Search Results for
"learning"

This study investigates how system characteristics and experiential factors influence learners’ satisfaction and continuous participation intention in business simulation systems. Drawing on survey data from 312 learners, the research examines the effects of simulation fidelity, system interactivity, multimedia richness, team collaboration, and novelty of business challenges on memorable learning experiences and satisfaction outcomes. Using PLS-SEM, the findings reveal that all system characteristics significantly enhance memorable learning experiences, which in turn strongly predict both learning satisfaction and the intention to continue participating. Notably, while simulation fidelity boosts experiential quality, its direct effect on satisfaction is non-significant, underscoring the importance of emotionally engaging design elements. By integrating cognitive, affective, and behavioral dimensions, the study advances experiential learning theory and offers actionable insights for designing effective simulation-based learning environments. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

One of the major challenges of the German vocational education and training (VET) system is the integration of adolescents with unfavorable learning prerequisites, i.e., individuals with no or lower school-leaving certificates or low levels of basic competencies (e.g., reading and mathematics). This paper examines the extent to which trainees’ learning prerequisites affect the development of professional knowledge during VET. In addition, the analysis focuses on the role of learning conditions during VET in reducing inequalities that stem from differences in trainees’ learning prerequisites. This paper implements a longitudinal design to examine within-person effects regarding the professional knowledge of N = 401 prospective chefs in a German dual VET program over the first two years of VET. Based on a domain-specific knowledge test, weighted likelihood estimates (WLE) are calculated as person parameter estimates for trainees’ professional knowledge at the beginning (t1) and the second year of VET (t3). Following the idea of value-added modeling, professional knowledge at t3 serves as the dependent variable in a structural equation model. Trainees’ professional knowledge level at t3 is modeled as a function of the initial professional knowledge level (t1) and trainees’ learning prerequisites when entering the VET program (educational background and basic competencies) as well as learning conditions (work assignments, social interactions, and feedback) during the first year of VET (t2). Moderation effects additionally examine whether trainees with less favorable learning prerequisites benefit more from high-quality learning conditions. The study yields two primary findings. First, the association between trainees’ learning prerequisites and their professional knowledge decreases over the course of VET. Controlling for initial levels of professional knowledge, only trainees’ reading skills are found to be significantly directly associated with professional knowledge at t3, i.e. the second year of VET (β = 0.209, p <.01), while mathematical skills are shown to be indirectly related to professional knowledge at t3 (via initial knowledge levels). Similarly, the association between trainees’ educational background and professional knowledge at t3 is mediated via basic competencies. Hence, when controlling for initial professional knowledge levels, the role of trainees’ learning prerequisites in subsequent knowledge acquisition during VET is rather limited. Second, the results underline the importance of learning conditions during in-company training periods in VET – especially for trainees with unfavorable learning prerequisites. Controlling for trainees’ learning prerequisites and initial professional knowledge levels, the variety of work assignments during in-company training is significantly positively associated with professional knowledge gains (β = 0.156, p <.05). In addition, the moderation analyses show that trainees’ learning prerequisites (educational background, reading comprehension skills, and mathematical knowledge) moderate the association between all three learning conditions examined and professional knowledge acquisition during VET. This means that trainees with less favorable learning prerequisites benefit more strongly from high-quality learning conditions. Implications for the selection of trainees as well as the design of VET programs are discussed. © The Author(s) 2025.

Clinical training preparedness is defined as the degree of competency of a veterinary student to work and learn at an expected level. The aim of this study was to quantitatively investigate the level of importance and agreement attached to each of 91 clinical training preparedness factors by practice-based clinical supervisors and faculty veterinary academics in three veterinary programmes with remote distributed models of workplace-based clinical training. The data was collected using an online questionnaire from academics and preceptors at the School of Veterinary Medicine, University of Surrey; the College of Veterinary Medicine, University of Arizona; and the College of Veterinary Medicine, Western University of Health Sciences. The participants were requested to rate each factor according to an ordinal five-point impact Likert scale. Impact was defined as how much effect a factor would have on a student being able to learn and participate. There were 115 preceptor and 44 academic responders. There was a high level of agreement between the preceptors and academics within, between and across each of the three schools for the factor rating mean, median and mode values. The impact on learning and engagement were all rated moderate or higher. The outcomes of this quantitative survey provide strong evidence that the student preparedness factors investigated were considered important by the preceptors and the academics. When adopting the preparedness framework within the curriculum it is important that academics, preceptors and students share a common understanding of what preparedness for clinical training means. © 2025 Elsevier Ltd

This study investigates cadet performance segmentation during on-board maritime training using clustering analysis of data from the On Training Monitoring (OTMon) system. Grounded in the competency-based education framework and experiential learning theory, the research aims to identify behavioral patterns and competency levels among 80 maritime cadets over a twelve-month sea-based training program. The OTMon application continuously recorded task completion rates, feedback interactions, sign-on consistency, and report submissions. K-Means clustering and Principal Component Analysis (PCA) revealed three distinct cadet profiles: Cluster 1 (high-performing) with average task completion of 92.4% and feedback frequency of 15.2 times/month; Cluster 2 (administratively consistent) with 88.1% completion but only 6.3 feedback interactions/month; and Cluster 3 (at-risk) with 67.5% completion and 3.8 feedback interactions/month. Linear Discriminant Analysis (LDA) validated the clusters with 98.8% resubstitution accuracy and 97.6% cross-validation accuracy, supported by generalized squared distances above 9.5 between all cluster pairs, indicating strong separation. These findings demonstrate that unsupervised clustering can reliably distinguish high-performing cadets from those needing targeted intervention, enabling data-informed mentoring and adaptive learning strategies in maritime education. The contribution of this study lies in integrating digital monitoring data with both unsupervised and supervised machine learning methods to enhance competency assessment. The novelty is in applying maritime-specific learning analytics for real-time performance segmentation, offering a scalable diagnostic framework for improving supervision quality and supporting individualized cadet development in vocational training contexts. © 2025, Bright Publisher. All rights reserved.

This research investigates the impact of incorporating authentic materials within a classroom intervention on the speaking motivation and anxiety of Indonesian EFL lower secondary school students. Utilizing a quasi-experimental design, the study involved 42 students who were selected based on their availability and willingness to participate. Pre- and post-intervention assessments measured students’ speaking motivation and anxiety levels using the study questionnaires, enabling a comparison of results pre- and post- intervention. Findings indicated an increase in average speaking motivation from 128.6 to 130.7, with a significant rise in students demonstrating high motivation levels. However, the average speaking anxiety score also increased slightly, from 128.6 to 130.7, with only a marginal reduction in the number of students experiencing high speaking anxiety. Although statistical analyses confirmed significant gains in motivation (p < 0.001), the reduction in speaking anxiety was not statistically significant (p > 0.05), suggesting the need for additional affective support. The findings highlight the dual effect of authentic materials: while they enhance intrinsic motivation and engagement, they may also introduce cognitive challenges that sustain anxiety. The study concludes that authentic materials, when embedded in meaningful tasks, can effectively increase motivation but must be complemented with structured anxiety-reduction strategies to fully support students’ English-speaking performance. Future research should explore hybrid instructional models that integrate real-world materials with scaffolded support to address both the cognitive and emotional demands of speaking in EFL contexts. © The Author(s) 2025.

This study examines how university-industry linkages contribute to workforce needs in Ethiopian public universities. It adopts interpretive and pragmatic research paradigms. Using a mixed-methods design, the study collected quantitative data from 644 university instructors and qualitative, data through semi-structured interviews from government officials in the Ministry of Education, Ministry of Industry, Ministry of Innovation and Technology, manufacturing and construction industry experts, and conducted focus group discussions with prospective graduates. The study utilized Structural Equation Modeling (SEM), hypothesis testing, Kruskal–Wallis Test, Chi-Square Test, and Ordinal Logistic Regression, with thematic analysis for qualitative data. The results demonstrate that there are significant correlations between university-industry collaboration and graduate employability, and skills matching with industry needs. The results indicate that strong university-industry collaboration is linked to improved job placement rates and greater relevance of skills, indicating the necessity for curriculum reforms encompassing practical experiences and industry feedback. The paper concludes that strong collaboration between academia and industry is essential to align education programs with the evolving needs of the labor market recommendations for policymakers, industries, and universities include the need to accelerate investment in partnership activities, incorporate experiential learning experiences, and actively involve industry stakeholders in the development of curricula. © The Author(s) 2025.

This study addresses persistent challenges in traditional talent cultivation models, including misalignment with industry demands, outdated instructional content, and limited depth in school-enterprise collaboration. To overcome these issues, the study proposes an innovative approach by integrating Back Propagation Neural Network (BPNN) technology from the field of artificial intelligence to construct a multimodal, integrated teaching quality evaluation system. By aggregating diverse data sources—including classroom performance, online learning behaviors, and hands-on practice videos—the study builds a comprehensive digital representation of the teaching process. An enhanced BPNN model is introduced, optimized by determining the ideal number of hidden nodes to improve evaluation performance. The method employs a hybrid fusion strategy, in which features from different data modalities are extracted independently, processed through dedicated neural networks, and fused at the decision level. This design enhances the model’s adaptability to complex instructional environments and improves predictive accuracy. Empirical validation uses 1,500 samples collected from 18 public courses offered by Nanjing Institute of Industry Technology. The experimental results show that the improved BPNN model significantly outperforms baseline models in both prediction accuracy and convergence speed. Specifically, it achieves a prediction accuracy of 92% for teaching quality rated as “excellent” and 90% for those rated as “very good.” This study provides a novel and effective solution for evaluating teaching quality in vocational education, fostering deeper integration between industry and education, advancing talent development, and supporting broader goals of industrial transformation and upgrading. © The Author(s) 2025.

The integration of gamification in vocational education has gained attention as a strategy to enhance learner engagement, motivation, and skill acquisition. This study presents a systematic literature review (SLR) of 21 empirical studies published between 2016 and 2025, focusing on trends, methodologies, theoretical foundations, and outcomes of gamified learning in Technical and Vocational Education and Training (TVET). Using the PRISMA framework, we applied strict inclusion criteria to identify studies incorporating game elements such as points, badges, leaderboards, avatars, and simulations. The analysis shows that simple mechanics, aligned with behaviourist principles, dominate due to their ease of integration. However, more complex strategies, including role-playing games, 3D simulations, and digital escape rooms, rooted in constructivist and experiential learning theories, are emerging as practical alternatives. Despite positive findings, several methodological weaknesses were identified, such as inconsistent theoretical frameworks, brief study durations, and a lack of implementation details. Gamification consistently improves learner motivation, collaboration, cognitive engagement, and retention, with 75% of studies reporting significant improvements in student outcomes. The study recommends adopting structured instructional design, teacher training, and culturally relevant applications. Future research should explore longitudinal and multisite studies, incorporating learning analytics and AI-driven adaptive gamification for personalized, lifelong learning. By addressing these challenges, gamification can become a scalable tool for modernizing skills-based education. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

This study investigates the future STEM competencies of pre-service science teachers in the Philippines, addressing the gaps in preparing teachers to address the challenges in preparing STEM teachers to meet 21st-century demands. Using a quantitative approach, this study surveyed 444 pre-service science teachers from five state universities in Luzon, Visayas, and Mindanao using convenience sampling. A structured questionnaire, grounded in the Philippine Skills Framework and validated by experts, measured competencies, such as AI integration in science education, critical thinking, and lifelong learning. Data were analyzed using partial least squares structural equation modelling (PLS-SEM). The findings revealed that future competencies, such as creativity and innovation, resilience and adaptability, ethical awareness, and reasoning, are essential for fostering critical thinking, collaboration, and leadership. However, AI Integration in STEM Education is not significant for critical thinking and problem solving. This study recommends training pre-service teachers in future-oriented competencies, technology-enabled pedagogy, and resilience. The scope of this study was limited to self-reported data and a national context. Cross-cultural and longitudinal studies are recommended for broader application. © The Author(s) 2025.

This study examines how student-led game creation can serve as a transformative pedagogical model for integrating the Sustainable Development Goals (SDGs) into vocational education. Drawing on a semester-long, project-based course in a Chinese vocational university, the research investigates how designing educational games shaped students' creativity, collaboration, critical thinking, global awareness, and digital agency. Adopting a qualitative case study approach, we analysed reflection journals, project artifacts, peer evaluations, and group interviews through thematic analysis. Findings show that the process of designing games—rather than consuming them—enabled students to engage deeply with complex sustainability issues, negotiate ethical tensions, and develop systems thinking. Students shifted from passive learners to active creators, expressing a sense of authorship, civic responsibility, and collaborative ownership. The digital learning platform played a critical role in scaffolding this transition by facilitating reflection, co-creation, and iterative feedback. We argue that game creation, when situated within a structured, SDG-focused design task, fosters transversal competencies central to 21st-century vocational learning. The study contributes to emerging debates on design-based pedagogy, global competence, and transformative education in applied learning contexts. © 2025 John Wiley & Sons Ltd.