International Journal of Education, Technology and Science

TEACHING NON-SPECIALIZED SUBJECTS: CHALLENGES AND COPING STRATEGIES OF PRIVATE HIGH SCHOOL TEACHERS IN PILA, LAGUNA

2026-04-26T19:28:35+00:00

This study investigated the challenges encountered by private high school teachers in Pila, Laguna who were assigned to teach subjects beyond their field of specialization, as well as the coping strategies they used to manage these demands. Utilizing a descriptive-comparative research design, data were gathered from teachers across several private schools through a validated questionnaire. The respondents represented diverse backgrounds in terms of age, gender, and teaching experience. Findings showed that teachers generally experienced a moderate level of difficulty when handling subjects outside their specialization. Challenges were most evident in aspects such as teaching competence, content mastery, and pedagogical knowledge. Among the specific difficulties reported, the preparation of lesson plans and instructional materials for unfamiliar subjects emerged as the most demanding task. Despite these challenges, teachers demonstrated strong adaptability. They frequently employed a range of coping strategies, including problem-focused approaches, avoidance mechanisms, supportive methods, and adaptive techniques, allowing them to navigate the requirements of non-specialized teaching assignments effectively. Further analysis revealed that challenges related to content mastery, teaching competence, and pedagogical knowledge had a significant influence on the types of coping strategies teachers adopted. This relationship underscores the importance of equipping teachers with adequate support when they are required to teach beyond their specialization. The study concluded that, while teaching outside one’s expertise poses notable challenges, private school teachers in Pila remain resilient and resourceful. It recommended the implementation of targeted professional development programs, strengthened mentoring systems, and recognition initiatives to enhance teachers’ competence, confidence, and motivation when handling non-specialized teaching tasks.

MAPPING RESEARCH TRENDS IN TECHNOLOGY-ENHANCED L2 WRITING IN EFL CONTEXTS: A BIBLIOMETRIC ANALYSIS

2026-06-02T09:29:35+00:00

This study presents a comprehensive bibliometric and science mapping analysis of research on technology-enhanced second language (L2) writing in English as a Foreign Language (EFL) contexts. Although digital tools and artificial intelligence (AI) have increasingly influenced language education, a systematic understanding of research trends, intellectual structures, and thematic developments in L2 writing remains limited. To address this gap, a dataset of 221 articles published in Social Sciences Citation Index (SSCI)-indexed journals between 2010 and April 2024 was analyzed using VOSviewer and CiteSpace. The findings reveal a steady increase in research output, with major themes centering on automated writing evaluation (AWE), collaborative writing, digital writing environments, and feedback practices. Co-occurrence, co-citation, and burst analyses demonstrate the evolution of thematic clusters and the growing integration of pedagogical, linguistic, and technological perspectives. Emerging topics such as learner autonomy, data-driven learning, and AI-assisted writing tools indicate a shift toward more adaptive, personalized, and learner-centered approaches to writing instruction. Despite these developments, the findings suggest a continuing need for theoretically informed and interpretive research that can better connect innovation with pedagogical practice. Unlike previous reviews that focused on specific journals, technologies, or empirical studies, this study provides a comprehensive mapping of SSCI-indexed research over a fourteen-year period through the combined use of VOSviewer and CiteSpace. By identifying influential contributors, major research themes, and emerging directions, the study offers a valuable reference for researchers and practitioners and proposes a future research agenda for technology-enhanced L2 writing.

ARTIFICIAL INTELLIGENCE, DIGITAL SOCIAL NORMS, AND CREATIVE SUBJECTS IN EDUCATION

2026-06-11T15:47:39+00:00

In the digital environment, artificial intelligence and new social norms increasingly shape human cognition, behavior, creative capacity, and responsibility. This study examines the relationship among artificial intelligence, social norms, and creative subjects in digital culture. The research uses an interdisciplinary philosophical approach, combining conceptual analysis, academic literature synthesis, critical methods, and digital cultural approaches to clarify the relationship between technology, norms, and contemporary social life. The data were collected via academic works on social philosophy, artificial intelligence ethics, digital culture, and digital education. The steps of the methodology include conceptual analysis, document synthesis, theoretical comparison, and critique of technocratic mechanisms in digital life. The results of the study show that artificial intelligence both expands people's access to knowledge and information-processing capacity and poses the risk of standardizing cognition, impairing the ability to reflect, and increasing dependence on algorithmic systems. Social norms in the digital environment can support the stability of community life, but they can also become mechanisms of control that reduce individuals' subjectivity and creativity.

ACADEMIC PERMISSIBILITY IN LLM-ASSISTED WRITING: HOW CONTEXTUAL JUSTIFICATIONS SHAPE STUDENTS’ MORAL JUDGMENTS

2026-06-29T16:11:45+00:00

This paper investigates EFL students’ perceptions of ethical acceptability judgments of using Large Language Models (LLMs) into academic writing. In contrast to the simplistic view of acceptable/unacceptable use of LLMs, the present study models how specific contextual justifications shape students’ moral evaluations of LLM‑assisted writing. A cross-sectional within-subject design was used with 220 third-year EFL students at three public universities in Laghouat, Algeria, to rate the ethical acceptability of LLMs use to complete four writing assignments. Under a neutral baseline condition, participants assessed the use of LLM for completing the four assignments, as well as four single condition contexts (disclosure, accuracy verification, syllabus permission, and learning intent). Their ratings were analyzed using Δ‑effect scores (conditional minus baseline) to quantify condition effects above baseline and to describe task‑level differences in ethical acceptability. Contextual conditions increased ethical acceptability to different extents, with learning intent producing the largest positive shift (ΔM ≈ 1.6, d ≈ 0.7) and disclosure exerting only a small, non‑robust effect (ΔM ≈ 0.2, d ≈ 0.1). The baseline ratings also followed a clear gradient, which saw AI‑assisted proofreading as the most acceptable while paraphrasing was consistently least acceptable. Theoretically, the study adds value by supporting a conditional‑ethics perspective because it demonstrates how students’ moral considerations of LLMs use are dependent on learning-oriented and epistemically responsible frameworks rather than procedural cues like disclosure or syllabus permissions with no behavioral consequences. Practically, the paper advices that AI policies and pedagogy should be designed to encourage learning intent and verification activities as opposed to disclosure as a standalone requirement.

INVESTIGATING THE EFFECTS OF WEB 2.0 TOOLS TRAINING ON PRESERVICE TEACHERS’ PERCEPTIONS OF DIGITAL COMPETENCE, 21ST-CENTURY SKILLS, AND COMPETENCIES IN THE EDUCATIONAL USE OF WEB 2.0 TOOLS

2026-06-21T09:38:47+00:00

The purpose of this study was to examine the effects of training programs on the use of Web 2.0 tools in education designed for preservice teachers on their perceptions of digital competence, 21st-century skills, and Web 2.0 tool usage competencies. The study employed a one-group pretest–posttest experimental design and included 33 preservice teachers enrolled in the Faculty of Education at A state university during the spring semester of the 2023–2024 academic year. Data were collected using the Preservice Teachers’ Perceptions of Digital Competence Scale, the Multidimensional 21st-Century Skills Scale, and the Web 2.0 Tools Usage Competency Scale. Power analysis, descriptive statistics, and paired-samples t-tests were used for data analysis. The findings indicated that the training programs had statistically significant, positive, and moderate-to-high effects on preservice teachers’ perceptions of digital competence, 21st-century skills, and competencies in using Web 2.0 tools for educational purposes. Based on these findings, teacher education programs should incorporate systematic, practice-oriented Web 2.0 training and integrate such experiences into pedagogical and subject-specific teaching courses.

REINVENTING COMPREHENSIVE HUMAN EDUCATION IN THE AGE OF ARTIFICIAL INTELLIGENCE: A REALISTIC HUMANISTIC FRAMEWORK INTEGRATING EDUCATION, TECHNOLOGY, AND SOCIAL RESPONSIBILITY

2026-06-20T15:09:45+00:00

Artificial intelligence (AI), big data, and algorithmic technologies are transforming contemporary education by expanding access to knowledge, enabling personalized learning, and improving educational management. However, these technologies also raise fundamental concerns about human autonomy, reflective judgment, moral responsibility, social cohesion, and the technocratic reduction of education to efficiency and labor-market adaptation. This study aims to develop the Realistic Humanism Framework as a conceptual and normative foundation for reconstructing comprehensive human education in the age of artificial intelligence. Rather than conducting empirical measurement, the study employs philosophical analysis, literature-based synthesis, interdisciplinary interpretation, and normative theoretical construction. Drawing on classical theories of humanistic education and contemporary studies on AI, data society, and algorithmic governance, the article clarifies the relationship among education, technology, human subjectivity, and social responsibility. The analysis shows that education in the AI era should simultaneously cultivate four core capacities: cognitive capacity, reflective capacity, creative capacity, and responsibility capacity. The study concludes that comprehensive human education is necessary for orienting technological development toward human dignity, social justice, democratic participation, and the common good.

INTEGRATING PROBLEM-BASED LEARNING AND DEEP LEARNING TO ENHANCE MATHEMATICAL REASONING AMONG JUNIOR HIGH SCHOOL STUDENTS: EVIDENCE FROM A QUASI-EXPERIMENTAL STUDY

2026-08-05T07:31:03+00:00

Mathematical reasoning is a fundamental competency in contemporary mathematics education, yet many junior high school students continue to experience difficulties in constructing logical arguments, connecting mathematical concepts, and solving complex problems. This study examined changes in junior high school students' mathematical reasoning following the implementation of Problem-Based Learning (PBL) integrated with a Deep Learning approach. A quantitative one-group pretest–posttest quasi-experimental design was employed involving 30 Grade VIII students from a public junior high school in North Sumatra, Indonesia. The instructional intervention was implemented across four mathematics learning sessions on Systems of Linear Equations in Two Variables to promote meaningful learning, reflective thinking, and active problem solving. Data were collected using a validated mathematical reasoning test administered before and after the intervention. Descriptive statistics, the Kolmogorov–Smirnov normality test, paired-sample t-test, and N-Gain analysis were used. The findings revealed a statistically significant improvement in students' mathematical reasoning following the instructional intervention, with mean scores increasing from 41.73 in the pretest to 79.40 in the posttest (t(29) = 18.063, p < .001, Cohen's d = 3.30). Because the study employed a one-group pretest–posttest design, these findings indicate substantial within-group improvement following the intervention rather than definitive evidence of causal effectiveness. The mean N-Gain score of 0.64 indicated a moderate level of improvement. The results suggest that integrating PBL with a Deep Learning approach is associated with improvements in mathematical reasoning. The study contributes to innovative mathematics instruction and offers practical implications for improving teaching and learning in education.

THE APPLICATION OF INNOVATION, EMERGING TECHNOLOGIES, AND ARTIFICIAL INTELLIGENCE IN PHYSICAL EDUCATION INSTRUCTION: CHALLENGES AND OPPORTUNITIES AHEAD

2026-06-13T20:13:09+00:00

This systematic review and interpretive synthesis aimed to provide a comprehensive, evidence-based framework for the effective incorporation of emerging technologies and AI into physical education. The search was conducted in international and Persian databases, including PubMed, Scopus, Web of Science, SID and Noormags in order to identify studies published between 2015 up to 2024. The search process resulted in the identification of 1,283 records; after removal of the duplicated papers, title/abstract evaluation, and full-text evaluation of potential studies, 47 studies were selected for the current review (20 international studies and 27 Iranian studies). The quality of the studies included in the current review was evaluated using the Cochrane RoB 2, CASP and MMAT checklists. The technologies were categorized into three pedagogical levels: monitoring by means of wearable technologies, feedback provided through VR and video analysis, and somatization via AI-driven systems. While emerging technologies in physical education hold great promise for PE in terms of providing opportunities for personalization of instruction and increasing PE engagement, several barriers to adoption, including a number of ethical concerns (e.g. data privacy, algorithmic bias), the digital divide, and lack of preparation on the part of teachers to utilize technologies for teaching and learning physical education, need to be addressed. The current review drew attention to the strategic role of teachers in physical education and to the ways in which they can integrate emerging technologies into PE in order to realize physical education’s educational goals. The current review also highlighted several important research gaps including the scarcity of long-term studies conducted in regular school settings and the lack of locally grounded teaching models. The technologies reviewed in this article are enablers and not substitutes for teachers in physical education; thus, these technologies must be creatively combined with the teacher’s strategic role and within the framework of PE’s educational goals with support from professional development, local knowledge production, and equitable policymaking.