages. Selection and analysis criteria were based on two pillars, the general scores obtained in the arithmetic subtest, and a systematic evaluation of the students’ aptitude and inclination toward using AI tools. The results concluded that there is a close correlation between arithmetic ability and the quality of logical reasoning in AI contexts. Furthermore, statistically significant homogeneity confirmed that students proficient in AI skills demonstrate higher levels of creative thinking and the ability to apply logic in learning.
Developing a transdisciplinary design-based in-service science teacher training framework Joelash R. Honra; Ma. Kristina B. B Dela Cruz; Jermae B. Dizon-Yi; Raianne Joy V. Maulion; Sean Derrick M. Oliquiano; James C. Ollero; 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.v15i4.38783

Abstract

Contemporary science education requires teachers to facilitate learning that addresses complex, real-world problems beyond disciplinary boundaries. Yet, many in-service science teachers lack professional development that supports transdisciplinary problem-solving and innovative pedagogy. This qualitative study used a grounded theory (GT) approach to examine teachers’ experiences in a transdisciplinary, design-based training program and to develop a framework for effective professional learning. Participants engaged in sustained training grounded in design thinking and authentic problem contexts. Data were collected through semi-structured interviews, focus groups, reflective journals, training artifacts, and observations, and analyzed using constant comparative methods. Findings indicated shifts in teachers’ conceptions of problem-solving, enhanced capacity to integrate disciplinary and non-disciplinary perspectives, and changes in instructional planning and classroom practice. Design thinking functioned as a mediating process that helped teachers navigate ambiguity, collaboration, and iterative reflection. The resulting transdisciplinary design-based in-service science teacher training framework highlights key principles: authentic problem contexts, structured yet flexible design processes, collaborative inquiry, and iterative reflection. The study offers an empirically grounded framework with implications for teacher professional development, curriculum design, and policy.
Soft skills development in future foreign language teachers: evidence from digital educational artifacts Akbike Boranbayeva; Gulnur Yerik; Svetlana Minasyan
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.v15i4.38727

Abstract

In the context of digital transformation in teacher education, the development of soft skills among future foreign language teachers has become an important dimension of professional preparation. This qualitative case study aimed to identify the factors shaping soft skills development through the analysis of digital educational artifacts created in a technology-enhanced learning environment. The study involved 48 undergraduate students enrolled in a foreign language teacher education program during one academic semester. The data corpus included reflective essays, discussion posts, collaborative project outputs, multimedia assignments, and digital portfolios produced within a learning management system (LMS)-based course. Content analysis and thematic coding were used to identify recurring patterns in the artifacts. The findings revealed five interrelated groups of factors influencing soft skills development: pedagogical design and teaching methods, pedagogical strategies and learning activities, communication and collaboration in digital environments, organization and management of learning activities, and professional and personal development. The results show that digital educational artifacts provide rich evidence of authentic soft skills manifestation beyond traditional self-report methods. The proposed five-factor model may serve as a practical framework for teacher educators and curriculum designers in digitally mediated teacher education.
Writing a research paper with artificial intelligence: a step-by-step guide for junior researchers Emad Al-Mahdawi; Nkaepe Olaniyi
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.v15i4.38930

Abstract

Early-career researchers often have a sound idea yet struggle to turn it into a publishable manuscript that reviewers can trace and evaluate. This paper synthesizes practical guidance on structuring and drafting research articles using the introduction-methods-results-and-discussion (IMRaD) convention, while addressing emerging concerns about the responsible use of generative artificial intelligence (AI) in academic writing. A documentary narrative synthesis was conducted using 36 high-authority sources, including writing guides, guidance from journal editors, publisher and ethics policies, and recent empirical studies on AI-assisted writing. Recommendations were coded using an explicit IMRaD-aligned codebook and then consolidated into a step-by-step workflow from question formulation to submission checks. The synthesis indicates that treating IMRaD as a traceability checklist improves alignment between research questions, methods, results, and claims, and that iterative revision is more effective than one-pass drafting. AI support is most defensible when limited to language and process assistance, combined with disclosure, reference verification, and full human accountability for all content. The paper concludes with an actionable checklist and a visual ‘traceability map’ that can be adapted for research training and supervision.

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