Search Results for
"learning"

With the current globalized hospitality sector, workers need to possess competent English communicative skills to communicate effectively with foreign guests. Assuming this, the current research examined the synergistic effect of Task-Based Language Teaching (TBLT) and Translanguaging in improving English language competence and Willingness to Communicate (WTC) among 25 Indonesian hotel employees for a 16-week training program. The research employed a mixed-methods concurrent triangulation design with realistic role-play situations and bilingual approaches to building useable language capacity. Quantitative results demonstrated highly significant gains in task effectiveness, interest, and confidence measures, and significant gains in writing (pre-test M = 63.44; post-test M = 82.36, p < 0.001, d = 1.91) and speaking proficiency (pre-test M = 72.08; post-test M = 82.88, p < 0.001, d = 1.64). Translanguaging facilitated understanding and diminished anxiety, but its negative correlation with WTC (r = −0.87, p = 0.002) underscored limitations when over-reliant upon. Qualitative analysis underscored the value of role-playing in recreating real-life scenarios and gaining confidence, as well as the need to balance bilingual support with immersion in English. The outcomes provide a framework for context-sensitive, multilingual professional development program design. © 2025 The Author

This study aims to explore the impact of Edpuzzle-based learning media on conceptual understanding, learning motivation, and student competence, and their subsequent effects on learning outcomes in vocational education, particularly in the context of basic photography elements. A quantitative approach was employed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to test the relationships among latent variables. The study involved 60 students from SMK Negeri 1 Gunung Talang and SMK Negeri 4 Padang, Sumatera Barat. The results show significant positive impacts of Edpuzzle-based learning media on conceptual understanding (β = 0.482, p < 0.001), learning motivation (β = 0.259, p < 0.01), and student competence (β = 0.394, p < 0.001). Furthermore, conceptual understanding significantly affected learning outcomes (β = 0.398, p < 0.001) and student competence (β = 0.356, p < 0.001). learning motivation was also found to significantly influence learning outcomes (β = 0.382, p < 0.001) and student competence (β = 0.303, p < 0.01). The findings highlight the potential of Edpuzzle in enhancing both the motivation and competence of students, contributing positively to their learning outcomes. This research offers valuable insights into integrating interactive technology in vocational education, particularly in adapting teaching methods to meet industry demands in the digital era. © 2025, Arts and Science Press Pte. Ltd.. All rights reserved.

In today's competitive job market, coupled with rapid technological developments and global events like the pandemic, securing employment has become increasingly difficult for new graduates. Therefore, this study aims to identify the key features that influence the employment status (employed or unemployed) and type (regular or nonregular) of university graduates in South Korea using several machine learning methods including logistic regression, decision tree, random forest, XGBoost, support vector machine, neural network, and Naïve Bayes. Among these methods, XGBoost and neural network demonstrated the highest performance. We applied the SHAP (SHapley Additive exPlanations), one of the XAI (eXplainable AI) techniques, to the XGBoost model. The results revealed that cumulative GPA is the most significant factor influencing labor market outcomes. Furthermore, geographical location, including the location of the university, high school, and current city of residence, as well as family background factors such as parents' occupation and income at the time of university admission, and current assets also played crucial roles. Overall, these results demonstrate the significant impact of academic performance, geographical location, and family background in shaping graduates' employment outcomes. These findings offer valuable insights for policymakers, educational institutions, students, and their families to develop strategies and policies for improving employment prospects. © 2025 KIIE

This paper aims to highlight the significance and impact of an educational initiative developed at the Faculty of Electrical Engineering, Technical University of Cluj-Napoca (TUCN), Romania, aimed at reducing student dropout rates. Traditional learning methods in electrical engineering often fall short in providing real-world applications, making it challenging for students to stay engaged. To address this, the initiative took the form of a student-led club, Robotelier, which embraced interactive, team-based learning approaches. By integrating theoretical knowledge with hands-on applications and project-based learning, the club fosters a dynamic and engaging educational environment. Beyond enhancing technical expertise, it also provides a valuable platform for students to develop essential social and soft skills. What sets Robotelier apart is its peer-driven model, designed by students for students, creating a supportive community that directly contributes to reducing dropout rates at TUCN. © 2025 IEEE.

Purpose – This study aims to shed light on how work-integrated learning programs (WILP) affect graduate employability, job satisfaction and students’ adaptability to sustainable career transitions in comparison to participants who were not part of WILP. Through a validated model, this study also attempted to map the relationships among employability, job satisfaction, industry engagement and networking and skill enhancement under the auspices of WILP. Design/methodology/approach – In order to assess the study’s objectives, the researchers used structural equation modeling to analyze the quantitative data. Purposive and snowball sampling methods were used to gather primary data from 490 participants, of whom 295 were WIL participants and 195 were non-WIL participants who were recent graduates. Using regression analysis, structural equation modeling (SEM) and exploratory factor analysis (EFA), the objectives have been proved and the model validated. Findings – The findings of this study show that WIL graduates (M = 4.20 and SD = 0.60) and non-WIL graduates (M = 3.65 and SD = 0.65) had a statistically significant difference in career satisfaction. In every dependent variable, WIL participants outperform non-participants. According to SEM, WIL plays a crucial role in deciding students’ professional success by indirectly influencing career satisfaction through skill development, exposure to the industry, and self-confidence, all of which improve employability. The model displays good fit indices (CFI = 0.95, TLI = 0.94 and RMSEA = 0.04), affirming its strength and validity. Practical implications – Academicians, policymakers and organizations can rely on the suggestions of this study to enhance graduates’ employability and satisfaction. The results specify that WIL should be designed to cater to the industry demands, which in turn results in job readiness. Social implications – The study signifies the role of WIL in expediting positive career transitions, which in turn results in augmenting employability and raising economic stability. It advocates the broader-level application of WIL initiatives to link educational outcomes with industry demands. Originality/value – This study reinforces the existing literature by suggesting an advanced model that connects numerous features of WIL programs and their impact on career success. It can be considered one of the few researchers to empirically prove the links between these variables using structural equation modeling (SEM). © 2025 Emerald Publishing Limited

Background: Professional practice placements (work-integrated learning (WIL)) enable practical application of essential knowledge and skills, from the health information management university curricula, aligned to profession entry-level competencies. Objectives: To (1) identify formal (explicit learning outcomes (ELOs)) and informal (derived learning outcomes (DLOs)) articulated in final-year, health information management WIL proposals, 2012–2021, at Australia’s La Trobe University; and (2) map these to the contemporaneous, national Health Information Manager (HIM) profession entry-level competency (sub-)domains. Method: A random sample (20%; n = 129) of 2012–2021 final-year placement proposals was interrogated using documentary analysis. ELOs and DLOs were extracted and categorised to the (sub-)domains of the Health Information Management Association of Australia’s (2017) HIM Professional Competency Standards; between-group comparisons were made. Results: Of the 129 proposals: 38 (29.5%) were absent ELOs; one had no project description; almost 74% were project-related. Predominant sub-domains in Domain A, “Generic professional skills”: communication (in 63.7% of ELOs; 61.2% of DLOs); teamwork (40.7% ELOs; 50.8% DLOs). Predominant sub-domains in the eight profession-specific competency domains: “Health information services organisation and management” (Domain I; 60.5% ELOs; 100% DLOs); “Health information and records management” (Domain B; 54.9% ELOs; 56.3% DLOs); “Research methods” (Domain E; 45.1% ELOs; 44.5% DLOs). ELOs were most commonly aligned to four discipline-specific domains; DLOs were distributed across five. Conclusion: Analysis of the knowledge-skills learning outcomes for final-year, student-HIM placements has generated recommendations to support agency supervisors in framing WIL project proposals. Implications for health information management practice: This research will support more robust WIL to complement student HIMs’ academic education for competent, postgraduation practice. © The Author(s) 2025. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).

Debugging constitutes a pivotal component in the learning curve of programming, serving not only to enhance coding proficiencies but also to cultivate thinking skills. However, debugging tools embedded in integrated development environments (IDEs) often provide limited error diagnosis, which may reduce students” engagement with coding and inhibit their learning performances. This study therefore proposed a Reflective Generative Artificial Intelligence (GenAJ) Debugging (RGD) approach, an innovative debugging approach based on reflective strategies and operationalized through a GenAI tool, an intelligent conversational agent. To assess the performance of the approach, we used a quasi-experimental design and recruited 80 high school students from two classes of a province in eastern China. One class with 40 students was selected to be the experimental group using the RGD approach; the other class with 40 students was the control group utilizing the conventional coding and debuggmg (C’GD) approach. The results depicted that the RGD group better enhanced students” learning achievement than the CGD group. Nevertheless, a significant difference was found in the two groups” computational thinking skills. The findings could be a reference to instructors and researchers intending to use GenAI in programming classes. © Creative Commons CC-BY-NC-ND 3.0 license (https://creativecommons.org/licenses/by-nc-nd/3.0/).

This study investigates business students' perceptions in the United Arab Emirates (UAE) regarding their job readiness as they approach graduation. Recognizing the critical role of soft skills in securing employment, the research aims to evaluate the preparedness of UAE graduates for the competitive job market. A survey was carried out among 156 senior business students from various UAE universities, resulting in 90 usable responses. Quantitative analysis using statistical methods revealed that students prioritize communication, adaptability, cultural intelligence, and problem-solving as essential for securing entry-level positions. While participants expressed confidence in their academic and teamwork abilities, they identified creativity, innovation, and effective conflict resolution areas needing improvement. Additionally, the findings emphasize the significance of lifelong learning in navigating the UAE’s dynamic economy. This research provides actionable insights to align educational curricula with industry needs and better prepare graduates for the workforce. ©2025 IEEE.

This study aims to explore the impact of ChatGPT on students' perceptions during debates in a pedagogical course. The authors developed four innovative formats of in-class debate involving ChatGPT, where artificial intelligence acts as a consultant, an opponent, an expert or combined roles. Data was collected from a survey of 84 students of four academic groups and statistically analyzed using CAP Perceived learning Scale. Results of the study was explorer with analyze ANOVA. Findings reveal that using ChatGPT-3.5 as an opponent and an expert has the most profound impact on student’s cognitive and affective perceptions, opening new opportunities for fostering critical thinking and active learning. The study provides evidence-based recommendations for effectively integrating artificial intelligence into teaching and learning. ©2025 IEEE.

The incorporation of emerging technologies in educational environments is an undeniable phenomenon. The successful adoption of these technologies is heavily influenced by teachers' perceptions and understanding of them. In this study, we aimed to investigate the readiness of science teachers in post-basic schools to effectively integrate Augmented Reality (AR) into their instructional practices, taking into account their educational backgrounds. A semi-structured interview approach was used to collect data from a sample of 10 science teachers in two post-basic schools in the Al-Batinah North governorate of the Sultanate of Oman. The results suggested that science teachers show a propensity to use AR; however, not all possess prior familiarity with the technology. Subjects such as physics, chemistry, and biology were identified as areas where AR could significantly enhance learning outcomes. Participants recommended the introduction of instructional programs focused on the application of AR. Additionally, some teachers expressed caution regarding potential adverse effects of AR on humans, a scepticism likely stemming from limited exposure to tangible technological devices. This study contributes to the theoretical understanding by providing empirical evidence that validates the AR Readiness Index as a useful framework for exploring teachers' preparedness to effectively employ emerging technologies. ©2025 the Author(s).