Search Results for
"Vocational education"

This study examines the impact of teacher competency and industry-academic collaboration on vocational ability, focusing on technical, problem-solving, and soft skills. It also explores the mediating role of career self-efficacy and the moderating role of social support in these relationships. A quantitative and cross-sectional survey was conducted among Chinese students in higher vocational institutions. Stratified random sampling resulted in 350 distributed questionnaires with 270 completed responses. Data were analyzed using SmartPLS 4. Teacher competency and industry-academic collaboration both positively impacted vocational ability. Career self-efficacy mediated the relationships between these factors and vocational ability. Social support moderated these relationships highlighting its importance in enhancing vocational outcomes. This study integrates key factors— teacher competency, industry-academic collaboration, career self-efficacy, and social support providing a comprehensive understanding of vocational outcomes in higher vocational education. The findings offer insights to improve vocational education practices and policies, particularly in rapidly developing economies like China. Enhancing teacher competency, fostering industry-academic collaboration, and supporting career self-efficacy and social networks are crucial for improving vocational outcomes. © 2025 Conscientia Beam. All Rights Reserved.

The article updates the problem of developing digital skills in future teachers of specialized and vocational training. The possibilities of using informal education to solve this problem are identified. The need for developing modern digital skills of future teachers of specialized and vocational training based on competency-based, integrated, context-oriented and multimodal approaches is substantiated. During the experiment, a phased formation of digital skills is carried out: at the preparatory, project, training and final stages. The main task of the preparatory stage is to familiarize students with the features of using digital technologies, the structural components of digital skills and indicators of their formation. All students during their studies at the university take a course on the theoretical foundations of us ing digital technologies in education. At the project stage, the main task is to develop the ability of future teachers to professional self-management. Students of the experimental group additionally participate in a workshop and independently develop personal programs for the development of digital skills in the context of informal education. At the training stage, students of the experimental group implement these programs. At the final stage, students of the control and experimental groups perform creative work. Feedback on personal programs is provided by experts from among university teachers and practicing teachers. In the process of experimental work, the effectiveness of the development of digital skills in the context of informal education of future teachers is tested. The use of digital technologies is presented at three levels: household (low), user (medium), professional (high). The experiment shows the feasibility of using personal programs for informal education. Generalization of the results of the experimental work demonstrates the advantages of informal education in the formation of digital skills of future teachers of specialized and professional education. © 2025, Adam Marszalek Publishing House. All rights reserved.

The rapid advancement of big data technologies has transformed industries, necessitating the development of specialized educational programs to equip students with relevant skills. vocational and technical colleges play a crucial role in bridging the skill gap by offering big data professional education tailored to industry demands. However, assessing the quality and effectiveness of such programs remains a challenge due to the evolving nature of big data, the need for practical training, and alignment with industry requirements. This study proposes a comprehensive evaluation framework incorporating multiple criteria such as curriculum relevance, faculty expertise, infrastructure, industry collaboration, and student outcomes. By employing a Multi-Criteria Decision-Making (MCDM) approach, this research provides an in-depth analysis of big data education quality, ensuring that vocational institutions produce industry-ready graduates. We use two MCDM methods such as CRITIC method to compute the criteria weights and the VIKOR method to rank the alternatives. These methods are used with the Forest HyperSoft set to deal with criteria, sub criteria and sub-sub-criteria. We use five criteria and six alternatives in this study. These criteria are divided into Trees. Then we compute the criteria weights and rank the alternatives under each criterion. Then we obtain the rank of each criterion and combine these ranks into a final rank. © 2025, University of New Mexico. All rights reserved.

Ethiopia and China share a common educational agenda of cultivating and developing competent vocational graduates who meet the needs of the modern, technologically advanced industrial workplace. Unlike most of the literature, the present study adopted the self-determination theory to understand student learning motivation in the context of higher vocational education and training (VET) colleges in Ethiopia and China to reveal students’ satisfaction with psychological needs that are leveraged in building vocational professional development and identities. Ten senior higher VET students from each setting were recruited and participated in semistructured interviews. The study’s main finding affirms that although both groups felt they had the autonomy to choose the vocational field they sought to master, their learning process was subjected to traditional teaching methods, which ultimately restrained the participants’ feelings of competence because they trained in a less practical training space. Based on the study findings, we propose feasible policies and practical implications for meeting the motivational needs of VET students and promoting learning stability. © 2025 National Institute of education, Singapore.

Developing digital marketing competencies and team spirit is essential in vocational education to cope with the digital economy’s demands. Based on the needs assessment of vocational students and related literature research, this study discusses how to develop and implement the project-based Blended Learning (PjBBL) model and evaluates its effectiveness in enhancing digital marketing competencies and team spirit among vocational students. The research employs a quasi-experimental design with 90 students from Tongren Polytechnic College, Guizhou, China, divided equally into experimental and control groups. The experimental group followed the PjBBL model. The control group used blended learning (BL) methods. The learning activity lasted 8 weeks, pre-tests and post-tests were administered using a 5-point Likert scale for digital marketing competencies and team spirit. MANOVA analysis (level 0.05) showed a significant difference in digital marketing competencies and team spirit between PjBBL and BL. The results revealed that while both groups showed improvement, the experimental group achieved significantly higher scores in both areas, indicating the effectiveness of the PjBBL model. This study provides valuable insights into improving vocational education through innovative teaching approaches. © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Entrepreneurship education fosters economic growth and career development, yet innovative learning methods and research on openness to experience and creativity remain underexplored in higher vocational education. This study proposes the PjBBL-DT learning model and evaluates its impact on openness to experience and creativity through a 15-week 3-phase quasi-experiment with 61 first-year Chinese vocational students, using PjBBL model in Phase I and PjBBL-DT model in Phases II-III. Five experts evaluated the model, with mean and standard deviation scores indicating high quality. Repeated measures MANOVA revealed a significant improvement in creativity in Phase II, with no significant difference between Phases II and III, suggesting both immediate effects and retention. Openness to experience increased progressively across phases, demonstrating significant improvement but limited retention effect. The findings confirm the model's effectiveness in entrepreneurship education for higher vocational colleges. © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Introduction: This short report introduces an application of curriculum mapping in a postgraduate health professions continuing education setting. Our focus is on the Health Professions education Evaluation and Research (HPEER) Advanced Fellowship Program, a national interprofessional 2-year program offered through the Department of Veterans Affairs. Methods: We designed an Excel-based tool to align HPEER domains and competencies with curricular elements. An interprofessional team conducted an independent review of the curricula, ensuring consistency and accuracy in the mapping. Discrepancies were reconciled to maintain consistency. Results: The pilot use of the curriculum mapping tool showed that all planned competencies appeared in at least two sessions per year, with each competency appearing a median of six times. The curriculum featured a balance of didactic and interactive sessions, ensuring diverse learning experiences. Discussion: Our curriculum mapping tool demonstrates a program-wide approach, enabling program leaders to oversee the comprehensive alignment of educational content with fellowship goals. This approach enhances transparency and stakeholder engagement, offering a fresh perspective on curriculum mapping in postgraduate interprofessional education. Our method demonstrates significant potential for quality enhancement in various continuing education settings and demonstrates that CM need not rely on complex digital platforms to be effective. © This material is published by permission of the Health Professions education, Evaluation and Research Advanced Fellowship Coordinating Center, operated under the Department of Veterans Affairs under Grant No. #3HPECCD2020. The US Government retains for itself, and others acting on its behalf, a paid-up, non-exclusive, and irrevocable worldwide licence in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly and display publicly, by or on behalf of the Government.

This study focuses on developing a predictive modeling system to identify early signs of underperformance in vocational education, critical for building a skilled workforce. Addressing challenges like high dropout rates and inadequate graduate preparedness, the system utilizes machine learning techniques such as Neural Networks, Decision Trees, and Logistic Regression. Implemented in Python, it analyzes key features like academic records, attendance, engagement, and socioeconomic factors. Preprocessing steps, such as data cleaning and feature engineering, were implemented, and transfer learning was employed to adapt the model. This combination of feature engineering and transfer learning enables the transfer of knowledge from academic settings to vocational education by identifying and leveraging shared characteristics between the two domains. The system provides real time insights through automated reports and notifications, enabling targeted interventions to improve retention and graduation rates. This scalable approach advances educational technology and informs policies to enhance vocational education outcomes. © 2025 IEEE.

Technology is an ever-evolving topic at the forefront of conversations in education. For example, the use of artificial intelligence (AI) has highlighted the need for further discussion on its use in advanced learning. Within institutes of higher education (IHEs), students prepare for digital literacy and ever-changing technology tools. Due to the nature of this technological evolution, IHEs and future employers often work quickly. Further exploration may assist in collaborations and partnerships that streamline and strengthen the work related to increasing digital literacy. Institutes of Higher education (IHE) and Workforce Collaboration for Digital Literacy explores methodologies and strategies that highlight the collaboration between IHEs and the workforce. It highlights cutting-edge research on silo removal between IHEs and future employers pertaining to technology integration. Covering topics such as educational silos, technology access, and university libraries, this book is an excellent resource for educators, business owners, researchers, scholars, academicians, and more. Coverage: The many academic areas covered in this publication include, but are not limited to: • Digital Literacy • Educational Silos • Generative Artificial Intelligence (GAI) • Higher education • Information And Communication Technology (ICT) • Institutes of Higher education (IHEs) • Mental Well-Being • Open Online Courses • Rural vocational Schools • Sustainable Development Goals (SDGs) • Technology Access • University Libraries • Workforce Collaboration © 2025 by IGI Global Scientific Publishing. All rights reserved.