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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

An evaluation of counselling approach on communication apprehension among students in higher education

10.11591/ijere.v14i3.29619
Nor Hernamawarni Abd Majid , Nor Shafrin Ahmad , Rahimi Che Aman , Nik Rosila Nik Yaacob , Nur Hikmah Mubarak Ali
Communication apprehension is a major challenge in higher education, affecting students’ communication ability, which is crucial for academic success and future employability. It manifests as public speaking anxiety, reluctance in group discussions, and avoidance of classroom interactions, hindering soft skill development and academic performance. This study aims to evaluate the effectiveness of counselling approaches in reducing communication apprehension among students in higher education. Consequently, counselling intervention modules, including the solution-focused brief cognitive behavior (SFBCB) therapy and group counselling (GC) modules, were developed. Sixty students who participated in this study were studying at a public university. Pre-tests, post-tests, and follow-up tests were administered using the personal reports of communication apprehension questionnaire to measure changes in apprehension levels across different communication contexts, including group discussions, meetings, dyadic interactions, and public speaking. The results demonstrated that both intervention modules significantly reduced communication apprehension, with improvements in participants’ confidence and communication abilities. In conclusion, the study highlights the effectiveness of integrating solution-focused and cognitive-behavioral techniques in counselling interventions to mitigate communication apprehension. These findings suggest that such approaches can be valuable tools in higher education to enhance students’ communication skills, ultimately contributing to their academic success and personal growth.
Volume: 14
Issue: 3
Page: 1674-1683
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

Autonomy support and motivation in private music students: the role of basic psychological needs

10.11591/ijere.v14i3.33168
Qin Xiong , Mohamad Fitri Mohamad Haris
The objective of this research was to measure the impact of autonomous support and expectancy beliefs on autonomous motivation of students. The study investigated the impact of basic psychological needs on autonomous support. Furthermore, the mediating role of basic psychological needs is also analyzed. Using simple random sampling, the study collected cross-sectional data from 305 students on a Likert scale questionnaire at private music schools located in Nanchang, China. SPSS 26 and Smart PLS 4 are used for descriptive and inferential statistics and findings. The study found that autonomy support, expectancy beliefs and basic psychological needs have a significant impact on autonomous motivation. The study also found that autonomy support and expectancy beliefs also have significant influence on basic psychological needs. While the study found that basic psychological needs mediate the impact of autonomy support and expected beliefs on autonomous motivation. In addition, measuring the dimension of autonomous support, the study found that parental support and teachers’ support have a significant impact on autonomous motivation. While the study found that parental support and teachers’ support also have a significant impact on basic psychological needs. The study further confirmed that basic psychological needs positively mediate the impact of parental support and teachers’ support on autonomous motivation.
Volume: 14
Issue: 3
Page: 2018-2030
Publish at: 2025-06-01

Research capability of Filipino teacher educators: insights from a criterion-referenced test

10.11591/ijere.v14i3.32849
Jay-cen T. Amanonce , Conchita M. Temporal , Rudolf T. Vecaldo , Jhoanna B. Calubaquib , Antonio I. Tamayao , Maribel F. Malana , Ria A. Tamayo , Marie Claudette M. Calanoga
The research capability of Filipino teacher educators has been found to be lacking, which limits their ability to contribute effectively to academic research. This study aims to assess their foundational knowledge in research, as understanding their capability is essential for improvement. A quantitative approach was employed, evaluating 100 teacher educators from a state university in Northern Philippines using the research capability test (RCT), a validated criterion-referenced tool. Results showed that teacher educators generally possess average research capability, with significant differences based on educational attainment, field of specialization, and research teaching experience. Those with doctoral degrees, specializations in natural sciences and mathematics, and experience teaching research demonstrate higher capability. These findings suggest that, while basic research knowledge exists, there is a critical need for focused professional development programs to address specific gaps. Strengthening research capability not only improves the teacher educators’ performance but also enhances the overall quality of research outputs in the Philippine education system, ensuring long-term academic growth and global competitiveness.
Volume: 14
Issue: 3
Page: 1706-1716
Publish at: 2025-06-01

Bridging technology and humanity: humanizing online pedagogy in digital environments

10.11591/ijere.v14i3.31937
Nor Asiah Razak , Che Zalina Zulkifli , Yusri Abdullah , Ahmad Zulfadhli Khairuddin , Aervina Misron , Piriya Somasundram , Azizova Gulnora Shakirdjanovna
Comprehensive analyses on incorporating the intersection of online education, humanizing teaching approaches, and digital tools remain scarce. To the best of the authors' knowledge, limited comprehensive studies integrate online pedagogy and digital tools to humanize teaching methods, enabling students to become engaged and personalized learners, while fostering empathy among educators. A systematic literature review (SLR) was conducted, utilizing databases from the Scopus, Web of Science (WoS), and Google Scholar. The study employed content and comparative analysis and advocated a grounded theory approach to inductively analyses and navigate the articles’ data for addressing three research questions. Based on a set of criteria for inclusion and exclusion, 34 research articles written in English between 2010 and 2024 were reviewed. Results indicated the community of inquiry (CoI) framework has been prominent over the past two decades and is considered suitable for integration with any digital tools when investigating pedagogical strategies at all education levels, aiming to make online learning student-centered or human-centered with the principle of ‘no child left behind'. The review offers significant implications for humanizing online learning to the educational technology community, particularly for policymakers and practitioners, to strategies, reflect on, and, if necessary, improve their practices for future sustainable education and efficient pedagogical performance. 
Volume: 14
Issue: 3
Page: 2207-2223
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

Aerobics research in China: characteristics, hotspots, and evolution visualized

10.11591/ijphs.v14i2.24889
Wang Yang , Zainal Abidin B Zainuddin
This study utilizes CiteSpace software to visually analyze 679 core journal papers from the CNKI database, exploring the landscape of aerobics research in China. It aims to identify influential authors and institutions while elucidating the evolution of research focus from its early stages to current trends. The primary objective is to explore the characteristics of aerobics research, including hot topics, evolving frontiers, and key developments. By examining titles, keywords, abstracts, and other materials, CiteSpace software provides insights into the scientific knowledge graph, emphasizing influential authors and institutions in aerobics research. The findings reveal a notable shift in focus from early public teaching to current emphasis on competitive aerobics, physical education, and athlete transitions. The research field has expanded to encompass diversified topics, showcasing continuous depth in empirical and theoretical investigations. Three distinct periods are identified in research frontiers: early, middle, and recent stages, each with unique directions and emphases. The study recommends a multi-disciplinary integrated development approach in aerobics research, emphasizing enriched teaching and competition visions, improved regional integration policies, and a comprehensive display of the field’s research and development status. Acknowledging evolving trends and diversification will contribute to a holistic understanding and continued advancement of aerobics research.
Volume: 14
Issue: 2
Page: 967-977
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

Novel artificial intelligence-based ensemble learning for optimized software quality

10.11591/ijai.v14.i3.pp1820-1828
Sangeetha Govinda , Agnes Nalini Vincent , Merwa Ramesh Babu
Artificial intelligence (AI) contributes towards improving software engineering quality; however, existing AI models are witnessed to deploy learning-based approaches without addressing various complexities associated with datasets. A literature review showcases an unequilbrium between addressing the accuracy and computational burden. Therefore, the proposed manuscript presents a novel AI-based ensemble learning model that is capable of performing an effective prediction of software quality. The presented scheme adopts correlation-based and multicollinearity-based attributes to select essential feature selection. At the same time, the scheme also introduces a hybrid learning approach integrated with a bio-inspired algorithm for constructing the ensemble learning scheme. The quantified outcome of the proposed study showcases 65% minimized defect density, 94% minimized mean time to failure, 62% minimized processing time of the algorithm, and 43% enhanced predictive accuracy.
Volume: 14
Issue: 3
Page: 1820-1828
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

Rooftops detection with YOLOv8 from aerial imagery and a brief review on rooftop photovoltaic potential assessment

10.11591/ijai.v14.i3.pp2282-2290
Md. Sabbir Ahmed , Md. Shohel Arman , Nusrat Tasnim , Md Hafizul Imran , Musabbir Smmak , Touhid Bhuiyan
Recent years have seen significant advancements in the switch from fossil fuel-based energy systems to renewable energy. Decentralized solar photovoltaic (PV) is one of the most promising energy sources since there is a lot of rooftop space, it is easy to install, and the cost of the PV panels is low. The determination of rooftop locations for PV installation is crucial for energy planning. With this context, this study aimed to detect the suitable rooftops of different shapes. The dataset of 5,076 building roofs used in this study was gathered by us utilizing a drone. This study identified ten distinct roof shapes accurately, including triangle, square, penta, hexa, hepta, octa, nona, deca, gabled roof, and hipped roof, using the most recent version of you only live once (YOLO), known as YOLOv8. Recent research revealed, YOLOv8 is more accurate than earlier YOLO models which is the reason of utilizing YOLOv8. Accuracy of this work of rooftops detection is 93.6%. Also, the precision, recall, and F1-score confidence curve showed good performances too. Finally, a brief review of the most recent studies on the evaluation of rooftop PV potential was conducted to provide insight into the use of solar energy.
Volume: 14
Issue: 3
Page: 2282-2290
Publish at: 2025-06-01

Optimizing real-time data preprocessing in IoT-based fog computing using machine learning algorithms

10.11591/ijai.v14.i3.pp1900-1909
Nandini Gowda Puttaswamy , Anitha Narasimha Murthy
In the era of the internet of things (IoT), managing the massive influx of data with minimal latency is crucial, particularly within fog computing environments that process data close to its origin. Traditional methods have been inadequate, struggling with the high variability and volume of IoT data, which often leads to processing inefficiencies and poor resource allocation. To address these challenges, this paper introduces a novel machine learning-driven approach named real-time data preprocessing in IoT-based fog computing using machine learning algorithms (IoT-FCML). This method dynamically adapts to the changing characteristics of data and system demands. The implementation of IoT-FCML has led to significant performance enhancements: it reduces latency by approximately 0.26%, increases throughput by up to 0.3%, improves resource efficiency by 0.20%, and decreases data privacy overhead by 0.64%. These improvements are achieved through the integration of smart algorithms that prioritize data privacy and efficient resource use, allowing the IoT-FCML method to surpass traditional preprocessing techniques. Collectively, the enhancements in processing speed, adaptability, and data security represent a substantial advancement in developing more responsive and efficient IoT-based fog computing infrastructures, marking a pivotal progression in the field.
Volume: 14
Issue: 3
Page: 1900-1909
Publish at: 2025-06-01
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