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27,438 Article Results

Pioneering educational frontiers: South Korea-ASEAN synergy in big data integration and future innovations

10.11591/ijere.v14i3.31828
Catherine Joy T. Escuadra , Ella Joy Avellanoza Ponce
This study examines the evolving trends in publication collaboration and research topics related to big data and education in South Korea and the Association of Southeast Asian Nations (ASEAN) region, analyzed through the lens of international relations (IR). Using scientometric methods, the study analyzed 2,427 publications from Web of Science (WoS) through R Studio and VOSViewer, highlighting a marked increase in publication volume, citation, and collaboration in recent years. The research focuses on key areas such as the integration of big data in teaching and performance assessment, the intersection of big data with artificial intelligence (AI), and the varying implementation frameworks across different countries. The findings reveal that while significant progress has been made, there is a need for more structured collaborative efforts. To enhance future research output and collaboration, the study recommends establishing international research networks, organizing joint projects, facilitating exchange programs, and investing in necessary infrastructure. Additionally, it suggests developing policy frameworks and securing funding to support these initiatives. Engaging industry partners and expanding collaborative networks are crucial for advancing the field and optimizing the application of big data in education.
Volume: 14
Issue: 3
Page: 2007-2017
Publish at: 2025-06-01

Addressing fraction comprehension: global perspectives and Malaysian educational strategies

10.11591/ijere.v14i3.33092
Syed Azman Syed Ismail , Siti Mistima Maat , Fariza Khalid
Understanding fractions is a significant challenge in mathematics education globally, including in Malaysia, where students often struggle with core concepts. These difficulties hinder their progression into advanced areas like ratios, proportions, and algebra. This paper proposes a conceptual framework to enhance students’ understanding of fractions, with a focus on the Malaysian education system. Drawing on literature and practices from international contexts, this paper emphasizes the importance of visual models, manipulatives, technology integration and real-world applications in teaching fractions. As a concept paper, it synthesizes key insights from educational theories to develop strategies for improving fraction education. The framework highlights the need for alignment with both local and international curriculum. Key findings suggest that the use of manipulatives, visual models and technology can significantly improve fraction comprehension. By comparing global strategies, this paper offers insights into how these methods can be adapted to diverse learning environments, including low-resource settings. The framework implies that curriculum reforms, professional development for teachers and revised assessments are crucial to enhancing student outcomes in fraction education.
Volume: 14
Issue: 3
Page: 2107-2117
Publish at: 2025-06-01

The impact of innovative technology on shaping digital design skills in primary school students: a case study of Kazakhstan

10.11591/ijere.v14i3.32777
Saltanat Anapiyayeva , Gulnar Uaisova , Almash Turalbayeva , Sabira Nishanbayeva
The trajectory of digital progress in Kazakhstan has highlighted several challenges within the primary education system. A critical component of developing digital design skills (DDS) lies in the impact of innovative educational technologies on these skills. Despite the potential of such technologies to enhance DDS and engage students in digital literacy, the existing literature falls short in exploring this area comprehensively. The study aims to examine students’ DDS and examines how innovative educational learning technology affects these skills. This study used a quantitative research approach to measure innovative educational learning technology's impact on primary school students’ DDS. The experiment involved 120 participants and uncovered several key insights. The deficiency in DDS and lack of motivation revealed by the study called for systematic changes in how digital literacy is taught. These changes included restructuring curricula, enhanced teacher training, access to digital resources, and more engaging, practical learning environments. The study demonstrated substantial improvements in students’ DDS following the introduction and testing of the author's academic program with the experimental group (EG) participants. The findings from this study can serve as a foundation for developing strategies to enhance DDS in primary school and provide a methodological basis for adapting educational programs to support DDS development.
Volume: 14
Issue: 3
Page: 2389-2399
Publish at: 2025-06-01

Challenges of educational leaders’ utilization of educational portal information systems

10.11591/ijere.v14i3.31984
Hamed Hilal Nasser Al Yahmadi , Yousuf Nasser Said Al Husaini
The study aims to determine the challenges that hinder the adoption of educational portal information systems by Omani educational leaders, in order to explore the manner through which their capabilities can be improved. Moreover, the study uses quantitative research through the questionnaire as the main research instrument. The research population consisted of all educational leaders of the educational portal information systems in the Sultanate of Oman. The research sample included 96 individuals from the study population, selected using a convenience sampling method. Moreover, the study findings concluded that the challenges hinder the adoption of educational portal information systems obtained a moderate response degree, whereas the requirements for developing educational portal information systems obtained a very high response degree. Moreover, there were no statistically significant differences in the challenges hinder the adoption of educational portal information systems and the requirements for their development attributed to the variable of gender, years of experience, technological competency, and job position. Lastly, the study recommends the necessity to encourage leaders to participate in workshops and to keep educational leaders continuously updated on the latest improvements of the educational portal is necessary.
Volume: 14
Issue: 3
Page: 1961-1971
Publish at: 2025-06-01

The impact of leader motives in students: a systematic review

10.11591/ijere.v14i3.31418
Anil DCosta , Joseph Chacko Chennattuserry , G. S. Prakasha
Leader motives elucidate the driving forces behind leadership behavior and decision-making, which are pivotal for understanding effective leadership dynamics across diverse contexts. In this context, the systematic literature review (SLR) analyzed leader motives among students, providing insights into the underlying drivers shaping leadership behaviors within educational environments. This paper aims to understand how leader motives impact student behavior, academic performance, and social dynamics within educational environments. Based on McClelland’s needs theory as a conceptual framework, the review examines students’ prevalence and manifestations of achievement, power, and affiliation motives. This study systematically reviewed 16 papers, scholarly databases, and pertinent literature published between 2007 and 2024. A preferred reporting items for systematic reviews and meta-analysis (PRISMA) method was used to report the items. The findings underscore the importance of nurturing leader motives in educational settings, which contribute to positive student outcomes and foster leadership development through the lens of need theory. This study contributes to understanding how leader motives can elevate leadership behaviors and outcomes, offering valuable insights for policymakers and academic leaders aiming to enhance educational quality.
Volume: 14
Issue: 3
Page: 2144-2153
Publish at: 2025-06-01

Perceptions of the generative AI-enabled cognitive offload instruction in English writing

10.11591/ijere.v14i3.33138
Hui Hong , Poonsri Vate-U-Lan , Chantana Viriyavejakul
This study examines the students’ perceptions of the generative artificial intelligence (AI)-enabled cognitive offload instruction and its effectiveness in improving their critical thinking skills in writing English essays. This qualitative research collects data from 120 students through focus group discussions and is analyzed by Word Clouds to generate a visual representation of the word frequencies. The findings reveal that generative AI-enabled cognitive offload instruction had: i) an impact on critical thinking and writing skills; ii) effective features of Skywork, ability to generate relevant prompts and provide constructive feedback; iii) use of Skywork in developing stronger arguments; iv) promoting critical examination of different perspectives; v) interactive nature and motivation; vi) enhanced analytical skills; vii) impact on essay structuring and organization; viii) feedback and revision process; and ix) transferability of critical thinking skills. This study concludes that the highest frequency was Skywork, ability, writing, feedback, evidence, skills, thinking, arguments, essays, and peers. Students recommend in-depth explanations for complex topics, advanced tutorials, regular updates, collaboration features, advanced modules, and personalized learning paces to enhance Skyworks’s integration into instruction.
Volume: 14
Issue: 3
Page: 1761-1769
Publish at: 2025-06-01

An improved internal and external resilience framework for new high school teachers

10.11591/ijere.v14i3.31186
Wan Mohd Agil Mat Yamin , Lim Hooi Lian
The concept of resilience gained widespread recognition in the teaching profession as some new high school teachers are confronted with various challenges and pressures, which cause some of them to leave the profession during the first four to five years of their employment. By considering the guidance new high school teachers need to survive and retain their profession, this qualitative study aimed to identify resilient strategies used by new high school teachers. This study focuses on semi-structured interviews with twelve new high school teachers. After performing a thematic analysis, this study found internal and external resilience, with five strategies new high school teachers use to overcome challenges and pressures (internal: professional, emotional, and motivational; external: social and spiritual). This study validates the applicability of Mansfield’s four-dimensional teacher resilience frameworks (professional, emotional, motivational, and social resilience) to the resistance of new high school teachers in Malaysia. This study also improved Mansfield’s framework through its findings by considering a new dimension, spiritual resilience. The Malaysian Ministry of Education, specifically through public universities that train future high school teachers, can use these resilient strategies to develop intervention programs that enhance their resilience, thereby fulfilling the objectives of the Malaysia Education Development Plan (MEDP) 2013–2025.
Volume: 14
Issue: 3
Page: 1608-1620
Publish at: 2025-06-01

Enhancing educational outcomes using AlAfnan taxonomy: integrating cognitive, affective, and psychomotor domains

10.11591/ijere.v14i3.33147
Mohammad Awad AlAfnan
Following the introduction of AlAfnan’s taxonomy of educational objectives, this study offers a framework for educational development encompassing cognitive, affective, and psychomotor domains essential for nurturing well-rounded learners. The cognitive domain emphasizes knowledge acquisition, critical thinking, ethical reasoning, practical application, creativity, and lifelong learning skills. It prepares students to analyze, synthesize, and evaluate information effectively, fostering intellectual depth and adaptability in navigating complex challenges. The affective domain focuses on emotional intelligence, creativity, resilience, collaboration, and visionary thinking. By cultivating these attributes, educators create a supportive environment that encourages self-awareness, empathy, and ethical decision-making. This domain prepares students to excel academically and contribute meaningfully to society, emphasizing holistic personal development alongside academic achievement. The psychomotor domain enhances sensory perception, cognitive-motor integration, feedback responsiveness, creative motor expression, precision, and leadership through physical action. It equips learners with practical skills and dexterity, enabling them to effectively apply theoretical knowledge in real-world contexts. This domain emphasizes hands-on learning experiences that promote mastery, innovation, and leadership in various fields. The study emphasizes that integrating AlAfnan’s taxonomy into educational practices requires strategic alignment of instructional methods and assessment approaches tailored to each domain’s objectives. Educators are encouraged to utilize inquiry-based learning, collaborative projects, experiential activities, and reflective practices to foster comprehensive skill development across all learning styles. This shall foster students’ intellectual curiosity, emotional resilience, and practical competence. This framework promotes a balanced educational approach that prepares learners to thrive in diverse professional settings and contribute actively to global challenges.
Volume: 14
Issue: 3
Page: 2419-2437
Publish at: 2025-06-01

Multiple-cutoff regression discontinuity designs in educational evaluation

10.11591/ijere.v14i3.31081
HyeonJin Yoon , Keith Zvoch , Keith Smolkowski , Ben Clarke
The regression discontinuity design (RDD) can be used for evaluating cut-score based educational interventions. The design enables researchers and evaluators to estimate the local causal effect of an intervention provided to those who are most at-risk. In certain educational evaluations, an RDD with multiple cutoffs can also be applied, where different cutoffs across classrooms or schools are used to assign students to the intervention condition. The availability of multiple cutoffs allows estimation of a pooled average treatment effect across cutoffs and/or individual estimates at each cutoff location, allowing for the possibility of heterogeneous treatment effects. The purpose of this paper is to demonstrate the design and analysis of the multiple-cutoff regression discontinuity (MCRD) design for the evaluation of need-based educational programs. Using data obtained from a kindergarten mathematics intervention for low achieving students, we illustrate the utility of the MCRD design for examining the average and potential variability of the regression discontinuity (RD) treatment effect. Implications for evaluation research and practice in education are discussed.
Volume: 14
Issue: 3
Page: 1597-1607
Publish at: 2025-06-01

Exploring patient-patient interactions graphs by network analysis

10.11591/ijai.v14.i3.pp1752-1762
Zaher Salah , Esraa Abu Elsoud , Kamal Salah
Understanding how patient demographics and shared experiences impact interactions is essential for strengthening pa/tient support networks and optimizing health outcomes as personalized healthcare becomes more and more important. To this end, this study explores the patient-patient interactions (PPIs) graph as a network and applies selected network analysis approaches to examine the PPIs network of accutane drug. Two main research questions are addressed by gaining deeper insight at the hidden patterns of reactivity and connectivity among interchanging nodes. There was a negative response to the first research question, which asked if patients react to others that have similar gender and/or age profiles in a consistent way. Patients tended to interact with people of different genders and ages, indicating a high degree of heterogeneity in the network. Negative responses were likewise given to the second research question, which asked if communities inside the network could identify patients based on gender or age profile. Network analysis approaches for community detection failed to distinguish between groups with similar demographic characteristics. Rather, groups seemed to emerge based on other factors, like similarity in patient opinions. The results imply that gender and age do not have a major influence on community membership. Future research will concentrate on applying more sophisticated graph mining techniques to expand these approaches to cover more and larger PPIs networks.
Volume: 14
Issue: 3
Page: 1752-1762
Publish at: 2025-06-01

LMS bot: enhanced learning management systems for improved student learning experiences using robotic process automation

10.11591/ijai.v14.i3.pp2044-2054
Mamidyala Durga Prasad , Nandini Balusu
In this paper, a workflow for bot is designed using robotic process automation (RPA) that is used to enhance learning management systems (LMS) by providing content from external sources along with educator made course content for better student learning experiences. Many students prefer to watch YouTube videos for learning, even if they have been taught the same content by an educator. YouTube is a dynamic platform where video rankings change based on viewer engagement, relevance, and newly included videos. This variability poses a challenge for educators seeking to include external videos, as the content environment within the LMS platform is unpredictable and can change significantly. The bot addresses the challenge by conducting periodic searches for related courses and topics on YouTube. It retrieves top-ranked videos based on relevance, which are then seamlessly integrated into external links within LMS. The LMS external links option enhances accessibility by offering videos sorted by popularity, ensuring students receive updated and relevant information seamlessly. The bot efficiently retrieves details of 750 videos from YouTube in just 17 seconds, showcasing its exceptional performance. Moreover, its capability to autonomously update LMS external links content weekly represents an added advantage. The bot is designed and tested using UiPath tool.
Volume: 14
Issue: 3
Page: 2044-2054
Publish at: 2025-06-01

BioTapSync: revolutionizing data synchronization with human touch

10.11591/ijai.v14.i3.pp2528-2536
Sohil Shah , Harshal Shah
Human Tap introduces a new way to ensure secure data transmission synchronization by integrating advanced technologies. Motivated by the need for secure and efficient communication, it uses both near field communication (NFC) and human field communication (HFC) to provide a wide range of secure communication solutions. The aim is to create a system with detailed specifications, including maximum coverage range, frequency of operation, type of communication, and data rate for each protocol. These specifications are tailored for various applications, such as credit card payments, e-ticket bookings, E-ZPass systems, and item tracking. A notable contribution of Human Tap is its ability to achieve microsecond-level accuracy for distances up to 2 cm by thoroughly analyzing the relationship between distance and time. This innovative synchronization method not only ensures a secure data transmission environment but also shows remarkable flexibility, effectively addressing the challenges of modern communication systems. Human Tap sets a new benchmark for secure and adaptable data transmission technologies, paving the way for future advancements in the field. The objective is to establish a robust and versatile data transmission method that can be adapted to a wide range of modern applications.
Volume: 14
Issue: 3
Page: 2528-2536
Publish at: 2025-06-01

Addressing the challenges of overweight and obesity: strategies for promoting a healthier future

10.11591/ijphs.v14i2.24677
Irfan Chaudhuri , Md. Shahidul Islam
The prevalence of overweight and obesity among over 1 billion people worldwide constitutes a major public health concern. There is an increased risk for the onset of noncommunicable diseases such as type 2 diabetes, cardiovascular diseases, and various types of cancer, while productivity and life quality are diminished. The social, environmental, and behavioral influences on obesity and overweight can be mitigated through targeted interventions, as these conditions are largely avoidable. This study explores the latest findings on the causes, consequences, and remedies for overweight and obesity, with a global perspective. Additionally, it outlines several effective measures and strategies that have been put into place or are being considered in various contexts, including financial constraints, marketing limits, primary healthcare options, and school-based initiatives. To change the obesity epidemic and promote healthy eating and active living for everyone, the research calls for immediate action and a useful strategy that promotes healthy eating and diet, increased physical exercise, and modifications to environmental elements.
Volume: 14
Issue: 2
Page: 936-950
Publish at: 2025-06-01

Camera-based advanced driver assistance with integrated YOLOv4for real-time detection

10.11591/ijai.v14.i3.pp2236-2245
Keerthi Jayan , Balakrishnan Muruganantham
Testing object detection in adverse weather conditions poses significant chal lenges. This paper presents a framework for a camera-based advanced driver assistance system (ADAS) using the YOLOv4 model, supported by an electronic control unit (ECU). The ADAS-based ECU identifies object classes from real-time video, with detection efficiency validated against the YOLOv4 model. Performance is analysed using three testing methods: projection, video injection, and real vehicle testing. Each method is evaluated for accuracy in object detection, synchronization rate, correlated outcomes, and computational complexity. Results show that the projection method achieves highest accuracy with minimal frame deviation (1-2 frames) and up to 90% correlated outcomes, at approximately 30% computational complexity. The video injection method shows moderate accuracy and complexity, with frame deviation of 3-4 frames and 75%correlated outcomes. The real vehicle testing method, though demand ing higher computational resources and showing a lower synchronization rate (> 5 frames deviation), provides critical insights under realistic weather condi tions despite higher misclassification rates. The study highlights the importance of choosing appropriate method based on testing conditions and objectives, bal ancing computational efficiency, synchronization accuracy, and robustness in various weather scenarios. This research significantly advances autonomous ve hicle technology, particularly in enhancing ADAS object detection capabilities in diverse environmental conditions.
Volume: 14
Issue: 3
Page: 2236-2245
Publish at: 2025-06-01

A comparative study on electricity load forecasting using statistical and deep learning approaches

10.11591/ijeecs.v38.i3.pp1540-1552
Tehreem Fatima Butt , Sana Tameer , Muhammad Saleem , Jawwad Sami Ur Rehman , Sathish Kumar Selvaperumal
Load forecasting has become reproving aspect of an energy management system (EMS). It gives basic advantage to grid stability, cost effectiveness and battery storage system (BSS). For this purpose, machine learning (ML) is widely adopted to forecast the electricity load. This research paper investigates the performances of various time series estimating models applied to electricity load data for an Irish company. The research mainly adopts the autoregressive integrated moving average (ARIMA) model, long short-term memory (LSTM) networks and transformer neural network (TNN) to forecast the electricity load. A comparison evaluation is conducted encompassing various quantifying measures such as root mean square error (RMSE), mean square error (MSE) and mean absolute error (MAE). The results are then compared to get an understanding whether the TNN using attention-based mechanism is better than the two state of the art models. Hence provides a complete understanding about which of the model needs improvements in its architecture for enhancement of operational efficiency and cost effectiveness in the realm of EMS.
Volume: 38
Issue: 3
Page: 1540-1552
Publish at: 2025-06-01
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