Search Results for
"learning"

Lifelong learning is essential for translators and interpreters to succeed in the fastpaced translation industry. It addresses professional issues such as machine translation, time constraints, and the need for ongoing professional growth. The chapter promotes machine translation and post-editing in translation programs, human translation's importance, and translator self-sufficiency. Professional development options like conferences, workshops, and webinars improve skills and flexibility. The chapter discusses how language service providers, translation companies, and translators promote ongoing learning. Case studies of successful lifetime learning approaches demonstrate their benefits. The chapter concludes that translators must continue learning to improve their language skills, translation skills, and industry knowledge to ensure their long-term career success. © 2025 by IGI Global Scientific Publishing. All rights reserved.

The exploration of signature pedagogies in selected arts and design disciplines has identified distinctive traits and concepts that are important to professional education in each field. This chapter discusses nine salient themes that characterise these pedagogies: the artist's voice, style and identity; interpersonal interaction and collaboration; reflection and reflexivity; technology-enhanced teaching and learning; linking, connecting and relating through synthesis and coherence; creativity; truthfulness, authenticity and trust; creative collaboration with other artists and designers; and the interplay between surface structure and deep structure. Based on these themes and the chapter topics, nine pedagogical issues are proposed for future exploration and development in the signature pedagogy framework. These are pedagogies of pioneers in the profession, generative apprenticeship, reflexivity, transition, artistic tradition and heritage, truth, evocative ambiguity, creative uncertainty and designerly formation. Collectively, these pedagogical issues inform three defining characteristics of signature pedagogies: first, what experts in the field do; second, how knowledge within the discipline is analysed, critiqued, accepted or refuted; and third, what constitutes the threshold concepts that shape the discipline. © The Author(s) 2025. All rights reserved.

Generative apprenticeship is a higher-order form of apprenticeship that extends beyond foundational skills and knowledge acquired through traditional apprenticeship models, creating a platform for both master and apprentice to engage in complex inquiry and generate new forms of learning. It is generative in the sense that the learning pivots towards innovation and productive change. While traditional apprenticeship focusses on a one-on-one relationship between master and apprentice in order to excel in the mimetic replication of best practice, generative apprenticeship starts with a question or trigger that challenges students to make their own decision. Pedagogies of generative apprenticeship recognise that expertise is not held solely by the master but can also emerge from the apprentice's unique experiences and insights. This model of apprenticeship fosters creativity and mutual learning exchanges, enabling students to draw from the experts' knowledge and experience while allowing space for a dialectical tension between expert and student ideas that leads to new inventions or artistic imagination. © The Author(s) 2025. All rights reserved.

I n today's world, characterized by the dominance of digital technologies, vocational education plays a pivotal role in driving economic growth and development. Nevertheless, it faces significant challenges in adapting to the rapidly evolving demands of modern industries. This study explores the role of Artificial Intelligence (AI) in reshaping vocational education curricula. A total of 73 articles were initially identified from the Web of Science database using specific queries related to AI, vocational education, and curriculum design. After applying inclusion and exclusion criteria, 27 articles published between 2020 and 2024 were selected for in-depth analysis. The systematic review employs the PRISMA methodology to analyze 73 articles, ultimately focusing on 27 relevant studies published between 2020 and 2024. The systematic review in the study follows the PRISMA methodology, ensuring a rigorous and transparent process. Key themes include the integration of AI tools for data-driven insights, personalized learning environments, curriculum design emphasizing AI and digital skills. The study underscores the importance of AI in enhancing teaching practices, promoting inclusiveness, and preparing students for AI-focused careers. It also emphasizes the necessity of AI training for educators, equitable access to technology, and the development of ethical frameworks to guide AI integration in education. The findings emphasize that personalized learning supported by AI enhances students' skill acquisition and aligns educational outcomes with workforce demands. Legal and ethical dimensions of AI, particularly in vocational education, need to be addressed to ensure responsible usage and equitable implementation. © 2025, Publishing House of the Romanian Academy. All rights reserved.

This study is based on preliminary studies that identified the problem of suboptimal learning quality. The objective of the study is to develop a digital e-module within the teaching factory (TEFA) (TEFA)-T learning model as an effort to improve the academic achievements of automotive vocational students, ensuring the module is valid, practical, and effective. The study method is research and development (R&D) using the Instructional Development Institute (IDI) model development procedure, which consists of three stages: define, develop, and evaluate. The results of this study generally produce a comprehensive digital learning e-module design consisting of a cover, preface, table of contents, learning structure, learning patterns, e-module position map in learning, glossary, learning introduction, learning activities, evaluation, and closing. The TEFA-T learning e-module is statistically validated and practical. The average Aiken’s V value obtained is 0.967, indicating that the digital e-module content is in the valid category. The TEFA-T learning e-module is considered very practical, as shown by the average practicality assessment scores of 92.20% from lecturers and 90.60% from students, both in the “Very Practical” category. In conclusion, after implementing the TEFA-T learning e-module, students can build knowledge inductively and deductively, as well as gain learning experiences through one-way interaction, personal interaction, and effective learning interaction, significantly improving student academic achievement (Sig. 2-tailed value is less than 0.05). © 2025 by the authors of this article. Publis.

learning is a multimodal process, and learning analytics (LA) researchers can readily access rich learning process data from multiple modalities, including audio-video recordings or transcripts of in-person interactions; logfiles and messages from online activities; and biometric measurements such as eye-tracking, movement, and galvanic skin response. While many techniques are used in LA to model different types of learning process data—most of which are state-dependent (or state-space) approaches that model a learning process at any given time as a function of the preceding events—constructing multimodal models has so far relied on fusion of different data streams, which converts multimodal data into a unimodal format. This creates a number of problems for multimodal modelling, the most important of which is that it treats different data modalities as equivalent. That is, existing state-dependent models of fused data cannot easily account for (a) events that may have different impacts on future events based on what those future events are and the context in which they are occurring; (b) how events may influence some groups of learners differently; and (c) which events are visible (and thus potentially impactful) to which students. In this paper, we propose transmodal analysis (TMA), a mathematical and computational framework designed to address these challenges. TMA is not a data analysis method but rather an approach to modelling that can augment existing state-dependent models of learning processes to account for multimodal data without data fusion. We present a conceptual and methodological description of TMA, and we include an appendix with a detailed worked example as a proof of concept. While this approach is in the early stages of development, it has the potential to significantly improve the ease, efficiency, and fairness of multimodal analyses of learning processes. © 2025, Society for learning Analytics Research (SOLAR). All rights reserved.

Vocational high schools encounter substantial challenges in preparing graduates who can meet the demands of the 21st century. This study developed and assessed an innovative mobile learning model based on augmented reality (ARMOL) to enhance vocational students’ competencies, using both the ADDIE model for instructional design and the SEM-PLS method to evaluate effectiveness. The urgency of this research stems from the disparity between vocational graduates’ skills and industry needs, coupled with augmented reality’s (AR) potential to offer a more immersive and interactive learning experience. By employing the ADDIE model, the research successfully created a valid, practical, and effective AR-based mobile learning model. This model enhances students’ cognitive, affective, and psychomotor competencies and fosters 21st-century skills such as critical thinking, creativity, collaboration, and communication. The SEM-PLS analysis revealed significant improvements in creativity and critical thinking, while effects on communication and collaboration were less pronounced. These findings suggest that while the ARMOL model effectively enhances certain competencies, further refinement is needed to fully address all 21st-century skills. This innovative learning model offers a promising solution for elevating the quality of vocational education and preparing graduates for global competition. © 2025 by the authors of this article.

The study aimed to reveal the consideration degree of the Darsak Educational Platform (DEP) for the International Design Standards (IDS) from teachers’ perspectives in Jordan. In addition, it aimed to investigate the relationship between the consideration degree and the variables of teacher’s gender, specialization, and classes they teach. To achieve the study objectives, the analytical descriptive method was used, and the study instrument (questionnaire) was developed based on reviewing many IDS, such as QM, SCORM, INACOL, and IEEE-LOM. The questionnaire was distributed after checking its validity and reliability. The study sample con-sisted of 352 teachers from public schools of the Kasbah District in Amman during the first semester of the school year 2022/2023. The sample study was selected based on the strati-fied random method. The results showed that the consideration degree of DEP for IDS from teachers’ perspectives in Jordan was moderate. Further, findings indicated that there were no statistically significant differences in the consideration degree of DEP for IDS from teachers’ perspectives attributable to the variables of teacher’s gender, specialisation, and classes they teach. In light of these results, the researchers recommended the need for redesigning and developing DEP in accordance with IDS for the quality of international e-courses. In addition, they suggested periodically reviewing and evaluating the DEP platform every three years as a maximum, as well as conducting further research on the evaluation of the inclusivity and resource availability in DEP as one of the virtual learning environments. These findings imply the need for enhancements in the platform’s design to better align with IDS, thereby improving usability, accessibility, and overall effectiveness. Additionally, the lack of differences across demographic variables underscores the importance of adopting universally effective design practices to ensure equitable support for all educators, regardless of their backgrounds or teaching contexts. © 2025 by the authors of this article. Published under CC-BY.

This study aims to develop a digital authentic assessment (DAA) model based on competencybased learning (CBL) in the field work practice program at vocational high schools. The background of this study is the need to improve the quality of assessment in vocational education, which often still uses less effective, traditional methods. The urgency of this study lies in the need for assessments that are more relevant to the world of work so that Vocational High school graduates can be better prepared to face challenges in the industry. The methods used in this study include the development of the ADDIE model, validation by experts, and implementation of the assessment model in several vocational high schools, followed by evaluation through surveys and interviews. The evaluation showed that the model successfully increased student engagement and competency achievement, with high average scores in ease of use, material relevance, and assessment quality. The implications of this study suggest that the DAA model can contribute to innovation in vocational education assessment in Indonesia and improve the readiness of vocational high school graduates in the job market, although challenges related to technology access need to be addressed to ensure the sustainability of implementation. © 2025 by the authors of this article.

Early science learning has the potential to enhance children's social interaction development, but a lack of resources in schools requires well-structured activities and a supportive learning environment. In a project aimed at helping children develop an interest in science education from an early age, this describes a Project-Based, Technology-Enhanced Science Module (PTBLM) for preschool children, fostering their interest in science through collaborative activities. This study employs a multi-method design, utilising the ADDIE module based on five phases. In the first phase, the needs analysis phase, nine experienced early childhood education educators were interviewed, and thematic analysis revealed the necessity of developing a science learning module for preschool children. During the second and third phases, the design and development phases, the module content was validated by six different experts, with the Content Validity Index (CVI) indicating unanimous agreement on the module’s design and development (k = 1). In the fourth phase, the implementation phase, an 8-week intervention was conducted with 25 preschool children, and the mean scores showed a significant increase, with post-test scores being higher (m = 66.0) than pre-test scores (m = 33.00). In the final evaluation phase, an educator was interviewed, and content analysis indicated that the learning module was highly positive in enhancing children's social interaction development through engaging science projects. In summary, this learning module provides educators with more opportunities and resources to enhance science education in preschool, thereby expanding children's exposure to the world of science. © 2025, Firtina Academy. All rights reserved.