Search Results for
"learning"

The Programme for International Student Assessment (PISA), a global benchmark for science education, reported stagnation in student achievement worldwide. While some Asian nations excel, their emphasis on cognitive achievement puts high emotional pressure on students. This study investigated the progression of meta-affective skills in science education across the junior high school years by comparing students in the 7th and 9th grades from two cities in West Java, Indonesia. The research employed a developmental study methodology using a cross-sectional design. Two hundred participants were involved, evenly divided between the two grades. Meta-affective traits were assessed using the Meta-Affective Traits for Science Young Learners (MATSYL) questionnaire, comprising 26 statements rated on a five-point Likert scale, measuring two leading indicators: awareness of affect and regulation of affect. Data analysis employed the Independent Samples T-Test, Percentage Change, and Annual Growth Rate. Results revealed significant differences between 7th and 9th grade students across four sub-indicators: awareness of positive affect, awareness of negative affect, expression of positive affect, and expression of negative affect. The 9th-grade students consistently exhibited higher mean scores in all four sub-indicators than their 7th-grade counterparts. These findings suggest a progression in meta-affective growth as students advance through junior high school, particularly in their ability to recognize and express positive and negative emotions in science learning contexts. However, the two groups are not different in expressing and regulating negative affect. This development study provides valuable insights into students' affective development trajectory in science education throughout the junior high school years, thereby enhancing our understanding of meta-affective growth in academic settings. © 2025

Teaching the technology behind microcomputers to beginner students can be challenging due to the fundamental knowledge they need to grasp. Students must understand what happens in the “brain” of microcomputers to comprehend the complexities of the technology. This paper outlines a pragmatic approach that includes a practical implementation of problem-solving techniques for a microcomputer course, focusing on a robotic ground locomotive vehicle as the application. This involved assembling and seamlessly integrating mechanical, electrical, and microcontroller elements, using two software programs: Flowcode and Proteus. Evaluation of the implementation’s efficacy includes quantitative and qualitative measures. Results were evaluated based on achievements throughout the course, and students’ feedback was gathered through a questionnaire at the end of the course. Various aspects were assessed through the questionnaire, including the effect of the practice on students’ understanding, the alignment with the curriculum, and how the practice boosted students’ interest in the field. The analysis showed that the approach had a very positive impact on students, with an average score of 4.16 for application relevance and 4.29 for overall student involvement, based on a Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). Most students recommended continuing the exercise, with the most common rating being 5 (strongly agree). The findings underscore the value of hands-on, application-oriented pedagogies in facilitating effective learning experiences within microcomputer education. © The Author(s) 2025.

Active learning strategies embedded in video content have become increasingly prominent tools for enhancing learners' educational experiences. However, the literature offers varied results concerning their effectiveness. In this research, we conducted a series of meta-analyses to assess the influence of active learning strategies on learners' motivation, cognitive load, and learning performance. On the basis of our criteria, 46 articles were included, encompassing 54 studies comparing active strategies with passive video watching. Most of these studies (74 %) were conducted between 2019 and 2025 and focused primarily on adults (93 %) and STEM disciplines (75 %), with embedded questions being the most common strategy (46 %). The meta-analysis results revealed that active learning strategies had a significant positive effect on learning performance, including retention (k = 24, g = 0.33), comprehension (k = 33, g = 0.28) and transfer (k = 24, g = 0.43), and increased motivation (k = 8, g = 0.15) and cognitive load (k = 19, g = 0.19). Additionally, our moderator analysis revealed that learners’ characteristics (i.e., age) and video attributes (i.e., pace, setting) significantly influenced the outcomes associated with active learning strategies. This research, grounded in various theoretical frameworks, highlights the potential of active learning strategies to increase the efficiency and quality of video-based education. © 2025 Elsevier Ltd

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 problemsolving 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. © 2025, Institute of Advanced Engineering and Science. All rights reserved.

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. © 2025, Institute of Advanced Engineering and Science. All rights reserved.

Despite substantial investments in higher education, many Kazakhstani graduates face challenges in securing employment due to a lack of essential job-related competencies. The predominant discipline-based learning approach in Kazakhstani universities often fails to cultivate autopedagogical competence—a critical skill for applying knowledge in real-world contexts and solving practical problems. This study aims to examine the impact of work-integrated curriculum (WIC) transformation on the development of student autopedagogical competence (SAC). A non-experimental quantitative research design was employed, utilizing survey techniques to collect data from a sample of 180 students in Kazakhstan. The sample was determined through random stratified sampling to ensure representativeness. Data analysis was conducted using structural equation modeling (SEM) to identify relationships between dependent (autopedagogical competence), independent (WIC transformation), and moderating variables. The findings reveal that curriculum transformation has a significant and positive impact on the development of autopedagogical competencies. Students exposed to work-integrated learning (WIL) demonstrate stronger self-directed learning capabilities, enhancing their readiness for workforce integration and lifelong professional development. These insights highlight the necessity of innovative curriculum strategies to bridge the gap between academic learning and practical skill acquisition, offering valuable guidance for educators seeking to improve vocational education outcomes. © 2025, Institute of Advanced Engineering and Science. All rights reserved.

The accelerating pace of industrial transformation necessitates a strategic reconfiguration of higher education curriculum to ensure alignment with dynamic labour market demands. This study introduces a hybrid decision-making framework that integrates Machine learning with Multi-Criteria Decision Making techniques to evaluate and classify the readiness and relevance of academic programs. The methodological core includes the Step-wise Weight Assessment Ratio Analysis, Linguistic q-Rung Orthopair Fuzzy Numbers, and the Multi-Attributive Border Approximation Area Comparison method for criteria weighting, coupled with a classification model based on Support Vector Machine optimized using the Salp Swarm Optimization algorithm. The results demonstrate the framework's efficacy in identifying curriculum gaps and recommending adaptive enhancements, especially for programs categorized as “Needs Improvement” Beyond classification, the system facilitates strategic curriculum planning, fosters pedagogical innovation, and promotes industry-responsive learning pathways. This study highlights the transformative potential of machine learning in higher education, equipping students with the skills required to navigate an increasingly dynamic professional landscape, while offering actionable insights into instructional redesign, competency-based delivery, and industry-informed pedagogy. Future research will explore longitudinal impact assessment and broader stakeholder integration to enhance the framework’s scalability and contextual adaptability. © 2025, Modern Education and Computer Science Press. All rights reserved.

Objective: To develop a model for workplace-based faculty development (WBFD) by identifying key components for its framework that enhance the transfer of teaching skills in the workplace through a meta-synthesis review of relevant qualitative studies in medical education. Methodology: We conducted a meta-synthesis using a meta-ethnographic approach. We searched PubMed, Medline, PsycINFO, SCOPUS and Google Scholar for qualitative studies. Studies published between January 2000 to September 2024 were included. We used a thematic synthesis approach to analyses the data, compare the findings from different studies and identified main themes for making the WBFD model. Results: From the 1,235 studies screened, 10 met the inclusion criteria for this review. Seven core themes emerged as key components of a framework for WBFD model: (1) Peer Coaching, (2) learning by Observing, Doing and Reflecting, (3) Workplace-Based learning, (4) Cognitive Apprenticeship Model, (5) Institutional Support, (6) Feedback and Reflection and (7) Evaluation of Faculty Development Programs. Peer coaching facilitated the faculty development through reflection and feedback, while the Cognitive Apprenticeship Model enhanced the learning transfer and provided scaffolding mechanisms that supported faculty in refining their teaching methodologies with institutional support. Conclusions: This meta-synthesis highlighted the significance of the WBFD model by integrating peer coaching with feedback, reflective practice, cognitive apprenticeship and institutional support with evaluation. The WBFD model promotes the sustainable learning transfer of teaching skills at the workplace. Future studies should examine how well this model works through experimental research on faculty development. © 2025, Professional Medical Publications. All rights reserved.

Modern technologies are transforming occupational health and safety training by enhancing education, innovation, fire prevention, and promoting sustainability conditions in various sectors of industries. Digital tools such as virtual reality, artificial intelligence, and interactive simulations improve learning efficiency, engagement, and risk awareness. By integrating the technologies, companies can better prepare employees for hazardous situations, reduce workplace accidents, and ensure compliance with safety regulations. Fire courses on fire prevention and control are an essential element in health and safety trainings, and a crucial aspect of safety management. In any business, employees should be prepared for emergency situations, including fires by using modern tools like artificial intelligence. This article aimed to assess the implementation of modern technologies in Polish occupational health and safety training across various industrial sectors. Additionally, this research considered variations in training program development based on company size and financial capacity, highlighting the importance of integrating training, education, and innovative technologies into the company’s overall development strategy. The relationships between safety training programs, education, and innovation in 597 industrial companies were evaluated. The research findings suggest that integrating innovative technologies into training can improve working conditions in a more sustainable way and enhance the market competitiveness of enterprises. © 2025 by the authors.

Educational institutions are facing a crisis characterized by the need to address diverse learning styles and vocational aspirations, exacerbated by ongoing financial pressures. To navigate these challenges effectively, there is an urgent need to innovate educational practices and learning environments, ensuring they are adaptable and responsive to the evolving needs of students and the workforce. The adoption of the Industry 5.0 framework offers a promising solution, providing a holistic approach that emphasizes the integration of human creativity and advanced technologies to transform educational institutions into resilient, human-centric, and sustainable learning environments. In this context, this article presents a transdisciplinary methodology that integrates Asset Management (AM) with Social Innovation (SI) through Design Thinking (DT) to co-design Educational Facilities 5.0 with stakeholders. The application of the proposed approach in an AgroLab case study—a food and agricultural laboratory—demonstrates how the methodology enables the definition of an Educational Facility 5.0 and generates AM Design Knowledge to support informed decision-making in the subsequent design, implementation, and operation phases. Following DT principles—where knowledge emerges through iterative experimentation and insights from practical applications—this article also discusses the role of SI and DT in AM, the role of Large Language Models in convergent processes, and a vision for Educational Facilities 5.0. © 2025 by the authors.