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28,451 Article Results

Teaching competencies and entrepreneurial performance among the Hashemite University faculty members

10.11591/ijere.v14i5.33166
Hytham M. Bany Issa , Zohair H. Al-Zoubi , Omar T. Bataineh , Hassan Mohammad Bani-Issa , Awad Faek Altarawneh
The study examines the application of teaching competencies among faculty members at Hashemite University and investigates their relationship with perceived entrepreneurial performance within a quality assurance framework. Using a descriptive-relational survey design, a sample of 340 faculty members was selected through stratified sampling during the first semester of the 2022/2023 academic year. Data were collected via a validated questionnaire measuring teaching competencies across five domains—personal, academic, administrative, cultural, and professional—and entrepreneurial performance. The findings indicated that both teaching competencies and entrepreneurial performance were at a moderate level. A positive and statistically significant relationship was identified across all competency dimensions and entrepreneurial performance, suggesting that enhanced competencies can positively impact entrepreneurial outcomes. Based on these results, the study recommends integrating teaching competency evaluations into university quality assurance policies and suggests combining intrinsic and extrinsic incentives to foster faculty productivity. These recommendations offer valuable insights for enhancing academic standards and fostering entrepreneurial skills among faculty in higher education.
Volume: 14
Issue: 5
Page: 3557-3564
Publish at: 2025-10-01

Boosting algebra mastery through activity-based learning in an indigenous peoples education secondary school

10.11591/ijere.v14i5.33969
Rolly Najial Apdo , Rachel Basañez Apdo
Algebra is a fundamental area of mathematics, yet many students, particularly indigenous learners, struggle with its concepts and procedures. This study examines the impact of activity-based learning on the conceptual understanding and procedural skills of junior high school students in an indigenous peoples education (IPEd) school. Using a mixed-methods approach, 105 indigenous students from grades 7 to 9 at Daan Taligaman Integrated Secondary School (DTISS), Philippines, participated. Pre-test and post-test scores were analyzed using a paired-samples t-test, while thematic analysis explored students’ learning experiences. The results revealed significant improvements in both conceptual understanding and procedural skills, with grade 7 scores increasing from 41.08% to 80.38% (conceptual) and 34.83% to 74.13% (procedural). A similar trend was apparent for the grades 8 and 9 students. Key themes identified were engagement and enjoyment, increased confidence, and improved understanding. The study highlights the effectiveness of interactive, culturally responsive learning strategies in enhancing algebra mastery among indigenous students and calls for their integration into mathematics education.
Volume: 14
Issue: 5
Page: 4029-4039
Publish at: 2025-10-01

Job performance of human resource management graduates from the employers’ and graduates’ perspectives

10.11591/ijere.v14i5.31959
Dahlee Sadang-Pascua , Jennifer Montenegro-Villanueva
Graduates’ job performance reflects their academic orientation in pursuit of their degrees. Thus, academic institutions should prepare students to be competitive, match the needs of the industry, and become worthy of employment after graduation. This research determines the job performance of human resource management (HRM) graduates in terms of their job competencies, career skills, and team performance from the perception of the graduates and their employers. A quantitative research method with statistical tools such as frequency, percentage, weighted mean, and Mann-Whitney U Test was used. Findings revealed a significant difference in the respondents’ perception, specifically in conveying ideas, use of IT, values, quality work, communication skills, human relations, technical, research, leadership skills, and team performance. The result also shows that graduates perceived themselves as excellent performers, which is in contrast to their employers’ perceptions of them as good performers only regarding their job competencies, career skills, and team performance. The differences in perceptions of the performance of the graduates depicts a mismatch between the academe and the industry requirements that result in a recommendation of thorough review and revision of the HRM curriculum, the teaching methodology, and the strategy of the academic institutions to meet the needs of the industry.
Volume: 14
Issue: 5
Page: 3756-3764
Publish at: 2025-10-01

Exploring error patterns in English writing: a pathway to innovative multimodal instructional material

10.11591/ijere.v14i5.33677
Joshua B. Tupas , Jr., Salvador P. Bacio
Considered as a crucial element that leads to better academic performance, Filipino learners always aim to master English language skills. Among various factors that affect the learning of English language skills, the availability of resources that cater to a diverse set of learners is important. Using semiotic or multimodal resources may help teachers assist students in enhancing their macro skills in the English language. This developmental research aimed to design, develop and evaluate a multimodal instructional material (IM) based on students identified common errors in writing. English major education students were selected as participants as they are important role-players in enhancing the future generation of learners in the English language. There were 39 freshman bachelor of secondary education (BSEd) English major students, three English teachers, two curriculum experts, and one information technology expert participated in the study. A panel of experts validated the instruments, which included the questionnaire to gauge the respondents’ writing skills, the adapted rubric for writing proficiency, and the adapted evaluation form for printed IM exclusively used by the university. Results of the study revealed that the respondents’ writing skills were poor. The evaluation conclusively showed that the IM was very acceptable for classroom use and teaching. It was recommended that the developed multimodal IM be used as a supplementary workbook to facilitate the need for primary English textbooks for the freshman BSEd English major students.
Volume: 14
Issue: 5
Page: 3367-3378
Publish at: 2025-10-01

Factor influencing of teachers’ readiness to implement the Independent Curriculum

10.11591/ijere.v14i5.29141
Fitra Delita , Tumiar Sidauruk , Alna Hanana , Mona Adria Wirda
The education curriculum in Indonesia is gradually changing from the 2013 Curriculum to the Independent “Merdeka” Curriculum. The new curriculum is certainly a challenge for teachers. The aim of this research is to analyze the factors that influence teacher’s readiness and to measure the level of teacher readiness in implementing the Independent Curriculum. This quantitative research was designed using a survey method. The participants involved were 172 teachers from elementary, middle, and high school education levels in Medan City, Indonesia. Data were collected using online questionnaires and interviews. Data analysis was conducted using descriptive statistics using mean scores, factor analysis, and multiple linear regression t-test. The research results show the level of teachers’ readiness in implementing the Independent Curriculum based on gender, age, and years of teaching experience, both at elementary, middle, and high school levels with a mean interval of 6.00–6.99 (the initiation level). Subsequently, there are four dominant factors that influence teachers’ readiness to implement the Independent Curriculum, which are teacher, school, government policy, and student. The teacher factor contributed the most in determining teachers’ readiness to implement the Independent Curriculum (43.7%).
Volume: 14
Issue: 5
Page: 4173-4182
Publish at: 2025-10-01

The underlying physics concept of a soccer game as a catalyst for enhancing creative thinking skills

10.11591/ijere.v14i5.32682
Ida Sriyanti , Mardiah Afifa , Meilinda Meilinda , Anisya Sefina Puteri , Nyimas Aisyah , Wahyu Indra Bayu , Zulkardi Zulkardi , Ratu Ilma Indra Putri , Hapizah Hapizah
Teachers need to improve students’ creative thinking skills by incorporating relevant everyday contexts. Soccer, as a familiar part of daily life, has not been widely used in education, and its impact on creative thinking requires further study. This research aimed to develop a contextual physics e-module centered on soccer to enhance creative thinking in physics learning. The study followed Rowntree's development model, including planning, development, and evaluation, with Tessmer’s formative evaluation through expert reviews, one-on-one assessments, small-group evaluations, and field tests. The creative thinking indicators used in the research are fluency, flexibility, originality, and elaboration. Data were collected from 346 high school students in Palembang via walkthroughs, questionnaires, and written tests, then analyzed using SPSS version 16. The results showed that the soccer-based physics e-module is valid (Sig. 0.00), practical (one-to-one: 82.75%; small group: 91.00%), and in the moderate category for improving creative thinking (N-gain: 0.59). These findings highlight the need to explore other everyday contexts and assess the long-term impact of the e-module across different educational settings.
Volume: 14
Issue: 5
Page: 3712-3726
Publish at: 2025-10-01

Facial image analysis for autism spectrum disorder detection in toddlers using deep learning and transfer learning

10.11591/ijece.v15i5.pp4856-4864
Anupam Das , Prasant Kumar Pattnaik , Anjan Bandyopadhyay
Autism spectrum disorder (ASD) is a neurological illness that manifests itself through restricted and repeated activity patterns, frivolous or recidivist interests or hobbies and consistent handicaps to social interactions and exchanges. Better results and early intervention are dependent upon the early identification of people with ASD. Doctors employ a variety of techniques to anticipate autism, including genetic testing, neuropsychological testing, hearing and vision screenings, and diagnostic interviews. In addition to requiring more time and money, the traditional diagnosis approach makes the parents of children with extensive developmental abnormalities feel too inadequate to disclose their condition. So, we need a tool that can detect autism early in less time and money. Machine learning methods can be used to fulfill this criterion. In this study, deep learning with transfer learning (VGG-16) is used to detect autism through facial images of children and achieved almost 97% accuracy. The suggested model significantly improves accuracy and saves time and money by using face features in photos of children to identify early autism tendencies in children.
Volume: 15
Issue: 5
Page: 4856-4864
Publish at: 2025-10-01

New approximations for the numerical radius of an n×n operator matrix

10.11591/ijece.v15i5.pp4732-4739
Amer Hasan Darweesh , Adel Almalki , Kamel Al-Khaled
Many mathematicians have been interested in establishing more stringent bounds on the numerical radius of operators on a Hilbert space. Studying the numerical radii of operator matrices has provided valuable insights using operator matrices. In this paper, we present new, sharper bounds for the numerical radius 1/4 ‖|A|^2+|A^* |^2 ‖≤w^2 (A)≤1/2 ‖|A|^2+|A^* |^2 ‖, that found by Kittaneh. Specifically, we develop a new bound for the numerical radius w(T) of block operators. Moreover, we show that these bounds not only improve upon but also generalize some of the current lower and upper bounds. The concept of finding and understanding these bounds in matrices and linear operators is revisited throughout this research. Furthermore, the study emphasizes the importance of these bounds in mathematics and their potential applications in various mathematical fields.
Volume: 15
Issue: 5
Page: 4732-4739
Publish at: 2025-10-01

Real time object detection for advanced driver assistance systems using deep learning techniques

10.11591/ijece.v15i5.pp4942-4953
Sudarshan Sivakumar , Shikha Tripathi
Object detection plays a critical role in advanced driver assistance systems (ADAS), where timely and accurate detection of objects on road is essential for vehicular safety. In this study, we propose and evaluate deep learning-based object detection techniques—specifically, convolutional neural networks (CNN) and dense neural networks for real-time object detection. The proposed model is trained on a publicly available image dataset demonstrating its potential to enhance the reliability of ADAS systems without the use of an image preprocessing block. Here the system automatically stops without any human intervention. Our results highlight the strengths and limitations of using CIFAR-10, CIFAR-100 and YOLO datasets for transfer learning, pre-training and algorithm classification. Improvements in model optimization and hardware integration have been achieved using hardware in loop (HIL) set up. The models are evaluated on CIFAR-10, CIFAR-100 and YOLO datasets, with a focus on the impact of image pre-processing on detection accuracy and speed. Experimental results show that the proposed algorithm outperforms the previous methods, by achieving a better accuracy, contributing to safer and robust system without an additional image preprocessing block.
Volume: 15
Issue: 5
Page: 4942-4953
Publish at: 2025-10-01

Enhancing source currents and ensuring load voltage stability in railway electrification system via unified power quality conditions implementation

10.11591/ijece.v15i5.pp4430-4444
Kittaya Somsai , Jeerapong Srivichai , Veera Thanyaphirak
In recent years, interest in electric railway system as a transportation solution for large urban areas has grown significantly. This increased attention stems from several key advantages, including environmental friendliness, high performance, reduced maintenance costs, and lower energy expenses. Railway electrification system rely on supplying power to trains through single-phase transformers. However, these transformers can cause issues such as current imbalances and harmonics at the system connection point, which may impact critical loads. Additionally, fluctuations in source voltage can influence the system's performance. This study examines the causes of unbalanced loading in railway electrification system and introduces an innovative unified power quality conditioner (UPQC) specifically designed for integration into low-voltage railway electrification system. The proposed UPQC aims to restore current balance, minimize harmonics, and enhance overall power quality. Furthermore, it addresses the mitigation of voltage sags in the power distribution network. The simulation results generated through MATLAB programming demonstrate the UPQC's effectiveness in enhancing system performance. The findings reveal that the UPQC reduces source current imbalance to less than 1.6% and total harmonic distortion (THD) to below 4.89% across all test scenarios. Additionally, the UPQC successfully maintains a load bus voltage of 25 kV during single-phase-to-ground and unbalanced three-phase-to-ground fault conditions.
Volume: 15
Issue: 5
Page: 4430-4444
Publish at: 2025-10-01

Prospective applications of assistive robotics for the benefit of population groups

10.11591/ijece.v15i5.pp4531-4541
Anny Astrid Espitia-Cubillos , Robinson Jimenez-Moreno , Javier Eduardo Martínez-Baquero
The development of robotics has reached various fields of application such as the assistance field, where robots support people with different abilities in different activities to provide independence, comfort and interaction, even improving their self-esteem and quality of life. The objective is to identify the main benefits of the application of assistive robotics achieved to project its future fields of action. For this purpose, the Scopus database is used to find documents related to assistive robotics, which are filtered by publication date and according to the elimination criteria determined by the authors, and then bibliometric networks are constructed using VOSviewer. Finally, the main findings are analyzed and presented according to their area of application. Five areas of application of assistive robotics are identified that benefit children, the elderly, provide hospital assistance, help people with disabilities or support therapy and rehabilitation work, developments that allow the formulation of areas for future study. It is concluded that there are many advances in assistive robotics that demonstrate robotic development and provide assistance to a particular population, but more work is still needed to increase the number of beneficiaries, reduce costs and expand research in the areas mentioned and to be developed.
Volume: 15
Issue: 5
Page: 4531-4541
Publish at: 2025-10-01

Practical specification of the speech universe of the maximum power point tracking controller based on the asymmetrical fuzzy logic: a dynamic behavior study of the photovoltaic system

10.11591/ijece.v15i5.pp4355-4365
Ahmed Amine Barakate , Sami Choubane , Abdelkader Hadjoudja
In this paper, we present a procedure for extracting data from a stand-alone photovoltaic (PV) panel to program a maximum power point tracking (MPPT) controller based on the fuzzy logic (FL) method, aiming to optimize the performance of the photovoltaic system. Photovoltaic data acquisition enables the determination of the input and output speech universe for the MPPT controller using fuzzy logic. This method adapts to nonlinear systems without requiring a complex mathematical model. Additionally, it improves the performance of the photovoltaic system in both dynamic and steady-state conditions. To further enhance the method’s efficiency, an asymmetric membership function concept is proposed based on the dynamic behavior study of the photovoltaic system. Compared to the symmetric method, the asymmetric fuzzy logic controller achieves higher maximum power output and better tracking precision. This technology is essential for maximizing photovoltaic panel efficiency, a key requirement as solar energy gains prominence as a clean and renewable energy source.
Volume: 15
Issue: 5
Page: 4355-4365
Publish at: 2025-10-01

Dynamic head pose estimation in varied conditions using Dlib and MediaPipe

10.11591/ijece.v15i5.pp4581-4592
Rusnani Yahya , Rozita Jailani , Nur Khalidah Zakaria , Fazah Akhtar Hanapiah
This paper presents the formulation and validation of a dynamic head pose estimation (HPE) algorithm, addressing challenges related to diverse conditions, complex poses, and partial obstructions. The study aims to create a robust algorithm that maintains high accuracy in real-time applications across varying conditions. The algorithm was implemented and assessed using Dlib and MediaPipe models. The study involved 30 participants in face and head without obstacles, face with obstacles and head with obstacles conditions. The results demonstrated impressive performance in both controlled and spontaneous head movement categories. The algorithm achieved an average accuracy of 93% for head pose estimation and 88% in detecting visual attention under spontaneous head movement categories. A correlation coefficient of 0.866 indicates a strong positive linear association between performance and attention accuracy, indicating that performance improvements are intricately linked to proportional increases in attention accuracy. However, this does not necessarily imply causation. The findings provide valuable insights into the effectiveness of the proposed algorithms in assessing visual attention and demonstrate their potential applications in healthcare monitoring, educational intervention, and driver monitoring systems. The significance of these results lies in the ability to advance human-computer interaction, enhance healthcare diagnostics, and offer innovative solutions across various domains.
Volume: 15
Issue: 5
Page: 4581-4592
Publish at: 2025-10-01

Discount factor-based data-driven reinforcement learning cascade control structure for unmanned aerial vehicle systems

10.11591/ijece.v15i5.pp4542-4554
Ngoc Trung Dang , Quynh Nga Duong
This article investigates the discount factor-based data-driven reinforcement learning control (DDRLC) algorithm for completely uncertain unmanned aerial vehicle (UAV) quadrotors. The proposed cascade control structure of UAV is categorized with two control loops of attitude and position sub-systems, which are established the proposed discount factor-based DDRLC algorithm. Through the analysis of the Bellman function's time derivative from two perspectives, a revised Hamilton-Jacobi-Bellman (HJB) equation including a discount factor is developed. Then, in the view of off-policy consideration, an equation is formulated to simultaneously solve the approximate Bellman function and approximate optimal control law in the proposed DDRLC algorithm with guaranteed convergence. According to the modified state variables vector, the development of the discount factor-based DDRLC algorithm in each control loop is indirectly implemented by transforming the time-varying tracking error model into the time invariant system. Finally, a simulation study on the proposed discount factor-based DDRLC algorithm is provided to validate its effectiveness. To validate the tracking performance of the quadrotor, four performance indices are considered, including IAE_p=3.0527, IAE_Ω=0.1175, ITAE_p=1.8408, and ITAE_Ω=0.0144, where the subscript p denotes position tracking error and Ω denotes attitude tracking error.
Volume: 15
Issue: 5
Page: 4542-4554
Publish at: 2025-10-01

A computational study of passive cooling of photovoltaic panels using hybrid material heat sink

10.11591/ijece.v15i5.pp4487-4499
Dang Van Binh , Pham Quang Vu , Pham Manh-Hai
Photovoltaic panels generate electricity from solar energy based on the photovoltaic effect. The conversion efficiency of photovoltaic panels depends on many factors such as solar radiation, wind speed, dust, orientation, tilt angle, and operating temperature. When the operating temperature increases by 1 C, the conversion efficiency of photovoltaic panels decreases by 0.4% - 0.5%. Heat sink is a device used to cool electrical and electronic equipment, including photovoltaic panels. This paper presents calculating the cooling capability of hybrid heat sink made from two materials in steady state using heat transfer theory. Heat sink base is constructed from aluminum and copper layers, with copper layer thickness is 1 and 2 mm. Under different conditions of radiation intensity, wind speed, and tilt angle of photovoltaic panel, results show that heat sink added copper layers of 1 and 2 mm, the operating temperature decreases by about 0.6 K and 1.2 K compared to the aluminum base. Accordingly, the conversion efficiency of photovoltaic panel increased by 0.1% and 0.2%.
Volume: 15
Issue: 5
Page: 4487-4499
Publish at: 2025-10-01
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