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31,291 Article Results

Constructivist-based teacher education and pre-service teachers’ instructional competence for fostering cognitive activity

10.11591/ijere.v15i5.40296
Bakytkul Yessentayeva , Sazhila Nurzhanova , Askarbek Kussainov , Assel Tanatova , Bakyt Aidarkhan , Iroda Kholdorova
This study examines the effect of a constructivist-based teacher education (CBTE) program on pre-service primary teachers’ (PST) instructional competence for fostering cognitive activity (IC-CA). A quasi-experimental pretest–posttest control group (CG) design was employed with 180 pre-service teachers assigned to experimental (n=90) and control (n=90) groups using stratified allocation within intact cohorts. The intervention consisted of a 12-week program incorporating problem-based learning, collaborative tasks, microteaching, and reflective activities. Results indicated a statistically significant difference in adjusted posttest instructional competence scores in favor of the experimental group (EG) after controlling for baseline performance. Although both groups showed improvement over time, gains were greater in the experimental condition. The findings suggest that structured constructivist teacher education is associated with enhanced development of multidimensional instructional competence for fostering cognitively engaging teaching practices, including instructional design, learner interaction, pedagogical questioning, reflection, and instructional decision-making. The study provides empirical evidence that practice-oriented constructivist learning environments can support the development of such competence in pre-service teachers.
Volume: 15
Issue: 5
Page: 4256-4266
Publish at: 2026-10-01

Virtual laboratories and online learning in engineering education: a review

10.11591/ijere.v15i5.39538
Hamza Abu Owida , Areen Arabiat
The rapid expansion of virtual laboratories and online learning in engineering education, accelerated by the COVID-19 pandemic, has created an urgent need for clearer pedagogical guidance on how digital laboratory modalities should be used. This review addresses the unresolved educational problem of ensuring that virtual and remote laboratory environments support not only conceptual understanding but also practical laboratory skills and broader professional competencies. Using a structured review of recent empirical studies, systematic reviews, and meta-analyses, the paper synthesizes evidence on simulation-based laboratories, remote laboratories, immersive environments, and the wider online learning conditions that shape their effectiveness. The review finds that virtual laboratories are consistently effective for conceptual learning, visualization, flexibility, and access, while remote and immersive environments can strengthen authenticity and practical skill development when combined with active learning, multimodal assessment, and strong instructional support. However, persistent limitations remain in psychomotor skill development, assessment validity, accessibility, and institutional readiness. The review concludes that no single modality is sufficient on its own; rather, a hybrid model that pedagogically integrates virtual, remote, immersive, and physical laboratory experiences offers the most defensible pathway for meaningful and sustainable engineering laboratory education.
Volume: 15
Issue: 5
Page: 3857-3869
Publish at: 2026-10-01

The STUDIES model: validating a human-centric framework for Education 5.0

10.11591/ijere.v15i5.39645
Phichittra Thongpanit , Pratya Thongpanit , Sutep Uamcharoen
This study addresses the gap in teacher education frameworks that integrate Education 5.0 principles with empirically validated metacognitive development. The purpose was to develop and validate a seven-stage human-centric instructional framework, the setting goals, task analysis, universal design, digital learning, integrated knowledge, evaluation, standards-based assessment (STUDIES) model, grounded in constructivism, self-determination theory, and digital humanism, and to evaluate its effectiveness across three sequential phases with pre-service teachers. Three published phases employed one-group pretest–posttest designs. Phase I (N=24, English education) achieved efficiency ratios E1/E2 of 80.56/80.68 (t(23)=26.17, p
Volume: 15
Issue: 5
Page: 3677-3689
Publish at: 2026-10-01

Evaluating integrity and governance efficiency in blockchain-supported online assessment

10.11591/ijere.v15i5.39221
Aivar Sakhipov , Laura Smagulova , Aigul Yelepbergenova , Alexey Fedenko
With the increasing deployment of remote proctoring systems, there is a noticeable gap in online testing governance due to the lack of credible evidence, which might have adverse implications in terms of trust between the testing platform and its participants. This study, therefore, examines the potential impact of blockchain-powered evidence management on auditability and audit process efficiency in the context of online examinations. In our study, we used an experimental research method and examined the impact of tamper-proof distributed ledger technology on auditability and audit time using a sample of 160 exam sessions divided equally into two groups: a control group (CG, n=80) and an experimental group (EG, n=80). The findings suggest a positive and statistically significant influence of blockchain adoption on auditability (12.5% higher), reaching 96.3% compared to 83.8% in the CG, as well as a 37% reduction in audit time. Furthermore, the inter-rater agreement level reached 0.846. Notably, based on our surveys, test-takers find the process more credible and legitimate without any increased privacy concerns.
Volume: 15
Issue: 5
Page: 4068-4079
Publish at: 2026-10-01

Enhancing educators’ digital literacy through digital leadership and organizational culture

10.11591/ijere.v15i5.39153
Sugiarto Sutomo , Heni Rochimah
Despite rapid advances in digital technology and online learning, educators at the education and training center face limited digital access, low information and communication technology (ICT) proficiency, and difficulty integrating technology, reflecting the slow national rise in digital literacy. This study tests whether strengthening digital leadership and aligning organizational culture can improve educators’ digital competencies. A cross-sectional survey of 120 educators was analyzed using path analysis in JASP. Findings indicate that digital leadership strongly predicts organizational culture (β=0.869, z=28.834, p
Volume: 15
Issue: 5
Page: 3777-3789
Publish at: 2026-10-01

The impact of digital comics as a teaching and learning tool in economics education on future-ready talent development: the mediating role of attitude

10.11591/ijere.v15i5.37622
Hainnuraqma Rahim , Abd Hadi Mustaffa , Norashida Othman , Putri Aliah Mohd Hidzir
Economics education at the tertiary level dominated by text-heavy materials that often disengage students. At the same time, the potential of digital comics as an innovative pedagogical alternative are insufficiently examine. Hence, this study examines the impact of digital comics (IMP) on students’ learning in economic subjects at Universiti Teknologi MARA (UiTM) Melaka, with particular focus on the mediating role of attitude (ATT). A quantitative design was employed using structured questionnaires distributed to 146 diploma and degree students to measure the determinants of perceived IMP. Data were analyzed using the partial least squares– structural equation modeling (PLS-SEM). The findings show that ATT and subjective norms (SN) significantly influence the IMP, while digital literacy (DL) and perceived behavioral control (PBC) exhibit no direct effects. In addition, ATT significantly mediates the relationships with SN, PBC and the IMP. Practically, the findings suggest that lecturers can embed digital comics into case-based class activities to enhance engagement and conceptual understanding. The novelty of the study indicated that this is the first studies applying theory of planned behavior (TPB) to digital comics in economic education. This study also offers future research which can be extend the studies into experimental, longitudinal and cross-sectional.
Volume: 15
Issue: 5
Page: 4192-4206
Publish at: 2026-10-01

Gamification and MOOC persistence: an integrated UTAUT2–SDT–engagement model

10.11591/ijere.v15i5.37547
Waraporn Jirapanthong , Siwakorn Banluesapy
Massive open online courses (MOOC) completion rates remain low despite the continued growth of online learning platforms. This study examined the factors influencing learning persistence (PERS) in gamified MOOCs using an integrated unified theory of acceptance and use of technology 2-self-determination theory (UTAUT2–SDT)–engagement (ENG) model. A cross-sectional survey was conducted with 200 MOOC learners in Thailand, and the data were analyzed using partial least squares structural equation modeling (PLS-SEM). The results showed that student ENG significantly predicted behavioral intention (BI) (β=0.352,p
Volume: 15
Issue: 5
Page: 4657-4666
Publish at: 2026-10-01

BDLock: A blockchain-enabled two tier privacy-aware federated idam service platform using RBAC

10.11591/ijece.v16i5.pp2537-2548
Muhammad Shakil Pervez , Md. Nasim Adnan , Sarker Tanveer Ahmed Rumee , Moinul Islam Zaber
Centralized identity and access management (IDAM) systems suffer from sin-gle points of failure, lack of authorization transparency, and susceptibility to in-sider threats and privilege abuse. While role-based access control (RBAC) of-fers structured permission management, its enforcement through centralized pol-icy engines introduces auditability gaps unacceptable in modern distributed service delivery environments. This paper presents BDLock, a blockchain-enabled two-tier privacy-aware federated IDAM platform integrating OAuth 2.0, OpenID Connect (OIDC), and Hyperledger Fabric 2.4. The first tier validates JSON Web Tokens (JWT) issued by Keycloak against a Spring Boot resource server, the second tier enforces immutable scope-based RBAC rights on the Hyperledger Fabric ledger, ensuring every access decision is tamper-proof and auditable. Unlike prior approaches, BDLock uniquely bridges OAuth-authenticated off-chain identities to cryptographic on-chain Fabric wallet identities, satisfying all six STRIDE-modelled threats categories across both Web2 and Web3 identity models. Validated with up to 1,800 concurrent users, BDLock achieves a peak throughput of approximately 200 transactions per second using round-robin load balancing. At high concurrency, it outperforms single-peer fallback by up to 25%. Furthermore, it maintains uninterrupted access control during peer failures, eliminating the single point of failure found in all nine compared state-of-the-art systems.
Volume: 16
Issue: 5
Page: 2537-2548
Publish at: 2026-10-01

Design science research in developing a religious chatbot based on Bulugh al-Maram

10.11591/ijece.v16i5.pp2782-2794
Aris Tjahyanto , Irmasari Hafidz , Faizal Johan Atletiko
Chatbots have recently gained significant popularity. For instance, ChatGPT has become a preferred tool for many individuals seeking instant answers without relying on human responses. This immediacy sets chatbots apart from books, which require users to search for information manually. This time-consuming process does not align with millennials' preference for convenience and efficiency. Studying hadith independently using the Bulugh al-Maram book demands considerable time and effort. The limited use of natural language processing technologies in religious chatbots restricts their ability to handle complex inquiries effectively. A chatbot capable of answering hadith-related questions could greatly assist the public in studying hadith texts by providing direct responses without extensive searching. This chatbot was designed for web browsers, utilizing deep learning as its core technology. This research led to the development of a chatbot prototype for learning hadith from Bulugh al-Maram. Built using the design science research (DSR) methodology, the prototype achieves an intent recognition rate (IRR) of 86.82%. However, its capabilities are below the BERT model, demonstrating a strong ability to accurately interpret user questions and statements.
Volume: 16
Issue: 5
Page: 2782-2794
Publish at: 2026-10-01

Calibration-guided score fusion for robust multimodal traffic anomaly detection

10.11591/ijece.v16i5.pp2516-2525
Quang Hiep Do , Thien Tan Nguyen
Multimodal traffic anomaly detection is affected by differences in visual and audio score ranges, temporal fluctuations, and unstable decision thresholds. This paper proposes a calibration-guided score fusion (CGSF) framework that processes video frames and audio spectrograms through separate reconstruction-based models. The resulting anomaly scores are temporally smoothed, normalized using validation data, and combined at the score level. A percentile estimated from normal validation samples is then used as the decision threshold. The framework was evaluated on the MAVD and DADA2000 datasets. On MAVD, CGSF achiev,,,,,,ed a ROC-AUC of 0.553, a PR-AUC of 0.082, and an F1-score of 0.129. It outperformed direct fusion in precision, recall, and F1-score, although the gain in ROC-AUC was small. Analysis on DADA2000 showed smoother temporal score behaviour after calibration and smoothing. The results indicate that CGSF mainly improves score comparability and threshold consistency rather than producing a large increase in detection accuracy. Its modular design also allows the visual and audio branches to be trained and updated independently.
Volume: 16
Issue: 5
Page: 2516-2525
Publish at: 2026-10-01

Conceptualizing cultural adaptation through game-based learning among international students: evidence from a systematic scoping review

10.11591/ijere.v15i5.39174
Yoon Shwe Sin , Ophat Kaosaiyaporn , Warapark Maitreephun
International students frequently experience acculturative stress and social isolation during their transition to higher education. This systematic scoping review investigates how game-based learning (GBL) serves as a structured experiential system to support this cultural transition. Following the preferred reporting items for systematic reviews and meta-analyses extension for scoping reviews (PRISMA-ScR) protocol and population, concept, and context (PCC) framework, we screened five academic databases (2015–2025), identifying eight peer-reviewed articles from an initial pool of 608 records. Data were synthesized using a three-stage thematic analysis to map the structural pathways between pedagogical design and adaptation outcomes. The results indicate that GBL design elements, such as immersive simulations and role-play, foster cultural awareness by activating core learning mechanisms like social negotiation and reflective feedback. These findings reveal a three-layered conceptual architecture where GBL facilitates shifts across cognitive, affective, and behavioral dimensions to support identity-level transformation. This study implies that GBL can move beyond superficial engagement to provide a predictive roadmap for educators. Ultimately, this framework advances theoretical understanding by reconceptualizing adaptation as an iterative, mechanism-driven learning process rather than a passive transition, offering a theoretically grounded approach for designing robust cultural adaptation (CA) interventions in higher education.
Volume: 15
Issue: 5
Page: 4144-4154
Publish at: 2026-10-01

Mapping trends in mathematics graduate theses

10.11591/ijere.v15i5.40078
Julie A. Buasen , Nick W. Sibaen , Monica S. Alimondo
Despite the increasing use of thesis archives to study research trends, there is still limited work that closely examines what graduate research in mathematics education focuses on within specific institutional contexts. This study explores the research trends and thematic orientations of Master of Arts (MA) in mathematics theses to inform curriculum development and future research directions. Using a qualitative content analysis approach, 129 theses completed between 2000 and 2024 were examined through their titles, abstracts, and statements of the problem. Through inductive coding and thematic synthesis, five major domains emerged: predictive and correlational studies (PCS) (31.78%); instructional interventions and innovations (III) (28.68%); assessment of mathematics readiness, achievement, and curriculum (AMRAC) (24.81%); cultural and contextual dimensions of mathematics learning (CCDML) (8.53%); and affective, motivational, and self-regulated learning in mathematics (AMSRLM) (6.20%). The findings point to a strong concentration on performance-oriented and quantitatively driven studies, particularly those using correlational and intervention-based approaches. This pattern reflects both the accessibility of quantitative methods and the program’s emphasis on measurable outcomes. In contrast, studies that explore affective and sociocultural aspects of learning remain limited, although there are signs of gradual growth in more recent years, especially in work that adopts qualitative and culturally grounded perspectives. These patterns suggest that graduate research is shaped not only by educational priorities but also by the structure of the program and the type of methodological training students receive. Overall, the study highlights the need to broaden the scope of inquiry toward more context-sensitive and interdisciplinary approaches, and it offers insight into how thesis work reflects the evolving directions of mathematics education research.
Volume: 15
Issue: 5
Page: 4588-4601
Publish at: 2026-10-01

Improving PaddleOCR optical character recognition for food composition labels using hybrid SymSpell and LayoutLM correction

10.12928/telkomnika.v24i5.27607
Ahmad; Universitas Qomaruddin Wahyu Rosyadi , Siti; Universitas Qomaruddin Ma’shumah , Muhammad; Institut Teknologi Sepuluh Nopember Qomaruz Zaman
A high level of text recognition accuracy is crucial for optical character recognition (OCR) applications, particularly those designed to extract information from food composition labels. However, packaging materials often introduce distortions, reflections, or irregular printing, which lead to recognition errors and word concatenation. To mitigate this issue, this study proposes a novel post-processing system that integrates PaddleOCR with the spelling correction (SymSpell) algorithm and layout language model (LayoutLM)-guided bigram-based word segmentation to enhance OCR accuracy. The implementation begins with capturing a composition label image using a smartphone camera, followed by initial text extraction performed by PaddleOCR. Consequently, SymSpell corrects misspelled tokens through a domain-specific food and beverage lexicon, while LayoutLM leverages spatial and contextual information to separate concatenated words. The performance was evaluated using the character error rate (CER) metric across four packaging surface categories: flat, curved, reflective, and textured. The results demonstrate consistent improvements across all categories, achieving an average CER of 0.0991, with the greatest reduction on flat surfaces (from 0.0885 to 0.0659). The experiments show that the system is robust across label conditions, lightweight for real-time use, and domain-aware. Its model-agnostic design adds flexibility, enabling effective post-OCR correction across different engines and improving readability for real-world food label applications.
Volume: 24
Issue: 5
Page: 1668-1679
Publish at: 2026-10-01

Real-time multimodal fatigue detection using facial vision and alert integration via ESP32 for occupational health applications

10.11591/ijece.v16i5.pp2750-2768
Andrés Enrique Rojas Primo , Alfredo Lazaro Gutierrez , Felix Pucuhuayla-Revatta
Early detection of work fatigue is a major challenge in industrial settings due to the lack of non-invasive, accessible, and low-cost systems capable of operating in real time. In this context, this research proposes a multimodal real-time fatigue detection system using facial vision and artificial intelligence, aimed at risk prevention and promoting occupational health. The system integrates geometric and behavioral parameters, such as eye aspect ratio (EAR), head tilt, and mouth opening, processed on a Raspberry Pi 5 using MediaPipe and a hybrid convolutional neural network (CNN) MobileViT model. Visual and audible alerts are managed by an ESP32 microcontroller using the message queuing telemetry transport (MQTT) protocol, while a graphical interface developed in Tkinter allows real-time monitoring of operator status. Experimental results, evaluated in a simulated work environment using AI-generated synthetic videos, show an accuracy greater than 97% and a latency of less than 250 ms, confirming the system's effectiveness in the early detection of signs of drowsiness and attention deficit. In conclusion, the proposal represents a non-invasive, scalable, and efficient solution that combines computer vision, deep learning, and the Internet of Things (IoT) to strengthen workplace safety and well-being.
Volume: 16
Issue: 5
Page: 2750-2768
Publish at: 2026-10-01

Robust resource allocation in multi-cell UE-specific RIS-assisted D2D relay networks under imperfect CSI

10.11591/ijece.v16i5.pp2575-2594
Kayode Popoola , Ayodeji Ajani , Stuart Nicholson , Muheeb Ahmed , Srilatha Narayangari Pamuri , Ibrahim Bala Alhassan
Device-to-device (D2D) communication enhances spectral efficiency but remains constrained by limited transmission range, underlay interference, and the half-duplex overhead of conventional relays. User equipment-specific reconfigurable intelligent surfaces (UE-RIS) offer a promising alternative by enabling passive beamforming to strengthen D2D links without additional spectrum consumption. However, existing studies typically assume perfect channel state information (CSI) and single-cell operation, limiting their applicability to practical deployments. This paper proposes a robust multi-cell resource allocation (RMRA) framework for UE-RIS-assisted D2D relay networks under imperfect CSI. A hybrid uncertainty model is adopted, combining statistical Gauss-Markov CSI errors for intra-cell links with bounded norm-ball uncertainty for inter-cell links. The joint optimisation of resource reuse, transmit power allocation, and RIS phase configuration is formulated as a stochastic mixed-integer nonlinear program that maximises network spectral efficiency while satisfying outage and quality-of-service constraints. To efficiently solve the problem, a three-stage algorithm is proposed comprising distance-pruned Hungarian assignment, robust power control using Bernstein-type inequality and S-procedure based semidefinite programming, and soft actor-critic (SAC) based passive beamforming. Simulation results show that RMRA achieves a 94% D2D access rate at light load and over 75% at full load, improves sum spectral efficiency by 34.7% and 70.2% over AF relaying and direct D2D, respectively, attains 118.5 bits/s/Hz/W energy efficiency, and maintains 30.2 bits/s/Hz under severe CSI uncertainty.
Volume: 16
Issue: 5
Page: 2575-2594
Publish at: 2026-10-01
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