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28,428 Article Results

Pre-service teachers’ demographics, cultural competence, and culturally responsive teaching practices

10.11591/ijere.v14i5.33064
Edilberto Z. Andal , Albert Andry E. Panergayo
This study examines the influence of cultural competence (CC) on culturally responsive teaching (CRT) practices among pre-service teachers (PSTs) in a state university in Laguna, Philippines. Despite the emphasis on education, the impact of cultural awareness, knowledge, and skills on CRT remains underexplored. Using a cross-sectional quantitative research design, data from 633 PSTs were collected through a validated web-based survey. Multiple regression analysis showed that cultural knowledge (B=0.373, p<0.05) and cultural skills (B=0.511, p<0.05) significantly predict CRT practices, while cultural awareness (B=0.003, p>0.05) does not. Demographic factors such as age, gender, and year level do not moderate this relationship. These findings highlight the need for prioritizing cultural knowledge and skills in teacher education curricula. Institutions should integrate structured training to equip PSTs for diverse classrooms. Future research should explore the long-term effects of these competencies in an actual teaching environment and assess targeted training interventions. Strengthening CC through curriculum enhancement can better prepare educators to meet the challenges of an increasingly diverse educational landscape.
Volume: 14
Issue: 5
Page: 3526-3533
Publish at: 2025-10-01

Unveiling multi-aspects behind students’ Arabic learning experience in creative writing

10.11591/ijere.v14i5.31974
Zakiyah Arifa , Al Lastu Nurul Fatim , Risna Rianti Sari , Ahmad Hidayatullah Zarkasyi , Dedi Mulyanto
The dynamic of team-based project (TBP) in learning stimulates multi-aspects through learning activities and experiences. Due to its complexity, the learning model impacts some skills and aspects. This research aims to identify students’ experiences of learning Arabic creative writing in TBP: language, psychology, collaboration, and creativity, and to explain the contribution of those aspects to the learning process. To understand these experiences comprehensively, this research used mixed-method model: concurrent triangulation strategy using descriptive quantitative survey and qualitative case study. Closed and opened questionnaire instruments, interviews, and focused group discussion (FGD) with participants at two Islamic Universities were used as data collection methods to confirm them mutually. Then, data was analyzed using descriptive and reflective analysis. The results found that TBP positively impacted four aspects: vocabulary, grammatical structure, and writing skills improved as language aspects. The psychological aspect can increase criticism, motivation, and self-confidence. The collaborative aspect enhanced skills and talents by providing input, criticism, and suggestions. The creativity aspect is felt by students when generating ideas and imagination during the learning process and completing projects. Through learning Arabic creative writing using TBP, severalmulti-aspects can be developed. The psychological and collaborative aspects trigger and build language and creativity skills, and this contribution gives meaningful student experiences. These findings indicate that some students’ skills can be developed through student-centered learning by integrating TBP and Arabic writing learning, which has implications for improving 21st-century skills. Also, it can be developed more in Arabic language learning as a second/foreign language in Indonesia or other countries.
Volume: 14
Issue: 5
Page: 4195-4209
Publish at: 2025-10-01

Teachers’ perceptions towards principals’ instructional supervisory role in selected secondary schools

10.11591/ijere.v14i5.34063
Bessy Kageni Kinyua , Elizabeth Atieno Obura , Johnson Mulongo Masinde
Effective instructional supervision plays a crucial role in enhancing teaching quality and student learning. However, teachers’ perceptions towards supervision vary, some view it as supportive while others see it as fault-finding. This study examines teachers’ perceptions towards principals’ instructional supervisory practices to identify areas of improvement. The Administrative theory of supervision and a concurrent triangulation mixed approach guided the study. Purposive and simple random sampling were utilized to sample 127 teachers and 10 principals. A survey and an interview guide were employed to gather data which was analyzed using descriptive and inferential statistics. An independent sample t-test and one-way analysis of variance (ANOVA) were utilized to test the mean differences in teachers’ perceptions. Findings indicate that while most teachers recognize supervision as beneficial for professional development, a significant number perceive supervision as authoritarian. The results unveiled that teachers’ gender, age and education qualification did not significantly influence their perceptions [t(98)=1.468, p>0.05, F(4, 95)=0.556, and F(4, 95)=0.174, p>0.05]. The study concludes that fostering a positive supervisory environment can enhance teachers’ confidence, improve instructional strategies, and ultimately lead to better student outcomes.
Volume: 14
Issue: 5
Page: 3891-3903
Publish at: 2025-10-01

Teaching in the digital frontier: what drives metaverse adoption in education?

10.11591/ijere.v14i5.34836
Cadelina Cassandra , Mohamad Noorman Masrek , Fadhilah Aman
The rapid evolution of digital technologies has caused dramatic changes in various areas, including education. Metaverse has become a very popular topic recently, many schools and university announce the development of metaverse, but until now there is no clear implementation of the idea and some schools cancelled to continue the implementation. One of the reasons behind it because of the lack of preparedness, reluctant from teachers, and there is no initial investigation about how the teachers will accept this technology. Several factors may influence the intention of the teachers. The purpose of this study is to analyze the factors that affect high school teachers’ intentions to use metaverse technology. By doing so, the institution can prepare for the real implementation. This study employs quantitative methods and survey techniques by developing a well-structured questionnaire from the theoretical framework. A total of 334 responses were collected and analyzed using SmartPLS software. The findings reveal that 14 hypotheses out of 18 hypotheses were significant and four others were not significant. Social influence (SI), performance expectancy (PE), effort expectancy (EE), and facilitating condition (FC) positively influence teachers’ behavioral intention (BI) to use metaverse applications. On the flip side, personal innovativeness (PI) does not significantly impact performance and EE. Trialability (TR) and corporeity (CR) also do not influence EE. However, hedonic motivation (HM), compatibility (CO), TR, interactivity (IN), and persistence are significant factors for performance and EE.
Volume: 14
Issue: 5
Page: 3601-3611
Publish at: 2025-10-01

Analysis of obstacles in teaching and learning nuclear physics: towards a digital approach in secondary education

10.11591/ijere.v14i5.30557
Aziz Taoussi , Ahmida Chikhaoui , Khalid El Khattabi , Hassan Yakkou
The study explores the specific obstacles encountered in the teaching and learning of nuclear physics within qualifying secondary schools in Morocco, particularly in the Fez-Meknes delegation. We identified a lack of specific research on this topic, despite a growing interest in improving science teaching. Using questionnaires administered to 100 teachers and 200 students, we found that the absence of laboratory experiments due to the dangers associated with nuclear physics is a major obstacle. Difficulties in understanding concepts such as radioactive decay, nuclear fusion, and fission were also noted. To overcome these challenges, we propose the development of digital teaching resources adapted to the Moroccan curriculum, including simulations and interactive tutorials. These resources are viewed positively by teachers and students alike, as they facilitate understanding of concepts, increase engagement and enable self-paced learning, promoting autonomy in learning and the development of creativity in students. For successful integration, it is essential to provide adequate training and ongoing support for teachers. The results offer concrete avenues for improving the quality of teaching in physical sciences and learning in a digital environment motivates students in Morocco.
Volume: 14
Issue: 5
Page: 3846-3858
Publish at: 2025-10-01

Identification of factors that influence student satisfaction from the analysis of voice messaging from WhatsApp: a case study

10.11591/ijere.v14i5.27328
Omar Chamorro-Atalaya , Giorgio Aquije-Cardenas , Raymundo Carranza-Noriega , Lilly Moreno-Chinchay , Yurfa Medina-Bedón , Rufino Alejos-Ipanaque , Abel Tasayco-Jala , Susan Gonzales-Saldaña
In these times when there is talk of a return to a new normality in education after what happened due to the pandemic, it is necessary to permanently evaluate the perception of student satisfaction, contributing to the results obtained through traditional methods such as the survey, with methods in which open opinions can be analyzed as in the case of voice analysis. In this sense, this article describes a case study, which aims to identify the factors that influence student satisfaction with respect to teaching performance, based on the analysis of WhatsApp voice messaging. The study has a qualitative approach, exploratory level and non-experimental design. It was possible to identify various factors grouped into five categories: i) planning; ii) didactic strategies; iii) communication; iv) administration of the class session; and v) professional and personal characteristics of the teacher. Therefore, it is concluded that it is possible to close the gaps between the factors that are sensitive and relevant for the university, when a questionnaire with delimited questions is applied to observe only some factors of student satisfaction, with respect to those sensitive factors and relevant to students, by analyzing their comments from the use of voice messaging from mobile applications.
Volume: 14
Issue: 5
Page: 3744-3755
Publish at: 2025-10-01

Design and analysis of reinforcement learning models for automated penetration testing

10.11591/ijai.v14.i5.pp4061-4073
Suresh Jaganathan , Mrithula Kesavan Latha , Krithika Dharanikota
Our paper proposes a framework to automate penetration testing by utilizing reinforcement learning (RL) capabilities. The framework aims to identify and prioritize vulnerable paths within a network by dynamically learning and adapting strategies for vulnerability assessment by acquiring the network data obtained from a comprehensive network scanner. The study evaluates three RL algorithms: deep Q-network (DQN), deep deterministic policy gradient (DDPG), and asynchronous episodic deep deterministic policy gradient (AE-DDPG) in order to compare their effectiveness for this task. DQN uses a learned model of the environment to make decisions and is hence called model-based RL, while DDPG and AE-DDPG learn directly from interactions with the network environment and are called model-free RL. By dynamically adapting its strategies, the framework can identify and focus on the most critical vulnerabilities within the network infrastructure. Our work is to check how well the RL technique picked security vulnerabilities. The identified vulnerable paths are tested using Metasploit, which also confirmed the accuracy of the RL approach's results. The tabulated findings show that RL promises to automate penetration testing tasks.
Volume: 14
Issue: 5
Page: 4061-4073
Publish at: 2025-10-01

Detection of chronic kidney disease based on ensemble approach with optimal feature selection using machine learning

10.11591/ijai.v14.i5.pp4017-4031
Deepika Amol Ajalkar , Jyoti Yogesh Deshmukh , Mayura Vishal Shelke , Shalini Vaibhav Wankhade , Shwetal Kishor Patil
Chronic kidney disease (CKD) poses a significant health risk globally, necessitating early and accurate detection to ensure timely intervention and effective treatment. This study presents an advanced ensemble machine learning (ML) approach combined with optimal feature selection to enhance the detection of CKD. Using five baseline ML classifiers like gradient boosting (GB), random forest (RF), K-nearest neighbors (KNN), support vector machine (SVM), and decision tree (DT), and utilizing grid search for hyperparameter tuning, the proposed ensemble model capitalizes on the strengths of each algorithm. Our approach was tested on a public benchmark CKD dataset from Kaggle. The experimental results demonstrate that the ensemble model consistently outperforms individual classifiers and existing methods, achieving 97.5% accuracy, precision, recall, and an F1-score of 97.4%. This superior performance underscores the ensemble model's potential as a reliable early CKD detection tool. Integrating ML into CKD diagnostics enhances accuracy. It facilitates the development of automated, scalable diagnostic tools, aiding healthcare professionals in making informed decisions and ultimately improving patient outcomes.
Volume: 14
Issue: 5
Page: 4017-4031
Publish at: 2025-10-01

Development of a counselling-based self-wellbeing model for informal caregivers of childhood cancer patients in Malaysia

10.11591/ijere.v14i5.32468
Nurul Hasyimah Mat Rani , Nurul ‘Ain Mohd Daud , Hapsah Md Yusof , Syaza Hazwani Zaini , Pau Kee , Mazuki Mohd Yasim , Wan Faizatul Azirah Ismayatim , Nur Shuhana Mohd Sansuddin
Cancer is a chronic disease that causes patients and their caregivers to face various challenges throughout treatment and care. This study aimed to develop a counselling-based self-wellbeing model for informal caregivers of childhood cancer patients in Malaysia. This study employed the design and development research (DDR). The first phase involved needs analysis using a systematic literature review and semi-structured interviews of nine caregivers of childhood cancer. The second phase involved two methods: nominal group technique (NGT) and interpretive structural modeling (ISM). The third phase involved evaluating the usability of the model through the Fuzzy Delphi method (FDM) with the agreement of seven experts. This study successfully developed a counselling-based self-wellbeing model for informal caregivers of childhood cancer patients in Malaysia. This model has 12 components consisting of: i) financial; ii) career; iii) knowledge related to management and care of child cancer patients; iv) emotional management and care; v) spiritual; vi) cognitive and rationalization; vii) social relationships; viii) roles of counsellors in helping parents; ix) spouse and family relationships; x) physical; xi) communication; and xii) facilities. This model is proposed to be used by counsellors, especially who serve in health institutions to help parents who have children with cancer.
Volume: 14
Issue: 5
Page: 4222-4230
Publish at: 2025-10-01

The educational accomplishments scale: development and validation in the context of education institutions

10.11591/ijere.v14i5.34224
Anil DCosta , Joseph Chacko Chennattuserry , Kennedy Andrew Thomas
Educational institutions play a significant role in fostering academic growth and personal development. However, there is a lack of standardized tools to assess the impact of educational accomplishments (EA), particularly integrating dimensions such as quality, value-based, integrated, and culture-enhanced education. This paper aims to create and validate a measurement tool that assesses how EA impacts students and institutions to foster academic growth, personal development, and institutional effectiveness, contributing to the overall quality of education. The data was collected from 120 participants, including religious heads, directors, principals, and coordinators of ten schools run by a specific religious congregation. The study implemented a three-stage systematic procedure in the development of the scale. Stage one consisted of item generation, literature review, and expert judgment. The second stage validated the scale and was followed by an item analysis, principal component with varimax rotation (exploratory factor analysis) using Kaiser normalization on IBM SPSS 26. The third step resulted in the final reliability and validity of the scale. A final 19-item educational accomplishments scale (EAS) is psychometrically reliable and of potential use to policymakers globally, comparing student and teacher perceptions, especially with religious congregational affiliations. This scale can particularly be used by each institution to evaluate the EA and can also be used by other researchers for further research.
Volume: 14
Issue: 5
Page: 3882-3890
Publish at: 2025-10-01

Leadership and management in early childhood: navigating contradictions and pedagogical practices to foster inclusivity

10.11591/ijere.v14i5.33061
Manoharan Nalliah , Shorouk Aboudahr , Lim Wei Huan , Esayas Teshome Taddese
Early years’ education is an important foundation for a child’s life-long learning, and leaders and managers in early childhood work settings have an important role in creating a nurturing environment that supports and enables children to learn regardless of their needs. This study investigates the challenges and contradictions leaders and managers face in early childhood education (ECE) settings. It examines how pedagogical praxis can be leveraged to foster inclusivity focusing on the tension between the intrinsic value of play and the pressure of child performativity meeting performance benchmarks. This qualitative study offers a constructive discussion on leadership practices in ECE and inclusion in Malaysia. The thematic analysis of nine interviews analyzed by N-VIVO software and showed the important considerations for enhancing leadership and management approaches, creating more inclusive spaces, and supporting the holistic development of early childhood curricula. The result offers a rich description of how leading practices are increasingly influenced by dominant trends in educational policies and society, including neoliberal agendas and narrowly conceived accountability systems that focus on measurable outcomes. It underlines the centrality of supporting the ongoing professional development of educators.
Volume: 14
Issue: 5
Page: 3765-3773
Publish at: 2025-10-01

Requirements for managing differentiated classrooms among Jordanian science teachers

10.11591/ijere.v14i5.30268
Mohammed S. Al-Rsa’i , Zobaida Abushwemeh , Eman Krieshan
Differentiated instruction (DI) is characterized by the fact that it achieves most educational goals and it is role in deepening the values of justice, equity, and a democratic climate in the learning environment. However, this approach requires highly skilled and qualified teachers, especially science teachers, due to the complexity of science learning tasks and environments. The current study aimed to examine the degree to which science teachers in Jordan possess the requirements of differentiated classroom management, and the extent to which they are affected by variables (gender and professional experience). The study sample consisted of 379 science teachers. A differentiated classroom management scale (DCMS) was prepared to achieve the study’s objective, consisting of 38 items with three domains: instruction management, classroom environment management, and managing feelings and emotions in the differentiated classroom. The results of the study showed that the degree to which science teachers in Jordan possess the requirements for differentiated classroom management is moderate. At the same time, there are differences in this degree in favor of the female parameters. However, professional experience did not affect this degree of tenure. The study recommended holding training programs for science teachers in differentiated classroom management and reviewing teacher training programs in Jordan.
Volume: 14
Issue: 5
Page: 4164-4172
Publish at: 2025-10-01

Let’s be a chef! The antecedents of chef’s key competencies for vocational school students

10.11591/ijere.v14i5.26708
Badraningsih Lastariwati , Tuatul Mahfud
Chefs are considered a factor in the success of a culinary tourism business. Therefore, mastering the chef’s key competencies (CKC) through vocational high schools is very important. Many studies have examined the competence of chefs. Still, the mechanism for getting key competency chefs involving industry commitment (IC), social support (SS), vocational teaching quality (TQ), and occupational self-efficacy (OSE) of culinary student chefs has not been discussed clearly. This study investigates the antecedents of the mastery of key chef competencies for vocational school students. This study involved 392 culinary students at seven vocational schools in Yogyakarta, Indonesia. Data was collected by proportional random sampling through a questionnaire. Amos 18 software is used for structural equation modeling (SEM) analysis. The study’s results revealed that the mastery of the chef’s critical competencies for students was directly and significantly influenced by IC, quality of vocational teaching, and OSE of chefs. In addition, chef OSE is a mediator on the influence of IC, SS, and quality of vocational teaching on mastering the chef’s critical competencies for culinary students. This study’s findings discuss in depth some of the implications for vocational education practitioners that are proposed for further improvement.
Volume: 14
Issue: 5
Page: 4006-4018
Publish at: 2025-10-01

Tomographic image reconstruction enhancement through median filtering and K-means clustering

10.11591/ijece.v15i5.pp4395-4408
Nguyen Quang Huy , Nguyen Truong Thang
Ultrasound tomography is a powerful and widely utilized imaging technique in the field of medical diagnostics. Its non-invasive nature and high sensitivity in detecting small objects make it an invaluable tool for healthcare professionals. However, a significant challenge associated with ultrasound tomography is that the reconstructed images often contain noise. This noise can severely compromise the accuracy and interpretability of the diagnostic information derived from these images. In this paper, we propose and rigorously evaluate the application of a median filter to address and mitigate noise artifacts in the reconstructed images obtained through the distorted born iterative method (DBIM). The primary aim is to enhance the quality of these images and thereby improve diagnostic reliability. The effectiveness of our proposed noise reduction approach is quantitatively assessed using the normalized error evaluation metric, which provides a precise measure of improvement in image quality. Furthermore, to enhance the interpretability and utility of the reconstructed images, we incorporate a basic machine learning technique known as K-means clustering. This method is employed to automatically segment the reconstructed images into distinct regions that represent objects, background, and noise. Hence, it facilitates a clearer delineation of different components within the images. Our results demonstrate that K-means clustering, when applied to images processed with the proposed median filter method, effectively delineates these regions with a significant reduction of noise. This combination not only enhances image clarity but also ensures that critical diagnostic details are preserved and more easily interpreted by medical professionals. The substantial reduction in noise achieved through our approach underscores its potential for improving the accuracy and reliability of ultrasound tomography in medical diagnostics.
Volume: 15
Issue: 5
Page: 4395-4408
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
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