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Practice of lateral dominance: an early evaluation strategy in children from the rural area of Puno

10.11591/ijere.v14i6.32729
Nelly Olga Zela-Payi , Haydee Clady Ticona-Arapa
The purpose of this study was to investigate the practice of lateral dominance as an early evaluation strategy in children from the rural area of Puno, Peru. Early assessment of lateral dominance is crucial for understanding a child’s cognitive and motor development. This study focused on children attending a school for children with learning disabilities in the rural Initial Educational Institution Camacani within the Local Educational Management Unit of Puno, located in the southern region of the Province of Puno, under the jurisdiction of the Platería District. A total of 100 children (50 boys and 50 girls), aged 5 years, were selected for the study. The research was descriptive-quantitative in nature, aimed at evaluating the dominance of four dimensions—hands, feet, ears, and eyes—using the Harris test. The findings revealed that lateral dominance in both boys and girls was characterized by poorly affirmed laterality in 60% of the cases and crossed laterality in 40%. This suggests that at the age of 5 years, the children were still in the developmental stage of lateralization, with no clear dominance of the left or right hemisphere. Based on the results, it was concluded that lateral dominance in these children was not yet fully established. Furthermore, the study emphasized the importance of incorporating psychomotor activities during early childhood development to promote the continuous improvement of laterality, motor skills, and spatial orientation.
Volume: 14
Issue: 6
Page: 5094-5104
Publish at: 2025-12-01

Practical instruction and mathematics academic achievement in selected Ugandan secondary schools

10.11591/ijere.v14i6.30273
Frank Murangira , Alphonse Uworwabayeho , Innocent Twagilimana
The challenges met in academic achievement of learners in mathematics at secondary school level are enormous. Taking a glance at the academic achievement of learners in mathematics in Uganda, poor academic achievement becomes more and more striking. It is a puzzle to understand the origin of the causes of this poor academic achievement despite the prominence and significance bestowed upon it by the Ugandan government and society at large. It is accepted that ways mathematics is taught have high impact on learners’ achievements. Therefore, an investigation on the effect of practical instruction (PI) on learners’ academic achievement in mathematics is timely. The study was carried out using a total of 383 senior three students from eight secondary schools both private and government aided schools. It involved a quantitative approach using mathematics achievement test (MAT). The results revealed that PI affects learners’ academic achievement positively in mathematics. They showed that learners that were taught using PI improved in their academic achievement more than their counterparts in the post-test examination. Considering these findings, the study recommends proactive measures to ensure the widespread adoption of PI strategies in secondary school classrooms. This includes revising curriculum standards, providing teacher training programmers, and allocating resources to support the implementation of PI, thereby fostering learning outcomes in mathematics.
Volume: 14
Issue: 6
Page: 4966-4977
Publish at: 2025-12-01

Environmental and psychological influences on adolescents’ self-concept: teacher-student relationship as a moderator

10.11591/ijere.v14i6.34518
Ting Chen , Jamalsafri Saibon
Adolescence is a critical stage for the development of self-concept and psychological resilience. However, the impact of environmental and psychological factors on adolescents’ self-concept through psychological resilience has not been fully explored. Meanwhile, the discussion on whether the teacher-student relationship moderates the relationship between psychological resilience and self-concept is relatively rare. Based on cognitive-behavioral and social learning theories, this study collected data from 404 Chinese adolescents through a questionnaire survey. It employed partial least squares structural equation modeling (SEM) to test the hypotheses. The study found that environmental and psychological factors significantly influence adolescents’ psychological resilience, and psychological resilience mediates the relationship between environmental and psychological factors and self-concept. Moreover, the teacher-student relationship moderates psychological resilience and self-concept, particularly the positive teacher-student relationship, significantly promoting adolescents’ self-concept. This research highlights the critical influence of psychological resilience and teacher-student relationships in shaping adolescents’ self-concept. It provides empirical support for educational practice, highlighting the key role of environment, psychological factors, and good teacher-student relationships in adolescents’ mental health and self-concept development.
Volume: 14
Issue: 6
Page: 4528-4539
Publish at: 2025-12-01

Understanding the link between graduate experiences and workforce integration in physical education and sports science

10.11591/ijere.v14i6.34909
Bryan M. Nozaleda , Jasmin B. Saquing , Maricel L. Dayag-Tungpalan , Hans Freyzer B. Arao , Chita C. Ramos , Daniel T. Casauay
Graduate employability remains a critical challenge in higher education in fields with diverse career pathways like physical education and sports science (PESS). Despite efforts to enhance employability through curriculum improvements and institutional support, gaps persist in workforce integration, particularly for non-teaching graduates. This study investigates the relationship between higher education experiences and employment outcomes among PESS graduates. Using data from 274 alumni of a state university in the Philippines, the study employed binary logistic regression to assess the influence of specialization, postgraduate education, and institutional support on employability. Results indicate that graduates in the teaching track were significantly more likely to secure employment as professional educators, while non-teaching graduates faced challenges aligning their careers with their academic background. Enrollment in postgraduate education emerged as a strong predictor of employment, however, curriculum evaluation and overall university experience were not immediate predictors of employability, though long-term employment outcomes were positively associated with graduates’ perceptions of their academic training. These findings reinforce the need for higher education institutions (HEIs) to strengthen career development initiatives for non-teaching graduates and enhance work-integrated learning (WIL) opportunities.
Volume: 14
Issue: 6
Page: 4418-4431
Publish at: 2025-12-01

The bootstrap procedure for selecting the number of principal components in PCA

10.11591/ijict.v14i3.pp1136-1145
Borislava Toleva
The initial step in determining the number of principal components for both classification and regression involves evaluating how much each component contributes to the total variance in the data. Based on this analysis, a subset of components that explains the highest percentage of variance is typically selected. However, multiple valid combinations may exist, and the final choice is often made manually by the researcher. This study introduces a novel yet straightforward algorithm for the automatic selection of the number of principal components. By integrating ANOVA and bootstrapping with principal component analysis (PCA), the proposed method enables automatic component selection in classification tasks. The algorithm is evaluated using three publicly available datasets and applied with both decision tree and support vector machine (SVM) classifiers. Results indicate that this automated procedure not only eliminates researcher bias in selecting components but also improves classification accuracy. Unlike traditional methods, it selects a single optimal combination of principal components without manual intervention, offering a new and efficient approach to PCAbased model development.
Volume: 14
Issue: 3
Page: 1136-1145
Publish at: 2025-12-01

Quality of service optimization for 4G LTE upload and download throughput

10.11591/ijict.v14i3.pp1024-1033
Afrizal Yuhanef , Siska Aulia , Lefenia Indriani
Demand for mobile data services and people’s dependence on 4G LTE networks continue to increase. However, the quality of service (QoS) of this network still requires improvement, especially regarding the effect of QoS on throughput at specific frequencies. The research gap lies in the lack of indepth analysis of the impact of QoS parameters on network performance at frequencies of 2,100 MHz and 2,300 MHz. This study evaluates the effect of QoS parameters, such as delay, jitter, and packet loss, on throughput in 4G LTE networks at both frequencies. The research methodology uses an experimental approach with throughput, delay, jitter, and packet loss measurements in various network conditions. The results showed that delay (17.2174 ms to 37.0322 ms), jitter, and packet loss significantly influence throughput, ranging from 624.5 Kbps to 1,322.4 Kbps. The 2,100 MHz frequency tends to show better performance than 2,300 MHz. This study concludes that optimizing QoS parameters, especially delay and jitter, can significantly improve 4G LTE network performance. These findings provide practical contributions for mobile operators in improving network quality and customer satisfaction and open opportunities for further research on other frequencies or newer network technologies.
Volume: 14
Issue: 3
Page: 1024-1033
Publish at: 2025-12-01

Effect on saturated and unsaturated fatty acids on various vegetable oils on droplet combustion characteristic

10.11591/ijape.v14.i4.pp980-987
Dony Perdana , Muhamad Nur Rohman , Mochamad Choifin
Vegetable oils have composed of triglycerides, which one consist of 3 fatty acids combined with glycerol. Each saturated and unsaturated fatty acid has a different effect on burning characteristics. This study aimed to investigated effect of fatty acids at ceiba pentandra and jatropha oils on the flame behavior of the droplet combustion process. The combustion characteristic was observed by an ignited droplet at the junction using a thermocouple and a high-speed camera (120 fps). Results showed that a higher saturated fatty acid content resulted in long-life and steady flames. This is because more oleic and linoleic acid carbon atoms leave the droplet area and react with air. Jatropha oil produces a higher temperature of 780 °C than ceiba pentandra oil. Temperature of a vegetable oils flame is influenced by number of carbon chains, double bond, and heating value. Ceiba pentandra oil has a higher burning rate of 0.185 mm/s than jatropha oil at 0.155 mm/s. The chain content of polyunsaturated fatty acids has significant effect on rate of combustion, which is due to the weak van der Waals dispersion forces, such that heat absorption is more active and energetic. The highest flame height for ceiba pentandra oil is 55.03 mm compared to for jatropha oil it is 46.82 mm. Long-chain unsaturated double bonds and glycerol cause micro-explosions. This micro-explosion caused the shape of the flame to split and expand so that evaporation occurred faster, thus increasing the size of the flame.
Volume: 14
Issue: 4
Page: 980-987
Publish at: 2025-12-01

Eco-friendly innovation: green energy empowered by IoT

10.11591/ijape.v14.i4.pp903-911
Nikita Amoli , Jitendra Singh , Rahul Mahala , Rajesh Singh , Anita Gehlot , Mahim Raj Gupta
Energy demand is high globally, impacting daily life and promoting sustainable modernization. Goal 9 aims to build an elastic framework for economies, while Goal 15 of the Sustainable Development Goals (SDGs) emphasizes the preservation of terrestrial environment, sustainable woodland management, and biodiversity conservation. The International Energy Agency predicts a significant increase in global renewable capacity, with solar PV being two-third of this growth. Green technology is crucial to combat global warming and Industry 4.0, a digital transformation that aims to create a strong framework for sustainable modernization. The growth of the smart grid is vital, involving energy sources, control techniques, computation, generation, transmission, distribution, and more. Supercapacitors store and deliver energy at high capacity, while green energy transforms fossil fuels into eco-friendly sources using natural resources like hydro, solar, wind, thermal, and biomass. This study explores the efficient use of microprocessors in solar and wind energy, as well as the application of actuators in the green energy sector. Green energy is a sustainable solution to increasing energy needs, reducing dependence on fossil fuels. IoT technologies, including sensors, actuators, microprocessors, and microcontrollers, are used in energy generation, transmission, distribution, and composition.
Volume: 14
Issue: 4
Page: 903-911
Publish at: 2025-12-01

Improving the adaptability of an active power filter using linearization feedback input-output sliding mode

10.11591/ijape.v14.i4.pp879-892
Leminh Thien Huynh , Van-Cuu Ho , Thanh-Vu Tran
As more and more non-linear loads are used in industrial applications, power quality problems become more serious. To address this challenge, a robust nonlinear control strategy is introduced using an active power filter (APF) to enhance the power quality of the three-phase neutral voltage. The system employs a control algorithm tailored for a three-phase split-capacitor inverter, which eliminates high-order harmonics through a voltage source inverter (VSI) equipped with an LCL filter. The grid-side components of the LCL filter are incorporated into a sliding mode control framework to minimize oscillations while maintaining performance. Additionally, the d-q-0 transformation within the synchronous reference frame is applied to effectively manage the second harmonic component. In addition, the linear feedback input-output sliding mode facilitates the control system. This system can help decrease total harmonic distortion (THD) to meet IEEE-519 standards. This method demonstrates its effectiveness through simulation results, reducing THD to less than 5% and defeating previous methods despite still using simple algorithms.
Volume: 14
Issue: 4
Page: 879-892
Publish at: 2025-12-01

Smartphone use and its association with academic performance among university students in Bangladesh

10.11591/ijere.v14i6.34651
Md. Biplob Hossain , Noyon Ali , Ahmed Al Sabbir , Faysal Ahmed Imran , Md Shahjahan
Smartphone use has become integral to daily life, particularly among university students. While smartphones provide educational benefits, their overuse and addiction may negatively impact academic performance. This study investigates the prevalence of smartphone use, addiction levels, and their associations with academic performance among undergraduate students in Bangladesh. A cross-sectional survey was conducted on 615 undergraduate students from seven universities. The smartphone addiction scale-short version (SAS-SV) measured addiction levels, while academic performance was assessed via self-reported cumulative grade point average (CGPA). Descriptive statistics and logistic regression analyses were performed to explore associations. Among respondents, 29.1% were categorized as smartphone-addicted based on SAS-SV thresholds. Key predictors of higher academic performance (CGPA>3.0) included male gender (adjusted odds ratio (AOR): 3.71, 95% confidence interval (CI): 2.47–5.59, p<0.01), rural background (AOR: 1.64, 95% CI: 1.11–2.43, p=0.01), and attending private universities (AOR: 1.85, 95% CI: 1.28–2.74, p<0.01). Smartphone use for educational purposes was positively associated with better academic outcomes (AOR: 1.48, 95% CI: 0.95–2.30, p<0.01). Although smartphones are widely used for academic purposes, excessive use for stress relief or non-educational activities may harm academic outcomes. Interventions promoting responsible use and raising awareness about smartphone addiction are crucial for enhancing academic performance among university students.
Volume: 14
Issue: 6
Page: 4854-4863
Publish at: 2025-12-01

A systematic review of gamified learning motivation for English language among undergraduates

10.11591/ijere.v14i6.34101
Minjuan Chen , Wee Hoe Tan , Sze Seau Lee , Jiaming Sun
Undergraduate students’ motivation for learning English as a foreign language (EFL) is influenced by multiple factors, yet traditional teaching methods often fail to sustain engagement, leading to learning disengagement and sub-optional outcomes. The increasing integration of gamified learning has shown potential in addressing this challenge, but its effectiveness remains unclear, necessitating a systematic synthetic of existing research. This systematic review employs the preferred reporting items for systematic reviews and meta-analyses (PRISMA) framework to examine 313 studies retrieved from Education Resources Information Center (ERIC),Web of Science (WoS), and Scopus, narrowing them down to 36 relevant articles. The review categorizes findings into five key themes: i) teaching techniques and strategies; ii) learning environments and styles; iii) psychological and cultural factors; iv) technological support; and v) individual learner variables. The results highlight the positive impact of game-based learning, personalized instruction, and technology-enhanced approaches to motivation. However, psychological challenges, such as burnout and anxiety, remain significant barriers. The studyreveals research gaps, particularly regarding the long-term impact of gamified learning on EFL motivation, underscoring the need for further empirical investigation to optimize gamification strategies in EFL education.
Volume: 14
Issue: 6
Page: 5187-5196
Publish at: 2025-12-01

From family to classroom: mediating roles in promoting social and emotional learning among early adolescents

10.11591/ijere.v14i6.35535
Pantipa Thiamta , Suntonrapot Damrongpanit
This research aims to examine the influence of authoritative parenting (PAREN), cooperative learning (COOP), school environment (ENVI), positive classroom climate (CLASS), and extrovert personality (EXTRO) on social and emotional learning (SEL), as well as analyze the complexity of mediating variable roles linking these factors. The sample consisted of 684 lower secondary school students from the upper northern region of Thailand. Questionnaires were used for data collection, and analysis was conducted using partial least square structural equation modeling (PLS-SEM) technique. Research findings revealed complex structures among factors collectively explaining 67.37% of SEL variance. PAREN emerged as the most powerful driving force followed by school factors, namely COOP and CLASS, which demonstrated strong interconnection while ENVI showed only indirect influence through EXTRO. Furthermore, CLASS and EXTRO functioned as significant mediating variables between classroom factors and SEL. However, EXTRO did not play a mediating role in the relationship between parenting and SEL, reflecting that family influence remains the primary factor determining SEL development in Thai youth.
Volume: 14
Issue: 6
Page: 4916-4927
Publish at: 2025-12-01

Content validity of an innovative behavior rubric for polytechnic engineering students

10.11591/ijere.v14i6.33370
Nor Aisyah Che Derasid , Aede Hatib Musta’amal @ Jamal , Nornazira Suhairom , Hary Suswanto
In engineering education, fostering innovative behaviors is crucial for preparing students to tackle complex, real-world challenges. Developing an assessment tool or rubric that accurately measures innovative behavior is essential to provide educators with the means to systematically evaluate students’ innovative potential. This article mainly focuses on assessing the content validity of the innovative behavior assessment rubric, which is designed to measure the innovative behavior of engineering students. The rubric was designed around three core dimensions: problem recognition, idea generation, and idea implementation. Content validity was assessed using the item-level content validity index (I-CVI), scale-level content validity index (S-CVI), and modified kappa statistic. Expert evaluations resulted in a final 35-item rubric, with an overall S-CVI of 0.85, indicating high content validity. Items with I-CVI values below 0.70 were either revised or removed to ensure relevance and clarity. The study highlights the importance of expert judgment in the validation process and underscores the utility of both I-CVI and kappa in refining assessment tools. Future research will focus on construct and criterion validation, as well as practical application across diverse educational contexts.
Volume: 14
Issue: 6
Page: 4307-4319
Publish at: 2025-12-01

Crowdsourcing in Kazakhstan’s higher education in the system of dual education as predictor of universal competencies

10.11591/ijere.v14i6.32200
Mukhtar Tolegen , Botagoz Baimukhambetova , Irina Rovnyakova , Natalya Radchenko , Svetlana Sakhariyeva , Perizate Anafia
The rapid transformation of professional competencies and the emergence of new professions every 3-5 years have accentuated the quest for effective means to facilitate the process of predicting future universal competencies among university graduates. An empirical study was conducted in three stages: organizational, investigative, and analytical. The crowdsourcing process algorithm comprised information gathering, idea generation, filtering, and voting. The findings suggest the feasibility of applying crowdsourced forecasting in the educational sector, where a clear trend towards alignment with real sectors of the economy and constantly changing market business environment conditions is evident. Calculations revealed that consensus decision-making was achieved regarding competencies such as 3D modeling and computer graphics, multilingualism, emotional intelligence, project management competencies, legal literacy, neural networks and big data, intercultural communication, digital competencies, export potential of the agricultural sector, logistics outsourcing, systems thinking, virtual reality competencies, artificial intelligence proficiency, analytics, and critical thinking, as confirmed by the analysis of variance. Forecasts indicated a predominance of subject-specific competencies associated with the growing volatility of the Kazakhstani labor market. The formulated profile of future universal competency development serves as an additional guideline in the development of educational programs (EPs) in professional training directions. Modified crowdsourcing design and methodology for measuring results can be utilized or adapted for addressing other challenges facing the higher education system that require feedback.
Volume: 14
Issue: 6
Page: 4614-4627
Publish at: 2025-12-01

An artificial intelligent system for cotton leaf disease detection

10.11591/ijict.v14i3.pp950-959
Priyanka Nilesh Jadhav , Pragati Prashant Patil , Nitesh Sureja , Nandini Chaudhari , Heli Sureja
This study aims to develop a deep learning-based system for the detection and classification of diseases in cotton leaves, with the goal of aiding in early diagnosis and disease management, thereby enhancing agricultural productivity in India. The study utilizes a dataset of cotton leaf images, classified into four categories: Fusarium wilt, Curl virus, Bacterial blight, and Healthy leaves. The dataset is used to train and evaluate various CNN models such as basic CNN, VGG19, Xception, InceptionV3, and ResNet50. These models were evaluated on their accuracy in identifying the presence of diseases and classifying cotton leaf images into the respective categories. The models were trained using standard deep learning frameworks and optimized for high performance. The results indicated that ResNet50 achieved the highest accuracy of 100%, followed by InceptionV3 with 98.75%, and VGG19 and Xception both with 97.50%. The basic CNN model showed an accuracy of 96.25%. These models demonstrated strong potential for accurate multi-class classification of cotton leaf diseases. This study emphasizes the potential of deep learning in agricultural diagnostics. Future research can focus on improving model robustness, incorporating larger datasets, and deploying the system for real-time field use to assist farmers in disease management and improving cotton production.
Volume: 14
Issue: 3
Page: 950-959
Publish at: 2025-12-01
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