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Soft skills gap: aligning higher education with job market needs in Spain

10.11591/ijere.v14i4.31518
Marina-Paola Ojan , Pablo Lara-Navarra , Jordi Sánchez-Navarro , Judith Clares-Gavilán
In the dynamic and complex context surrounding the fourth and fifth industrial revolution, dominated by volatility and uncertainty, the importance of communication training, particularly in developing soft skills, is evident. This study advocates for the inclusion of these competencies in higher education and professional training in communication, ensuring they align with the current needs of the Spanish labor market. The gap between the competencies taught and those required by employers is examined to strengthen the connection between academic training at university level and work adaptability. The research examines the gap between the skills taught and those required by employers, aiming to strengthen the connection between university education and workplace adaptability. It emphasizes the need for greater alignment between academic profiles and job demands, proposing comprehensive search and analysis methods for improvement. Additionally, the study underscores the significance of communication training in preparing students for both present and future challenges. Adaptability and continuous updating of soft skills are essential for maintaining professional competitiveness in today’s era.
Volume: 14
Issue: 4
Page: 2891-2901
Publish at: 2025-08-01

Determinants of artificial intelligence acceptance among undergraduates

10.11591/ijere.v14i4.32565
Tan Owee Kowang , Lim Kim Yew , Goh Chin Fei , Ong Choon Hee
Despite the potential benefits of artificial intelligence (AI) brings to education, its extensive use does not automatically guarantee effective integration or consistent improvements in learning. Hence, this research aims to identify the determinants of AI acceptance among undergraduates and examine the relationship between these determinants and AI acceptance. Five determinants of AI acceptance were identified based on the technology acceptance model (TAM) and empirical evidence: perceived effectiveness of AI, user satisfaction, user attitude toward AI technology, attitude toward using AI, and user self-efficacy. This quantitative study focused on 791 undergraduates from a management school in Malaysia. A questionnaire was distributed to 310 undergraduates using a stratified sampling method, and 259 responses were collected. Descriptive analysis results indicated that undergraduates perceive attitudes toward AI technology and using AI as very important determinants of AI acceptance. Pearson correlation analysis also revealed that four determinants (perceived effectiveness of AI, satisfaction in using AI, attitude towards AI technology, attitude towards using AI) significantly correlated with AI acceptance. This finding suggests that, within the context of AI acceptance among management school undergraduates, attitude-related determinants are the primary drivers. The findings from this research could be used by the management school as a reference to enhance undergraduates’ AI acceptance levels and identify areas for inclusive education system improvement.
Volume: 14
Issue: 4
Page: 2773-2780
Publish at: 2025-08-01

Enhancing logo security: VGG19, autoencoder, and sequential fusion for fake logo detection

10.11591/ijict.v14i2.pp506-515
Debani Prasad Mishra , Prajna Jeet Ojha , Arul Kumar Dash , Sai Kanha Sethy , Sandip Ranjan Behera , Surender Reddy Salkuti
This paper deals with a way of detecting fake logos through the integration of visual geometry group-19 (VGG19), an autoencoder, and a sequential model. The approach consists of applying the method to a variety of datasets that have gone through resizing and augmentation, using VGG19 for extracting features effectively and autoencoder for abstracting them in a subtle manner. The combination of these elements in a sequential model account for the improved performance levels as far as accuracy, precision, recall, and F1-score are concerned when compared to existing approaches. This article assesses the strengths and limitations of the method and its adapted comprehension of brand identity symbols. Comparative analysis of these competing approaches reveals the benefits resulting from such fusion. To sum up, this paper is not only a major contribution to the domain of counterfeit logo detection but also suggests prospects for enhancing brand security in the digital world.
Volume: 14
Issue: 2
Page: 506-515
Publish at: 2025-08-01

Techno-economic analysis of a 4 MW solar photovoltaic capacity expansion in a remote Indonesian village

10.11591/ijece.v15i4.pp4133-4147
Agie Maliki Akbar , Fahmy Rinanda Saputri , David Tee
As of the end of 2022, Indonesia’s electrification ratio reached 99.63%, reflecting significant progress. However, the province of East Nusa Tenggara lags behind with an electrification ratio below 90%, indicating a considerable gap in energy access. This challenge is particularly evident in Oelpuah village, where frequent power outages occur due to the inadequacy of the existing 5 MW solar farm. This study proposes addressing this shortfall by expanding the solar farm capacity by an additional 4 MW. Comprehensive feasibility studies were conducted, evaluating solar radiation, natural disaster risks, and land use. The analysis, supported by PVSyst simulations, identified a suitable site with high radiation levels, though it is not entirely free from disaster risks. The design requires 13,500 solar panel modules, each with a capacity of 330 Wp, and seven 500 kW inverters. Optimal system performance is achieved with a 15-degree panel tilt and a 0-degree azimuth, aligning with the site's location south of the equator. This expansion could supply electricity to up to 4,014 households, each with a typical power usage of 0.825 kW. The study highlights the need for further research to enhance electricity coverage across Indonesia.
Volume: 15
Issue: 4
Page: 4133-4147
Publish at: 2025-08-01

Artificial intelligence competencies of vocational teachers using for the design of learning activities

10.11591/ijere.v14i4.32334
Raweewarn Rattanakha , Kanitta Hinon , Panita Wannapiroon , Naphong Wannapiroon , Jira Jitsupa , Nipone Sookpreedee
Currently, information technology used in teaching and learning management is constantly evolving. Therefore, the development of vocational teachers’ artificial intelligence competencies (AIC) of vocational teachers using artificial intelligence (AI) for the design of learning activities using questions is to develop the ability to use information technology in teaching and learning management with an emphasis on the use of AI for education. Teachers in the college received practical training on the application of AI in teaching and learning management. In using AI, which creates knowledge and understanding for teachers, it can be applied in the design of learning activities. From allowing teachers to practice, this has a positive effect on the increase in AI skills of teachers from before attending the training. Overall, vocational teachers have a great level of AIC; the average score is 21.72 points and from the assessment of overall satisfaction at the highest level. The training content is suitable for the current situation. The knowledge gained can be used to benefit in organizing teaching activities. The speakers have interesting teaching techniques.
Volume: 14
Issue: 4
Page: 3336-3344
Publish at: 2025-08-01

Near-infrared spectroscopy and machine learning to detect olive oil type: a systematic review

10.11591/ijece.v15i4.pp4120-4132
Leonardo Ledesma Ortecho , Enrique Romero José , Christian Ovalle , Heli Alejandro Cordova Berona
The present study evaluates the effectiveness of visible/near-infrared spectroscopy (VIS/NIR) combined with machine learning in olive oil type detection. A search strategy based on the population, intervention, comparison, and outcome (PICO) framework was employed to formulate specific equations used in Scopus, ScienceDirect, and PubMed databases. After applying exclusion criteria, 53 studies were included in the review following preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. The reviewed studies demonstrate that VIS/NIR spectroscopy coupled with machine learning allows rapid and accurate identification of different types of olive oil, highlighting the detection of fatty acids, polyphenols, and other vital compounds. However, variability in samples and processing conditions present significant challenges. Although the results are promising, further research is required to fully validate the efficacy and feasibility of this technology in industrial settings. This review provides a comprehensive overview of the advances, challenges, and opportunities in this field, highlighting the need to optimize machine learning models and standardize analysis procedures for practical application in the food industry.
Volume: 15
Issue: 4
Page: 4120-4132
Publish at: 2025-08-01

Gender differences in motivation and problem-solving in a physics course online problem-based learning

10.11591/ijere.v14i4.31105
Elnetthra Folly Eldy , Fauziah Sulaiman , Mohd Zaki Ishak , Lorna Uden , Jo-Ann Netto-Shek
Online learning has been crucial since COVID-19, yet its effectiveness, particularly in physics education, remains debated. Understanding students’ motivation and problem-solving abilities in online environments is critical. This paper examined and presented the gender difference in motivation and problem-solving skills using an integrated online problem-based learning (iON-PBL) in a physics course. Developed using analysis, design, development, implementation, and evaluation (ADDIE) mode, iON-PBL module of physics guided students through problem-solving activities over 13 weeks. A post-test–delayed post-test design was used to assess retention of motivation and problem-solving skills. The study involved 116 pre-university students from Universiti Malaysia Sabah (88 females, 28 males). Motivation was measured using the motivated strategies for learning questionnaire (MSLQ) (four components), and problem-solving skills were assessed with the problem-solving inventory (PSI) (three components). Data analysis was conducted using SPSS version 28. Findings showed a significant gender difference in the ‘cognitive strategy’ component of motivation at the post-test, favoring female students. However, this difference was not sustained in the delayed post-test. In contrast, no gender difference was found in problem-solving at the post-test, but females scored significantly higher in ‘personal control’ in the delayed post-test. These findings suggest that female students are more likely to maintain cognitive strategies and personal control in online learning. Educators should consider targeted strategies to support male students’ motivation and problem-solving development in virtual environments to foster gender equity. Educators should consider targeted strategies to support male students’ motivation and problem-solving development in virtual environments to foster gender equity.
Volume: 14
Issue: 4
Page: 2832-2845
Publish at: 2025-08-01

Learning disabilities teachers’ perceptions of employing artificial intelligence applications in teaching their students

10.11591/ijere.v14i4.32888
Mariam Alnaim , Ghada Al-Otaibi
This study explores the learning disabilities teachers’ perceptions of employing artificial intelligence (AI) applications in teaching their students in Saudi Arabia. A quantitative approach was utilized, distributing a questionnaire to 108 teachers of students with learning disabilities. Findings indicate a moderate level of AI application use, with tools like virtual reality (VR) and speech recognition being more commonly recognized and valued. However, other applications, such as Thinkster Math, remain underutilized, revealing gaps in effective AI integration. The study recommends targeted strategies to overcome barriers such as insufficient teacher training, lack of digital infrastructure, and the need for culturally responsive AI tools. Key solutions include developing professional development programs, improving access to technology, and providing financial incentives to encourage wider adoption. By addressing these challenges and implementing these recommendations, Saudi Arabia can enhance its special education landscape, enabling teachers to leverage AI as a transformative tool and fostering a more inclusive and adaptive learning environment for students with learning disabilities. This study underscores the need for continuous research and feedback to refine AI tools, ensuring they meet educational goals and improve student outcomes.
Volume: 14
Issue: 4
Page: 2732-2741
Publish at: 2025-08-01

Study on parental involvement in Vietnamese primary students’ learning: insights from the era of educational reform

10.11591/ijere.v14i4.32897
Thi Hong Hanh Van , Xuan Quang Tran , Thi Phuong Vy Nguyen , Thai Hung Le
In light of Vietnam’s recent educational reforms emphasizing competency-based learning, this research explores how Vietnamese parents engage in their children’s education and the relationship between this involvement and students’ academic performance. Employing both quantitative (surveys) and qualitative (interviews) methods, the study focuses on three critical aspects of parenting and the family environment, based on Epstein’s theory: communication between parents and teachers, volunteering, and collaboration with the community. Quantitative data, analyzed using SPSS software, revealed the frequency of parental involvement activities, providing a comprehensive picture of both common and less frequent activities. Pearson correlation results confirmed a positive relationship between active parental involvement and student performance. The qualitative findings further highlight the challenges parents face when engaging in their children’s education and offer suggestions for improving parental participation. Overall, the paper provides valuable insights into the dynamics of parental involvement in Vietnamese schools and proposes practical, contextually appropriate solutions to enhance educational quality by strengthening cooperation between schools and parents.
Volume: 14
Issue: 4
Page: 2487-2499
Publish at: 2025-08-01

Using Canva and Microsoft Teams to support students’ writing tasks

10.11591/ijere.v14i4.27985
Wan Zahidah Wan Sulaiman , zuraina ali , Zarina Mohd Ali , Shahid Hussain Shahid , Muhammad Ishtiaq , Norsuhaily Abu Bakar
Teachers and students face difficulties in remote learning. These difficulties can be greatly reduced by utilizing applications, such as Microsoft Teams (MS Teams) and Canva. This study investigates the effectiveness of using Canva and MS Teams as helpful resources for students assigned to write informative speech essays. Employing a sequential explanatory research design in a mixed-method approach, the study involved sixteen English majors from a private university located on Malaysia’s East Coast. Students used MS Teams to complete pre-and post-tests, and afterward, interviews were held to learn more about how they felt about using Canva. The pre and post-tests showed that students improved their writing abilities when using MS Teams since they had a chance to collaborate with their peers and teachers. Qualitative findings also revealed that online learning environments promoted interaction between students and teachers and between students and their peers. The results suggest that incorporating web tools like MS Teams and Canva could enhance students’ learning experience as they complete their writing projects. Overall, this study highlights the potential benefits of incorporating web technologies into the writing process and underscores the importance of seeking student feedback to improve the effectiveness of these tools.
Volume: 14
Issue: 4
Page: 3295-3303
Publish at: 2025-08-01

Driving school program to strengthening anti-corruption education within the integrity zone policy

10.11591/ijere.v14i4.28773
Suyadi Suyadi , Zalik Nuryana , Anom Wahyu Asmorojati , Anton Yudhana
For an extended period, education institutions have functioned independently, resulting in a notable disparity in educational quality. The Merdeka Belajar Kampus Merdeka (MBKM) promotes collaboration between educational institutions and schools, with the aim of serving as mentors for joint program development. This groundbreaking research delves deeply into the pivotal roles played by both lecturers and students within the MBKM program. They emerge as mentors in the crusade for implementing anti-corruption education within the dynamic context of Sekolah Penggerak, also known as the driving school program (DSP). Conducted as a qualitative descriptive study, this research draws its data from the collaborative efforts between higher education institutions and schools in developing anti-corruption education, leading to recognition from the Indonesian Corruption Eradication Commission (KPK-RI). The data collection process unfolds through a meticulously orchestrated combination of observations, in-depth interviews, and thorough documentation. The findings of this study are nothing short of transformative, as they underscore how the active involvement of MBKM’s lecturers and students in anti-corruption education serves as a potent catalyst, reinforcing the integrity zone policy within the DSP program. This seamless integration of anti-corruption education with Islamic education, encompassing profound concepts like riswah (bribery), ghulul (betrayal), and mukabarah-ghasab (seizing), represents a paradigm shift in pedagogical strategies.
Volume: 14
Issue: 4
Page: 2722-2731
Publish at: 2025-08-01

Hope and grit: the driving forces behind student-athletes’ motivation in sports and academics

10.11591/ijere.v14i4.32916
Jet C. Longakit , Joseph Lobo , Teejay Panganiban , Jay Mark D. Sinag , Elvie F. Celestial , Janice D. Ballera
While the challenges student-athletes face in balancing academics and sports have garnered increasing attention, few studies have explored how factors like hope and grit contribute to this balance and enhance motivation. This study investigated the relationship between hope, grit, and motivation of academic and sports of student-athletes. A total of 247 student-athletes of Mindanao State University-Iligan Institute of Technology (MSU-IIT) answered a set of questionnaires assessing grit, dispositional hope, and student-athletes motivation towards sports and academics with the age range of 18-24 years old. Ethical approval was gained from the participants. The results showed that factors of hope (agency and pathways) and grit (consistency of interest or COI and perseverance of effort or POE) were significant predictors of motivation in sports and academics. This suggests that student-athletes with higher levels of hope and grit demonstrate increased motivation in both domains. These results could offer a more valuable insights for coaches, educators, and sports psychologist striving to support the long-term success and wellbeing of student-athletes.
Volume: 14
Issue: 4
Page: 2574-2583
Publish at: 2025-08-01

Deep learning for grape leaf disease detection

10.11591/ijict.v14i2.pp653-662
Pragati Patil , Priyanka Jadhav , Nandini Chaudhari , Nitesh Sureja , Umesh Pawar
Agriculture is crucial to India's economy. Agriculture supports almost 75% of the world's population and much of its gross domestic product (GDP). Climate and environmental changes pose a threat to agriculture. India is recognized for its grapes, a commercially important fruit. Diseases reduce grape yields by 10-30%. If not recognized and treated early, grape diseases can cost farmers a lot. The main grape diseases include downy and powdery mildew, leaf blight, esca, and black rot. This work creates an Android grape disease detection app which uses machine learning. When a farmer submits a snapshot of a diseased grape leaf, the smartphone app identifies the ailment and offers grape plant disease prevention tips. In this research, an android app that detects grape plant illnesses use convolutional neural network (CNN) and AlexNet machine learning architectures. We investigated and compared CNN and AlexNet architecture's efficacy for grape disease detection using accuracy and other metrics. The dataset used comes from Kaggle. CNN and AlexNet architectures yielded 98.04% and 99.03% accuracy. AlexNet was more accurate than CNN in the final result.
Volume: 14
Issue: 2
Page: 653-662
Publish at: 2025-08-01

How digital platforms improve teaching: comparing teacher performance across Peru

10.11591/ijere.v14i4.32562
Yurfa Carolina Medina-Bedón , Liliana Asuncion Sumarriva-Bustinza , Mery Jesús Arias Huánuco , Hugo Augusto Carlos-Yangali , Gladys Margarita Espinoza-Herrera , Luis Donato Araujo-Reyes , Maura Natalia Alfaro-Saavedra , Yeni Yauri-Huiza , Zaida Olinda Pumacayo-Sanchez , Karina Eddmy Madrid-Gómez
This study addresses the challenge of enhancing pedagogical content knowledge (PCK) performance among primary education teachers in Peru, particularly in the context of increasing reliance on digital platforms. With significant regional and demographic disparities in access to digital resources, this research aims to evaluate the effectiveness of digital platforms in supporting teaching practices. Using a quantitative, cross-sectional design, the study analyzed data from the 2022 national unique test (PUN), which assesses cognitive and pedagogical skills among teachers, and a digital platform integration questionnaire (DPIQ) administered to 2,000 teachers. The findings revealed a positive correlation between digital platform usage and PCK performance, with younger and female teachers demonstrating higher scores. Urban teachers also outperformed their rural counterparts, highlighting regional disparities in digital access. The study concludes that integrating digital platforms into teaching practices can enhance PCK performance, but there is a need for targeted professional development and investment in digital infrastructure, particularly in underserved areas. Addressing these disparities is crucial to ensuring that all teachers can benefit from digital advancements, ultimately improving educational outcomes.
Volume: 14
Issue: 4
Page: 2966-2978
Publish at: 2025-08-01

Exploring ICT competency and communication preferences in higher education: insights from Croatia

10.11591/ijere.v14i4.33513
Hrvoje Budić , Marko Šostar , Arnaldo Ryngelblum
The digital transformation of education underscores the need for effective integration of information and communication technologies (ICT) in higher education. This study examines differences in ICT usage between teaching staff and students across various types of higher education institutions in Croatia, focusing on the impact of institution type and academic programs on ICT usage levels, digital competencies, and communication preferences. A quantitative research approach was employed, with data collected via a survey distributed to 70 teaching staff and 472 students using random sampling from public universities, public polytechnics, and private higher education institutions. The results reveal significant disparities in digital competencies, with students in private institutions demonstrating higher ICT usage compared to public institutions. Additionally, both groups favor synchronous communication (SC), although students display a stronger preference. These findings highlight a digital divide within academia and the need for targeted ICT training, particularly in public institutions. The study proposes measures to enhance ICT infrastructure and develop digital competencies through systematic workshops and training sessions. This research emphasizes the importance of addressing digital inequalities and improving the quality of education by integrating advanced technological solutions in higher education.
Volume: 14
Issue: 4
Page: 2931-2944
Publish at: 2025-08-01
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