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25,002 Article Results

Mobile application for distributing information to students at the Sciences and Humanities University

10.11591/ijeecs.v37.i2.pp1085-1092
Patricia Condori-Obregon , Carlos Huallpa-Juarez , Carlos Palomino-Vidal
Currently, educational institutions around the world have implemented many standards and rules to ensure teaching quality. Many of these standards and rules are related to the use of technologies that provide students with services and facilities to learn. However, in Peru, a Latin American country, these standards and rules have been recently implemented, and as a result, information systems are required to guarantee teaching quality. This research exposes the implementation of a mobile application for distributing and managing information for students and teachers who require data about courses, grades, absences, and receive news about important university announcements. This work applied both research methods and Scrum methodologies together to demonstrate how the education process benefits from the use of technologies. As a result of these implementations, processes like finding academic information improved by an average of 50%. These results support that the implementation of mobile application technologies in educational environments is beneficial for guaranteeing process improvement and teaching quality.
Volume: 37
Issue: 2
Page: 1085-1092
Publish at: 2025-02-01

The social impact of artificial intelligence chatbots on college students

10.11591/ijere.v14i1.29469
Azman Hakimi , Reeda Li Meng Yue , Mariam Sufiah Muhsin , Maisarah Abu Bakar , Crendy Tan Yen Teng , Kususanto Ditto Prihadi
This study aims to investigate the impact of the freely accessible artificial intelligence chatbots (AICB) that might disrupt the teaching and learning pattern in higher education. While some education stakeholders developed strong opposition towards the AICB usage, condemning it as academic dishonesty, there are others believe the AICB might even improve the students’ learning. A total of 160 urban college students were purposively selected and requested to respond to the scales of ChatGPT acceptance and trust, academic self-efficacy, and university mattering to test the hypothesis that the acceptance and trust towards AICB should improve academic self-efficacy and general mattering among the students. The results indicated that academic self-efficacy partially mediates the contribution of AICB on the societal mattering. In other words, the findings suggest that students who trust and accept AICB usage would likely to believe that they can perform academically better and therefore they feel they are more meaningful to the society. Limitations and suggestions for future research are discussed.
Volume: 14
Issue: 1
Page: 10-16
Publish at: 2025-02-01

Educational management in a digital age: boss phubbing and teacher motivation

10.11591/ijere.v14i1.29046
Mukadder Erdem , Esra Kaya
The study aims to assess the level of phubbing behavior an antisocial common mobile phone using behavior of school principals and how it affects the motivation of the teachers working at Anatolian High Schools and Vocational High Schools. This relational screening modelled study was conducted in these schools in the 2nd term in 2022 to 2023 school year. For data collection purposes, Boss Phubbing Scale and Multidimensional Work Motivation Scale were used and 268 answers were collected from the whole population. The data was analyzed through descriptive statistics, exploratory factor analysis (EFA), Cronbach’s alpha reliability analysis, one-way analysis of variance (ANOVA), unpaired t test, Pearson correlation analysis and regression analysis. The data derived from these analyses indicates that while school principals phub teachers at a low level and their boss phubbing scores differentiate in accordance with the work experience of teachers; teachers’ motivation is high and there is a significant and positive relationship between boss phubbing of school principals and two factors of Multidimensional Work Motivation Scale, which were extrinsic motivation and amotivation. It may be suggested that school principals should alter their boss phubbing behavior or modify it to make the best of it.
Volume: 14
Issue: 1
Page: 50-60
Publish at: 2025-02-01

Advancing chronic pain relief cloud-based remote management with machine learning in healthcare

10.11591/ijeecs.v37.i2.pp1042-1052
Nagarajan Mohankumar , Sandeep Reddy Narani , Soundararajan Asha , Selvam Arivazhagan , Subramanian Rajanarayanan , Kuppan Padmanaban , Subbiah Murugan
Healthcare providers face a significant challenge in the treatment of chronic pain, requiring creative responses to enhance patient outcomes and streamline healthcare delivery. It suggests using cloud-based remote management with machine learning (ML) to alleviate chronic pain. Wearable device data, electronic health record (EHR) data, and patient-reported outcomes are all inputs into the suggested system’s data analysis pipeline, which combines support vector machines (SVM) with recurrent neural networks (RNN). SVM’s powerful classification skills make it possible to classify patients’ risks and predict how they will react to therapy. RNNs are very good at processing sequential data, which means they may identify trends in patient symptoms and drug adherence over time. By integrating these algorithms, healthcare professionals may create individualized treatment programs that consider each patient’s preferences and specific requirements. Early intervention and proactive treatment of pain symptoms are made possible by the system’s ability to monitor patients in real-time remotely. The system is further improved by using predictive analytics to identify patients who could benefit from extra support services and to forecast when they will have acute pain episodes. The proposed approach can change the game regarding managing chronic pain. It provides data-driven, individualized treatment that improves patient outcomes while cutting healthcare expenses.
Volume: 37
Issue: 2
Page: 1042-1052
Publish at: 2025-02-01

Mapping research on peace education: the bibliometric analysis for research agenda in the future

10.11591/ijere.v14i1.29097
Wahyu Nanda Eka Saputra , Prima Suci Rohmadheny , Nur Hidayah , Trikinasih Handayani , Agus Supriyanto , Agungbudiprabowo Agungbudiprabowo
This study aims to analyze the trend of scientific publications with the theme of peace education. This study uses bibliometric analysis to describe trends in peace education research and reveal its bibliometric profile. The data was taken from the Scopus database covering 1961 to 2023 with the keywords “peace education” and “violence.” The results of the analysis show that there is a positive trend toward an increase in publications with the theme of peace education. The most prominent country that contributes to peace educationthemed publications is the United States. The University of Toronto and the University of Kwazulu-Natal are the most famous universities that publish research results on peace education. The Journal of Peace Education is the favorite journal for publication on the theme of peace education. Vaughn Mitchell John and Johan Galtung are prominent names who have influenced publications on peace education. Potential themes regarding peace education are discussed in this paper. This research contributes to analyzing structure, trends, collaboration opportunities, and research roadmaps as a basis for future research.
Volume: 14
Issue: 1
Page: 61-73
Publish at: 2025-02-01

Innovative power sharing and secondary controls for meshed microgrids

10.11591/ijece.v15i1.pp99-113
Youssef Amine Ait Ben Hassi , Youssef Hennane , Abdelmajid Berdai
In alternating current (AC) microgrids, the prevalent approach for controlling the power distribution between generators and loads is droop control. This decentralized technique ensures accurate power sharing; however, its utility is restricted by significant drawbacks. Notably, in scenarios involving dissimilar power sources, mismatched impedance lines, or meshed microgrids, conventional droop control fails to ensure effective reactive power sharing among inverters, often leading to notable circulating currents. Hence, the primary objective of this paper is twofold: firstly, to examine limitations inherent to conventional droop control; secondly, to introduce a robust power-sharing methodology for AC microgrids. This novel approach is specifically designed to achieve consistent sharing of active and reactive power across meshed topology microgrids. The technique considers the presence of distributed power loads and the dynamic nature of the topology. Despite the attainment of satisfactory active and reactive power sharing, deviations in voltage and frequency occasionally manifest. To address this issue, a supplementary control mechanism is proposed as a third phase. This secondary control method focuses on reinstating the microgrid's voltage and frequency to rated values, all while upholding the precision of power sharing. The efficacy of this multi-stage methodology is rigorously validated through simulations using MATLAB/Simulink and practical experimentations.
Volume: 15
Issue: 1
Page: 99-113
Publish at: 2025-02-01

Efficient deep learning approach for enhancing plant leaf disease classification

10.11591/ijeecs.v37.i2.pp1112-1120
Meroua Belmir , Wafa Difallah , Abdelkader Ghazli
The widespread occurrence of plant diseases is a major factor in the reduction of agricultural output, affecting both crop quality and quantity. These diseases typically begin on the leaves, influenced by alterations in plant structure and growing techniques, and can eventually spread over the entire plant. This results in a notable decrease in crop variety and yield. Successfully managing these diseases depends on accurately classifying and detecting leaf infections early, which is essential for controlling their spread and ensuring healthy plant growth. To address these challenges, this paper introduces an efficient approach for detecting plant leaf diseases. A concatenation of pre-trained convolutional neural networks (CNN) for enhanced plant leaf disease using transfer learning technique is implemented, with a specific focus on accurate early detection, utilizing the comprehensive new plant diseases dataset. The combined residual network-50 (ResNet-50) with densely connected convolutional network-121 (DenseNet-121) architecture aims to provide an efficient and reliable solution to these critical agricultural concerns. Various evaluation metrics were utilized to evaluate the robustness of the proposed hybrid model. The proposed ResNet-50 with the DenseNet-121 hybrid model achieved a rate of accuracy of 99.66%.
Volume: 37
Issue: 2
Page: 1112-1120
Publish at: 2025-02-01

Literacy extension programs of higher education institution in the Philippines: insights from stakeholders

10.11591/ijere.v14i1.29736
Matronillo Del Mundo Martin , Lhea dela Cruz Ildefonso
This descriptive research investigates the impact of extension programs from a college of teacher education on public elementary school teachers. Three programs, literacy (n=75), Catch Me and Teach Me strategy literacy program (n=64), and campus journalism (n=48), were evaluated. Participants reported profound positive impact from these programs, considering them effective or very effective. The literacy program significantly improved reading and writing skills, fostered a love for learning, and benefitted the community. However, challenges like outdated materials and overemphasis on rote memorization need addressing. The Catch Me and Teach Me strategy literacy program excelled in practical teaching strategies and hands-on learning but required additional time and support, emphasizing the need for a more personalized approach. The campus journalism program was lauded for its informativeness but faced venue, food quality, time management issues, and a desire for more diverse topics. These findings stress the importance of customized professional development, long-term impact assessment, cultural sensitivity, and community involvement. Effective, engaging training methods, feedback, and efficient resource allocation are vital for program improvement. The research aims to enhance extension services’ quality for the community's benefit, providing valuable guidance to improve these programs and cater to participants' diverse needs.
Volume: 14
Issue: 1
Page: 544-556
Publish at: 2025-02-01

Optimal cleaning robot on solar panels with time-sequence input based on internet of things

10.11591/ijece.v15i1.pp280-291
Dwi Nur Fitriyanah , Rivaldi Dwi Pramana Saputra , Imam Abadi , Ali Musyafa
Solar panels are the main component of solar power generation systems, and they function by converting solar energy into electrical energy. Indonesia has great potential for solar energy. Solar panels will work optimally at temperatures of 25 °C to 28 °C. The greater the temperature of the solar panel, the more power generated by the panel. The influence of solar radiation intensity can be caused by dust and animal droppings attached to the surface of the solar panel module. If the surface of a solar panel is covered with dust or dirt, which can block the entry of solar radiation, the resulting power output is not optimal. The aim of this research is to design and implement an automatic cleaning system for solar power plants. The system used is using ESP32 based on the Blynk application and adding internet of things (IoT) devices with a cleaning method using pumped water spraying, then assisted with wipers which have silicon rubber material to clean dust and dirt. Based on the cleaning optimization simulation calculations, we found that the optimal or efficient cleaning condition was once a month, with an efficiency of 75.17%.
Volume: 15
Issue: 1
Page: 280-291
Publish at: 2025-02-01

Education and smart technologies: towards a new pedagogical paradigm

10.11591/ijere.v14i1.30470
Amine Dehbi , Abdellah Bakhouyi , Al Mahdi Khaddar , Mohamed Talea
Smart education, a new field of technology related to education, has emerged as a unique response to current educational challenges. This is becoming increasingly important for academic progress and aligns with the transformative impact of technology. This study addresses the transformative impact of smart technologies on education, focusing on the integration of the internet of things, big data, and artificial intelligence. Through a bibliometric and content analysis based on Scopus and Web of Science databases, we identify the most active researchers, leading universities, and the countries that contribute most significantly to the field of smart education. The findings reveal a significant increase in related publications, highlighting the growing importance of these technologies in enhancing teaching and learning experiences. The study shows the advantages and challenges of adopting such technologies, providing insights into their practical applications and the future direction of educational innovations. Integrating smart technologies in education is crucial for improving quality of life and academic outcomes, necessitating further research and development to fully realize their potential. This research contributes to the understanding of technological impacts on education and supports the development of strategies for their effective implementation.
Volume: 14
Issue: 1
Page: 297-309
Publish at: 2025-02-01

Development and validation of doctoral student social support perception scale

10.11591/ijere.v14i1.30920
Xiaohan Yang , Kee Jiar Yeo , Shih-Hui Lee , Boon Yew Wong , Lina Handayani
The perception of social support is crucial for doctoral students' academic careers, yet there is a notable absence of scales specifically designed to measure the social support that doctoral students receive. Consequently, there is a clear need for an effective tool to assess the level and nature of support perceived by these students. The Doctoral Students Social Support Perception Scale (DSSPS) is a multidimensional instrument developed to evaluate social support received by doctoral students from supervisors, family, and peers/friends. This scale operates in two phases: the first phase uses exploratory factor analysis to identify three potential dimensions of perceived social support: resource provision, emotional inspiration, and appropriate attention. The second phase employs confirmatory factor analysis to demonstrate the scale's robust overall fit. The results also indicate high internal consistency as well as convergent and discriminant validity. These findings suggest that the DSSPS is both an effective and reliable measure to assess the extent and nature of social support perceived by doctoral students.
Volume: 14
Issue: 1
Page: 1-9
Publish at: 2025-02-01

Refining thyroid function evaluation: a comparative study of preprocessing methods in diffuse reflectance spectroscopy

10.11591/ijece.v15i1.pp303-310
Wincent Anto Win Shalini , Thulasi Rajalakshmi , Selvanayagam Vasanthadev Suryakala
Thyroid dysfunction, comprising conditions such as hyperthyroidism and hypothyroidism, represents a substantial global health challenge, necessitating timely and precise diagnosis for effective therapeutic intervention and patient welfare. Conventional diagnostic modalities often involve invasive procedures, that could cause discomfort and inconvenience for individuals. The non-invasive techniques like diffuse reflectance spectroscopy (DRS) can offer a promising alternative. This study underscores the critical role of preprocessing methods in enhancing the accuracy of thyroid hormone functionality through a non-invasive approach. In the proposed study the spectral data acquired from the DRS setup are subjected to different preprocessing techniques to improve the efficacy of the prediction model. Thirty individuals with thyroid dysfunction were included in the study, and preprocessing methods such as baseline correction, multiplicative scatter correction (MSC), and standard normal variate (SNV), were systematically evaluated. The study highlights that SNV preprocessing outperformed other methods with a root mean square error (RMSE) of 0.005 and an R² of 0.99. In contrast, MSC resulted in an RMSE of 0.87 and an R² of 0.86, while baseline correction showed a RMSE of 0.84 and an unusual R² of 1.09, indicating potential issues. SNV proved to be the most effective technique.
Volume: 15
Issue: 1
Page: 303-310
Publish at: 2025-02-01

Determination of pedagogical principles for building functional science literacy of school children

10.11591/ijere.v14i1.30225
Maimatayeva Assiya Dwysengalievna , Kazakhbayeva Danakul , Karbayeva Sholpan , Zhumagulova Kalampyr , Bitibayeva Zhazira , Edi Setiawan
In this study, it was aimed to determine the pedagogical principles for building functional science literacy of school children in line with the Program for International Student Assessment (PISA) by examining the performing countries in PISA. The statistical results of the PISA results reports of China, Singapore, Hong Kong and Estonia were compared with the results of Kazakhstan. It was concluded that students in the top-ranked countries actively participate in scientific activities, enjoy practicing scientific activities, exhibit high-level cognitive skills, test and monitor the results of scientific research, and compete in national and international activities. The economic status of the family, learning environment, discipline, school equipment, and the number of teachers in the school are among the factors affecting children’s science literacy. Teachers’ continuous participation in in-service trainings, keeping their motivation at a high level, choosing different teaching methods, encouraging students to conduct research and activating high-level cognitive skills were considered among the most important reasons for good results in science PISA research. It is recommended that countries that want to rank higher in an international platform such as PISA should implement student-centered activities in their educational reforms and create educational environments where students can test their high-level skills.
Volume: 14
Issue: 1
Page: 648-658
Publish at: 2025-02-01

Psychometric properties of emotional intelligent scale: the application for university students in Indonesia

10.11591/ijere.v14i1.28599
Amin Akbar , Zulakbal Abd Karim , Jaffry Zakaria , Suryanef Suryanef , Muh Khairul Wajedi Imami , Utami Syahdiah , Hilwa Alfiani Fitri
The current research aims to assess the psychometric properties of the emotional intelligence scale among university students in Indonesia. This research used a survey design. The current research participants were 288 university students in Palembang, West Nusa Tenggara, Kupang, Yogyakarta, and Jakarta, Indonesia. Two procedures were used to analyze the data: exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The results showed that EFA with comprehensive techniques that compromise parallel analysis yielded a 5-factor solution: empathy with five items, handling relationships with five items, motivation for oneself with six items, self-awareness with seven items, and managing emotion with eight items. The five factors solution was confirmed through CFA with the value: Chi square=2.631, Tucker-Lewis’s index (TLI)=.804, comparative fit index (CFI)=.823, root mean square error of approximation (RMSEA)=.075, and standardized root mean residual (SRMR)=.743. The scale validation and reliability were tested through average variance extracted (AVE) with the value ranged from 0.271 to 0.594, construct reliability (CR) with the value ranged from 0.706 to 0.879, and Cronbach’s alpha with the value ranged from 0.706 to 0.879. Therefore, based on psychometric analysis, the scale is valid and reliable to be used in measuring emotional intelligence among university students in Indonesia.
Volume: 14
Issue: 1
Page: 157-170
Publish at: 2025-02-01

Entrepreneurship education in vocational schools: an Indonesian model

10.11591/ijere.v14i1.32317
Widodo Widodo , Aliyah Rasyid Baswedan , Pujiati Suyata , Wahyu Nanda Eka Saputra
Vocational education is crucial in bridging the gap between educational outcomes and labor market demands, significantly impacting employment rates and career prospects. The purpose of the study was to identify the acceptability of the entrepreneurship education model in Indonesian vocational schools. This paper explores the importance of vocational education in equipping individuals with job-ready skills, addressing challenges like long-term unemployment, and literacy skill disparities. It emphasizes the integration of entrepreneurship education to foster entrepreneurial intentions, competencies, and behaviors, crucial for sustainable economic growth, particularly in Indonesia. Utilizing a development model based on Borg and Gall, the study involves needs assessment, product development, and evaluation to craft an effective entrepreneurship education framework for vocational schools. Insights from vocational education experts, entrepreneurship practitioners or teachers, and entrepreneurs are integral to developing this model. The findings show that entrepreneurship education is acceptable to be implemented in Indonesian vocational schools. The proposed model focuses on characteristic Indonesian mindset formation, practical entrepreneurial skills, and active industry collaboration, aiming to prepare graduates for both employment and selfemployment. This research has implications for the transformation of vocational education in Indonesia by providing a strong framework that supports graduates’ transition to the world of work and encourages entrepreneurial efforts, thereby contributing to broader economic development and innovation.
Volume: 14
Issue: 1
Page: 373-381
Publish at: 2025-02-01
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