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"learning"

Vocational schools aim to equip students with the knowledge and skills needed to compete in the job market. However, the high unemployment rate among vocational high school graduates has demonstrated the ineffectiveness of learning in vocational schools. The implementation of teaching factory-based learning in vocational schools was theoretically expected to strengthen students' employability skills, which consist of seven indicators: fundamental skills, essential skills, workplace skills, twenty-first century skills, learning and innovation skills, information media and technology skills, and life and career skills. This study used a longitudinal approach to analyze the development of students' employability skills after being involved in teaching factory-based learning for five semesters. The population in this study were students from three public vocational high schools in East Java, Indonesia. Proportional random sampling was used to determine the sample size. Descriptive analysis was used in this study to describe the development of students' employability skills. Meanwhile, multivariate analysis was used to determine the most effective teaching factory-based learning model in strengthening students' employability skills. This study found that students’ involvement in teaching factory-based learning for five semesters significantly improved employability skills. The most effective learning models for sequentially strengthening students' employability skills are dual systems, industry-based learning, production-based education and training, and competency-based training. This study recommends that vocational schools intensify practical learning as a key for strengthening graduates' employability skills. Furthermore, schools should strengthen collaboration with businesses and industry to implement TEFA-based learning more effectively. © The Authors.

Cognitive processes, including understanding, thinking, and interpretation, are necessary to influence safe behaviour in cyberspace. However, among Technical and Vocational Education and Training (TVET) youth, educational focus prioritises technical skills development over cognitive and digital skills. Furthermore, systematic and coherent approaches are lacking to provide students with consistent, quality learning experiences that enhance their understanding of cyber ethics. The research model integrates the cognitive appraisal components based on the Protection Motivation Theory (PMT) with three social learning strategies: cyber ethical digital games, lecturer reminders, and motivational impact of achievement certificates, to understand TVET youth ethical decision-making in cyberspace refers to PAPA model (privacy, accuracy, property, and accessibility). The research employed a quantitative approach using a survey method with questionnaire instruments for data collection, with a random sample of 340 respondents selected from six community colleges around Selangor. Partial least squares structural equation modelling (PLS-SEM) analysis through SmartPLS version 4 software was used to analyse hypotheses and validate the developed model. Hypothesis testing revealed that 12 out of 14 hypotheses were significant, with Perceived Severity (PS), Self-Efficacy (SE), and Response Efficacy (RE) suggesting relationships in TVET youth’s cyber ethical behaviour. The three social learning strategies also demonstrated significant relationships with cyber threats’ appraisal and response processes. The developed Cyber Ethical Behavioural (CEB) model enhances the understanding of TVET youth’s cyber ethical behaviour and promotes the coordination of cyber ethics knowledge enhancement in TVET institutional environments, aligning with new technological developments such as Artificial Intelligence (AI). © 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 pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).

Background: In Benin, Technical Vocational Education and Training (TVET) and Apprenticeship Programs play a prominent role in the education system. The national unemployment rate was as low as 1.7% in 2022, suggesting that these forms of training contribute to aligning education outcomes with labour market needs. Objective: This research analyses the effectiveness of Benin employees focusing on the contribution of TVET at school and apprenticeship to the business sector. Methodology: To conduct this research, we gathered data by using literature and 45 semi-structured interviews. Respondents were selected from department of secondary education and TVET, agency for continuing education and apprenticeship, Swisscontact personnel, staff of the business sector and scholars in Parakou and Cotonou, Benin Republic. Findings: First, although TVET in secondary school offered several career opportunities to the students, 79 percent of the participants claim that TVET does not promote employment. The reforms of apprenticeship led to two formal apprenticeship programs: a dual training track and a renovated traditional apprenticeship. Second, 44.4 percent of participants found that the TVET programs as well as the two apprenticeship programs, do not meet the needs of the Beninese market. Though, 83 percent argued that people in Benin have preference for long-term education. It appears that those who achieve more education, are able to earn. Third, the research concludes that neither TVET nor formal apprenticeships, is effective to promote suitable employment and earning. Practical implication: Reforming technical education by matching the skills learning to the needs can lead to decent work. © The Author(s) 2025.

The rapid advancement of artificial intelligence (AI) has significantly transformed various educational domains, including engineering education. Despite AI’s growing prevalence, limited research has explored the determinants influencing engineering students' acceptance of AI. This study investigates the factors shaping AI acceptance among engineering students in Indonesia. Using Structural Equation Modeling (SEM) with the Partial Least Squares (PLS) approach, data were collected from 158 engineering students across multiple universities. The research model incorporates six constructs: Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Social Influence (SI), Facilitating Conditions (FC), Self-Efficacy (SE), and Perceived Risks (PR), each operationalized through seven measurement indicators. The results indicate that PU, PEOU, SI, and SE have significant positive effects on AI acceptance, while PR exerts a significant negative influence. Conversely, FC does not demonstrate a significant impact. These findings offer theoretical and practical implications for fostering AI adoption in engineering education, including strategies for educators, policymakers, and developers of AI-based tools to enhance user acceptance. This study extends the literature on technology acceptance in educational settings, providing actionable insights for improving the integration of AI in higher education. © 2025, The Online learning Consortium. All rights reserved.

This study develops and validates an integrated model explaining teachers’ core competence, focusing on three antecedents-teaching professionalism, workplace embeddedness, and innovation capability-with teachers’ job satisfaction as the key mediator that converts capabilities into sustained outputs. Using a questionnaire survey of university faculty, we distributed 800 surveys and collected 713 valid responses, for an effective response rate of 89%. The results show: (1) teaching professionalism positively enhances both job satisfaction and core competence; (2) within innovation capability, exploitation contributes more to job satisfaction, whereas exploration exerts a stronger influence on both subdimensions of core competence; (3) job satisfaction has a stable but moderate positive effect on core competence; and (4) the two subdimensions of core competence are highly correlated, indicating that institutional and process knowledge capabilities are mutually reinforcing. Theoretically, drawing on RBV/KBV, dynamic capabilities, social capital, and the JD-R framework, this study integrates the evidence chain among capability, satisfaction, and output, and proposes testable second-order process constructs. Practically, it offers governance-level investment priorities and evaluation indicators, integrating professional learning communities, deep workplace linkages, and value-aligned digital/AI integration into a single closed-loop management cycle to drive evidence-based improvements in curriculum and assessment, thereby enabling teachers to consistently deliver high-quality learning outcomes. © 2025, Expert Projects. All rights reserved.

This pilot practitioner inquiry examines the use of AI-generated podcasts within a higher education research module. The study investigated two questions: (1) How do students experience, perceive, and make use of AI-generated podcasts as part of their learning? (2) What opportunities, challenges, and pedagogical considerations emerge for the educator when designing and integrating AI-generated podcasts into teaching practice? Google’s NotebookLM was used to create short recordings that summarised lecture topics, addressed student queries, and offered assignment guidance. Data were gathered from both the educator’s reflective journal and a student focus group. Findings suggest that students valued the novelty, accessibility, and supportive tone of the podcasts. They described the recordings as helpful in revisiting key ideas, clarifying uncertainties, and managing study along with other responsibilities. The educator found the podcasts practical to produce and noted that they contributed to more focused classroom discussions. At the same time, both students and the educator identified limitations, including the constraints of an audio-only format, the need for transparency when using AI, and the additional time required. As a pilot study, the findings provide indicative insights rather than generalisable conclusions. The work points to the potential of AI-generated podcasts as a supplementary resource that may reinforce understanding and support independent study, while also highlighting considerations around inclusivity, educator workload, and responsible AI use in higher education. © 2025 by the author.

Vocational education and training (VET) is a strategic driver of national education and skills development systems. It covers both Initial VET (IVET), which provides young people with vocational qualifications before they enter the labor market, and Continuing VET (CVET), which supports adults in updating or expanding their skills throughout their working lives. VET provides individuals with essential skills for employment and supports economies in adapting to technological, labor market, and social changes. Within the European Union (EU), VET plays a central role in addressing labor market transformation, the green and digital transitions, the rise of artificial intelligence, and the pursuit of social equity. This paper presents a data-driven analysis of VET in the EU countries. It reviews the relevant literature and outlines the role of Cedefop, the European Centre for the Development of Vocational Training, together with its main VET performance indicators. The analysis draws on publicly available Cedefop data on key VET indicators, filtered for reliability and systematically processed to ensure robust results. This research focuses on a selected set of key indicators covering participation in IVET at upper- and post-secondary levels, adult participation in both formal and non-formal learning, government and enterprise expenditure on training, the gender employment gap, and adult employment rates. These indicators are derived from Cedefop data spanning the period 2010–2024, with coverage varying across indicators. This study applies descriptive analysis to identify outlier countries, correlation analysis to explore relationships between indicators, and cluster analysis to group countries with similar VET profiles. It also compares the largest EU countries using common indicators. The results suggest key patterns, differences, and connections in VET performance across EU countries, offering insights for policy development and future research in VET. © 2025 by the authors.

Vocational training aims to facilitate the acquisition of a series of professional skills by students, specified through a series of learning Outcomes described in the official curricula. This requires teachers to adopt a wide variety of teaching methods and resources that allow for an appropriate match between learning styles and teaching styles, covering the diversity of styles present among students, to facilitate the achievement of all students. The students’ perception of the usefulness of the teaching resources used is an important factor in achieving this balance, and as a guide for better planning the methods and resources to be used in the classroom. This exploratory case study investigates students’ perceptions of the usefulness of different teaching resources and methods used to achieve the learning outcomes set out in the subject of water network installation and commissioning in an intermediate vocational training programme for water networks and treatment plants. The data was collected through a survey and individual interviews. The results of the research show that, despite a predominant preference for resources and methods associated with practical activities, as might be expected in vocational training, a significant heterogeneity in the attribution of usefulness to resources within the group was identified, which could be linked to different learning styles. Moreover, different dimensions emerged regarding the perception of usefulness that could better guide course planning towards a balanced diversification of methods and resources. © 2025 by the authors.

This empirical study quantifies discrepancies in expectations between Chinese accounting VET interns and industry supervisors in work-based apprenticeships, aiming to bridge VET curricula with labor market demands to foster competence development and school-to-work transitions. Employing quantitative surveys (n=121) and non-parametric tests (Mann-Whitney U; Cronbach’s α >0.7 for reliability), this VET-focused study uncovers perceptual gaps among stakeholders in Chinese accounting apprenticeships, highlighting misalignments between academic preparation and industry demands that undermine VET effectiveness in higher education. There is a statistically significant difference between interns and supervisors (U = 1321.50, p = 0.02). The data shows that the two groups have very different ideas about the value of internships and the skills they want to improve. Interns typically prioritize personal development and skill enhancement, while supervisors concentrate on organizational efficiency and technical proficiency. These findings emphasize the necessity for enhanced communication and alignment between educational institutions and industry practitioners to ensure that internships fulfill both academic and professional objectives in interdisciplinary settings. This study advances empirical VET research by offering comparative evidence from China, with implications for designing work-based learning programs and aligning stakeholder expectations to enhance global VET outcomes, particularly in collectivist contexts. © 2025, Expert Projects. All rights reserved.

The purpose of this paper is to provide a comparative policy analysis of successful strategies that have been implemented across European countries to address early school leaving (ESL) and academic underachievement. Employing a transformative and multidimensional approach, the study examines systemic and local interventions that integrate cognitive and socio-emotional dimensions of learning. Using Eurostat data to categorise countries based on their ESL reduction progress, the analysis evaluates legislative frameworks, policy initiatives, and educational practices through the prevention, intervention, and compensation model. The findings identify common themes such as the expansion of early childhood education and care (ECEC), enhancement of guidance and counselling services, targeted support for socio-economically disadvantaged groups, inclusive policies for marginalised populations including Roma communities, and the development of vocational and second-chance education pathways. The paper highlights the critical importance of coherent and scalable policy design to reduce educational inequalities and contribute to achieving European Union ESL reduction targets by 2030. It advances policy discourse by emphasising the essential need for balanced preventive and compensatory measures to improve educational outcomes and to foster social inclusion across varied national contexts. © 2025 by the authors.