Articles

Access the latest knowledge in applied science, electrical engineering, computer science and information technology, education, and health.

Advanced Search
Filter Icon

Filters article

Years

FAQ Arrow
Single Year
Range Year
0
0

Source Title

FAQ Arrow

Authors

FAQ Arrow

29,061 Article Results

Design and psychometric validation of the research competency scale for university students in Peru

10.11591/ijere.v14i6.35752
Carmen Julia de los Milagros Luperdi-Román , Félix Fernando Goñi-Cruz , Angel Deroncele-Acosta
Research competence is essential for the academic and professional development of university students. However, in the context of Lima, Peru, no specific, valid, and reliable instruments have been found to assess this competency comprehensively. This deficiency reveals a significant knowledge gap in the accurate assessment of research competencies in university students. Therefore, in the present research, a scale was constructed and validated to effectively assess research competence in university students. As methodology, the quantitative approach was used, following three processes: item construction, item functionality, and psychometric analysis. A sample of 216 students was used for the exploratory factor analysis (EFA), and 206 for the confirmatory factor analysis (CFA). The final version of the research competency scale for university students comprises 37 items distributed across five dimensions identified through EFA: epistemic knowledge (10 items), interpretation skills (5 items), methodological knowledge (9 items), scientific communication (6 items), and information management (7 items). CFA supported the adequacy of the model (root mean square error of approximation/RMSEA=0.064; comparative fit index/CFI=0.918; Tucker-Lewis Index/TLI=0.911), and the scale demonstrated high internal consistency. The validated scale reliably measures research competence and can improve teaching, assessment, and curriculum design.
Volume: 14
Issue: 6
Page: 4887-4902
Publish at: 2025-12-01

New qualitative perspective in students’ English presentation skills in China-developing a student-based module

10.11591/ijere.v14i6.33708
Lifang Sun , Hanita Hanim Ismail , Azlina Abdul Aziz
Since English is the world’s lingua franca, English learners need to master communication skills to succeed in their respective fields. However, Chinese college students face the problem of separation between learning and using what they learned in the traditional English classrooms. This study aims to explore the university students’ needs of English presentation learning. The research questions are: i) What are the students’ language needs to improve an English presentation? ii) What are the skills needed when doing an English presentation? and iii) What are the students’ preferences in English presentation class? The researchers conducted focus-group interviews (FGI) which were participated by 30 students and semi-structured interview for five teachers to understand the students’ real needs and preferences in the process of learning English speaking. Three themes were generated by axial coding from the interview data: i) English language needs; ii) presentation skills’ needs; and iii) students’ preferences.The findings can help the teacher design the English-speaking class more effective and have adjustments according to students’ real productions using production-oriented approach in English presentation teaching.
Volume: 14
Issue: 6
Page: 5174-5186
Publish at: 2025-12-01

Determining student progression rates using discrete-time Markov chain model

10.11591/ijere.v14i6.32049
Mark John T. Mangsat , Daniel Bezalel A. Garcia , Andhee M. Jacobe , Maricel A. Bongolan
This study aims to analyze and understand the student progression from the Bachelor of Science in Mathematics (BS Math) program. A discrete-time Markov chain (DTMC) model was used to analyze data from 211 students enrolled from 2011-2012 to 2022-2023. The results reveal that there are students who will be retained in their year level, shift to another degree program, or drop. Additionally, the highest risk of shifting or dropping out of the program happens during the first two semesters in college or for first year in college. A bottleneck effect during the second year and third year was identified. Furthermore, the results suggest that there will be an approximately 35.22% graduation rate after eight semesters or four years, implying a large portion of BS Math students will be retained or dropped from the program, or shifted to other degree programs. To avoid such, it is suggested that the Mathematics and Natural Sciences Department should conduct review sessions, bridging programs, and continuous promotion. Lastly, it is suggested to conduct thorough studies about the possible intrinsic and extrinsic factors affecting the student progression to formulate a more specific intervention that may help in reducing the shifting and dropping rate.
Volume: 14
Issue: 6
Page: 4478-4486
Publish at: 2025-12-01

University students’ perceptions on developing constructivist learning approach in classroom settings

10.11591/ijere.v14i6.35117
Cuc Thi Doan , Tuan Van Vu , Ai Nhan Nguyen
This study investigated tertiary students’ perceptions regarding constructivist learning in the context of higher education in Vietnam. It aimed to examine the general perceptions of university students towards constructivist learning and the effects of constructivist learning on students’ learning outcomes. It also examined the conditions that make students more likely to embrace or resist these approaches. The study evaluated the engagement of students in problem-solving activities through the use of constructivist learning methods. A mixed-methods approach was employed, combining both quantitative and qualitative data. Specifically, the study involved a survey of 384 students from Hanoi Law University, using a researcher-made Likert-scale questionnaire and semi-structured interviews of 20 students from the sample. While descriptive and inferential statistics were used to analyze the quantitative data, the qualitative data were thematically analyzed for common themes and patterns. The results indicate that although the participants acknowledge the benefits of constructivist methods, particularly in fostering critical thinking and problem-solving, there is still uncertainty about their ability to engage in a self-directed learning approach. The findings suggest that while the constructivist approach has been recognized, practical efforts have not been made in teaching practices, teacher training, and assessment methods to create an interactive, student-centered learning environment in Vietnam.
Volume: 14
Issue: 6
Page: 4264-4275
Publish at: 2025-12-01

Students’ and teachers’ perceptions and experiences of using social media in learning foreign languages

10.11591/ijere.v14i6.34732
Le Thanh Nguyet Anh , Bui Thanh Tinh , Nguyen Van Canh
The benefits of social media applications have emerged as an advancement in teaching and learning foreign languages. However, it falls short of studies investigating the perspectives and experiences of educators and learners about social media usage in Vietnamese tertiary education contexts in rural areas. Therefore, this study examined the perceptions and experiences of teachers and students regarding the application of social media in foreign language learning at a university in the Mekong Delta, Southern Vietnam. The study was conducted with the participation of 199 students and 20 teachers. This study employed a mixed-methods approach, collecting data from questionnaires, and an in-depth interview. The findings showed that most teachers and students had a positive attitude towards applying this mode to teaching and learning foreign languages. However, they indicated some problems when utilizing those methods. Additionally, they suggested some measures for blending direct teaching and learning with social media based on their experience. The research results provided more insights into this field in the literature, especially in local settings.
Volume: 14
Issue: 6
Page: 5197-5208
Publish at: 2025-12-01

Perceptions of audiovisual media in vocabulary acquisition among English learners: benefits and challenges

10.11591/ijere.v14i6.34852
Xuan Hong Nguyen Thi , Thanh Thai Nguyen
Learning vocabulary through English audiovisual materials has long been a popular method among students. With the advancement of digital technology, this approach has gained even more attraction, leading to a growing number of studies that have investigated its effectiveness. However, there is a notable scarcity of research addressing the challenges that students face; therefore, the current study aims to explore students’ perspectives on the challenges along with the benefits of using audiovisual media as tools for learning vocabulary. This study was done through a quantitative approach using a questionnaire that included both open-ended and closed-ended questions. With the participation of 132 senior English-major students at Thu Dau Mot University in Vietnam, the study collected 117 valid questionnaires that provided valid data for analysis. Through descriptive statistics, the results reveal the improvements in pronunciation and listening skills, enhanced understanding of slang and idiomatic expressions, and increased exposure to the natural use of the target language. However, the findings also reveal that this method poses challenges for students, including misunderstandings stemming from the use of formal or informal language and an over-reliance on audiovisual media. Therefore, the study emphasizes the need for structured guidance to foster language learning outcomes.
Volume: 14
Issue: 6
Page: 5209-5218
Publish at: 2025-12-01

Emotional intelligence in teaching: a key to performance and institutional climate in basic education

10.11591/ijere.v14i6.34924
Benjamin Maraza-Quispe , Victor Hugo Rosas-Iman , Giuliana Feliciano-Yucra , Atilio Cesar Martinez-Lopez , Elizabeth Katherine Ortiz-Corimaya , Walter Choquehuanca-Quispe , Frida Karina Coasaca-Hancco , Luis Elfer Nuñez-Saavedra
This study addresses the lack of understanding regarding the relationship between emotional intelligence (EI), teaching performance, and institutional climate (IC) in basic education. As a solution, the study proposes evaluating and strengthening teachers’ EI to enhance both their performance and the school environment. Using a quantitative, non-experimental, correlational design, the research analyzed a randomly selected sample of 145 teachers. Validated questionnaires measured dimensions such as self-awareness, self-regulation, motivation, empathy, and social skills, as well as teaching preparation and IC. The results reveal significant positive correlations between EI and IC (r=0.85) and between teaching performance and IC (r=0.78). This suggests that higher EI not only improves teaching effectiveness but also fosters a positive institutional environment. The study concludes that enhancing teachers’ EI can optimize both their performance and institutional dynamics, contributing to higher-quality education. The findings support the implementation of EI training programs as a key strategy to improve teaching performance and the school climate (SC).
Volume: 14
Issue: 6
Page: 5054-5066
Publish at: 2025-12-01

Language learning strategies in relation to advanced Chinese vocabulary and writing proficiency

10.11591/ijere.v14i6.31857
Xinqin Liu , Mohammed Y.M. Mai
The study investigated the relationship between the language learning strategies (LLSs) employed by international undergraduate students at universities in Qinghai Province, China, and their proficiency in advanced Chinese vocabulary and writing. Data was collected from 45 advanced-level students selected through purposive sampling, using Oxford’s strategy inventory for language learning (SILL), an advanced Chinese vocabulary knowledge test, and advanced Chinese writing test scores. The descriptive analysis revealed moderate language learning strategy usage, with a preference for speaking and listening development. This result indicates a limited strategy usage. The correlation analysis showed no significant relationship between strategy usage and advanced Chinese vocabulary or writing proficiency. However, a strong relationship was observed between advanced Chinese vocabulary and writing proficiency. The absent relationship between strategy usage and proficiency levels suggests insufficient Chinese language proficiency among the students. The significant relationship highlights the crucial role of vocabulary in enhancing Chinese writing skills. The results provide practical insights for enhancing the use of strategies and vocabulary teaching to improve advanced writing and Chinese proficiency among international undergraduate students.
Volume: 14
Issue: 6
Page: 4844-4853
Publish at: 2025-12-01

Tailoring collaborative learning with jigsaw and VARK: a case study in teaching physics with environmental protection

10.11591/ijere.v14i6.32823
Ngan Hai My Le , Anh Thi Kim Nguyen
Collaboration is a crucial 21st century skill, requiring learning environments that foster teamwork while leveraging students’ individual strengths. This study aimed to enhance collaboration using the jigsaw strategy, which was adapted to students’ learning styles based on the model: visual, aural, read/write, and kinesthetic (VARK). The study involved 27 tenth-grade students in Ho Chi Minh City and focused on the topic “physics with environmental protection.” Students were initially grouped by learning styles into expert groups and later reorganized into mixed jigsaw groups to collaboratively address tasks related to environmental issues. A quasi-experimental design was employed, utilizing pre- and post-test self-assessment surveys, video observations, and group discussions to assess collaborative performance. Quantitative data were analyzed using the Wilcoxon signed rank test, while qualitative data provided deeper insights. Results demonstrated a significant improvement in team support (p=0.030), suggesting that aligning learning tasks with students’ styles foster group cohesion. However, participation and contribution showed minimal improvement, with students preferring reading/writing styles facing challenges in adapting to group activities. While the integration of jigsaw and VARK proved effective in enhancing collaboration, the study underscores the need to develop strategies to accommodate diverse learning preferences. Future research should involve larger sample sizes and consider teachers’ perspectives to optimize the practical implementation of learning styles in collaborative learning environments.
Volume: 14
Issue: 6
Page: 4364-4374
Publish at: 2025-12-01

Predicting Emirati student academic outcomes: school tracks and standardized tests

10.11591/ijere.v14i6.33951
Fatima Al-Ali , John Rice
Global education systems apply grouping strategies to enhance academic outcomes. The United Arab Emirates (UAE) has developed school tracks to address performance gaps by offering more varied high-school tracks while also creating a local Emirates Standardized Tests (EmSAT) for measurement. This study examines the impact of educational tracks in Emirati schools and EmSAT scores on UAE university students’ academic performance. A quantitative multivariate analysis of 3,190 University of Sharjah students compared the outcomes across different high school tracks and analyzed the predictive power of EmSAT scores on university cumulative grade point average (CGPA). EmSAT scores vary significantly by tracks, with elite students performing best, followed by those in the advanced and scientific tracks. Arabic and mathematics EmSAT scores predict CGPA more strongly than English, which has a moderate effect. General track students achieve higher CGPAs compared to other tracks, even after controlling EmSAT performance and gender, suggesting a complex relationship between high school experiences and university success. The findings highlight the track model’s effectiveness, with the elite fostering strong academic pathways. However, the overlap in university achievement between the general and advanced warrants further research. The study provides insights for policymakers to refine educational strategies and enhance student outcomes.
Volume: 14
Issue: 6
Page: 4592-4603
Publish at: 2025-12-01

ADC-LIO: A direct LiDAR-inertial odometry method based on adaptive distortion covariance

10.11591/ijra.v14i3.pp399-408
Lixiao Yang , Youbing Feng
Focusing on the localization challenges for robots in dynamic navigation environments, this study proposes a direct LiDAR-inertial odometry (LIO) system named ADC-LIO, which achieves robust pose estimation and accurate map reconstruction using adaptive distortion covariance. ADC-LIO is engineered to address uncertain motion patterns in autonomous mobile robots, effectively integrating LiDAR scan undistortion within the Kalman filtering update process by embedding an iterative smoothing process and a backpropagation strategy. The ADC-LIO architecture enhances point cloud accuracy, improving the system's overall performance and robustness. In addition, an adaptive covariance processing method is developed to resolve motion-induced sensing uncertainties, which calculates different covariances according to the error characteristics of the point cloud. This method enhances the constraints of high-quality point clouds, reduces the limitations on low-quality point clouds, and utilizes information more effectively. Experiments on the publicly available NTU-VIRAL dataset validate the effectiveness of ADC-LIO, which improves pose estimation accuracy and reduces absolute position errors compared to other state-of-the-art methods, including FAST-LIO, Faster-LIO, FR-LIO, and Point-LIO. The proposed ADC-LIO is an appealing odometry method that delivers accurate, real-time, and reliable tracking and map-building results, posing a practical solution for robotic applications in structured indoor and GPS-denied outdoor environments.
Volume: 14
Issue: 3
Page: 399-408
Publish at: 2025-12-01

Spth-FCM: decision support tool for speech therapist based on fuzzy cognitive mapping

10.11591/ijict.v14i3.pp845-859
Maziz Asma , Taouche Cherif
The development and integration of medical information systems into a unified information space is a significant focus in the field of information technologies. It is essential to develop decision support systems (DSS) to enhance the effectiveness of medical and diagnostic procedures. This article presents a novel decision support tool for speech therapists, which is based on fuzzy cognitive maps (FCM). The latter is a method of modeling complex systems using knowledge of human existence and experience. The proposed tool is composed of three phases. The first phase focuses on entering patient information into the graphical interface developed in JAVA based on the most precise observations. An FCM will be automatically constructed, describing the type of disorder and the patient’s case during the second phase. Finally, in the third phase, FCM-based scenarios were built during the execution of the inference process under FCM expert. The system is presented and demonstrated using a real cases study for eight weeks. The results show that the tool makes it possible to display, guide, assist, and confirm the medical decision of the speech therapist for an appropriate diagnosis and treatment.
Volume: 14
Issue: 3
Page: 845-859
Publish at: 2025-12-01

Classification of breast cancer using a precise deep learning model architecture

10.11591/ijict.v14i3.pp933-940
Mohammed Ghazal , Murtadha Al-Ghadhanfari , Fajer Fadhil
Breast cancer is an important topic in medical image analysis because it is a high-risk disease and the leading cause of death in women. Early detection of breast cancer improves treatment outcomes, which can be achieved by identifying it using mammography images. Computer-aided diagnostic systems detect and classify medical images of breast lesions, allowing radiologists to make accurate diagnoses. Deep learning algorithms improved the performance of these diagnoses systems. We utilized efficient deep learning approaches to propose a system that can detect breast cancer in mammograms. The proposed approach adopted relies on two main elements: improving image contrast to enhance marginal information and extracting discriminatory features sufficient to improve overall classification quality, these improvements achieved based on a new model from scratch to focus on enhancing the accuracy and reliability of breast cancer detection. The model trained on the digital database for screening mammography (DDSM) dataset and compared with different convolutional neural network (CNN) models, namely EfficientNetB1, EfficientNetB5, ResNet-50, and ResNet101. Moreover, to enhance the feature selection process, we have integrated adam optimizer in our methodology. In evaluation, the proposed method achieved 96.5% accuracy across the dataset. These results show the effectiveness of this method in identifying breast cancer through images.
Volume: 14
Issue: 3
Page: 933-940
Publish at: 2025-12-01

Antecedents and consequences of memorable experience in the airline industry: service robots versus human staff

10.11591/ijra.v14i3.pp409-417
Jinsoo Hwang , Ja Young (Jacey) Choe , Kyuhyeon Joo , Jinkyung Jenny Kim
The study aims to examine the type of service providers, such as service robots and human staff, as a potential moderator in the relationship between SERVQUAL and memorable experience in the airport industry. In order to verify 15 hypotheses, data were collected from 313 travelers who acquired information from service robots and 313 travelers who acquired information from human staff at the airport. The results of data analysis revealed that the five sub-dimensions of SERVQUAL, including tangibles, reliability, responsiveness, assurance, and empathy, enhance memorable experience. In addition, a memorable experience has a positive effect on customer satisfaction, which subsequently influences attitude and intention to use. In addition, the type of service providers moderated the links between i) responsiveness and memorable experience and ii) empathy and memorable experience.
Volume: 14
Issue: 3
Page: 409-417
Publish at: 2025-12-01

Review of NLP in EMR: abbreviation, diagnosis, and ICD classification

10.11591/ijict.v14i3.pp881-891
Nurul Anis Balqis Iqbal Basheer , Sharifalillah Nordin , Sazzli Shahlan Kasim , Azliza Mohd Ali , Nurzeatul Hamimah Abdul Hamid
This review explores state-of-the-art natural language processing (NLP) methods applied to electronic medical records (EMRs) for key tasks such as expanding medical abbreviations, automated diagnosis generation, international classification of diseases (ICD) classification, and explaining model outcomes. With the growing digitization of healthcare data, the complexity of EMR analysis presents a significant challenge for accurate and interpretable results. This paper evaluates various methodologies, highlighting their strengths, limitations, and potential for improving clinical decision-making. Special attention is given to abbreviation expansion as a crucial step for disambiguating terms in the clinical text, followed by an exploration of auto-diagnosis models and ICD code assignment techniques. Finally, interpretability methods like integrated gradients and attention-based approaches are reviewed to understand model predictions and their applicability in healthcare. This review aims to provide a comprehensive guide for researchers and practitioners interested in leveraging NLP for clinical text analysis.
Volume: 14
Issue: 3
Page: 881-891
Publish at: 2025-12-01
1 2 3
...
1937 1938
Show 19 of 1938

Discover Our Library

Embark on a journey through our expansive collection of articles and let curiosity lead your path to innovation.

Explore Now
Library 3D Ilustration