新质生产力背景下“数智工匠”能力标准与培养体系研究

with the rapid development of new quality productivity, digital and intelligent technology is changing all walks of life at an unprecedented speed, and the field of higher education is no exception. As the main position of training skilled talents, higher vocational colleges are facing unprecedented opportunities for change. With the acceleration of digital transformation, the“One-stop” construction of students' intelligent community in digital intelligence-enabled higher vocational education has become the key path to promote the development of high-quality education, the digital transformation has become an inexorable trend, which is bound to show greater achievements in training“Skilled craftsmen” who can match the new quality productivity. The purpose of this paper is to probe into the“One-stop” intelligent community of students in higher vocational education by means of mathematical and intellectual technology from the perspective of new qualitative productivity, we should promote the modernization of educational governance system, the precision of personnel training and the Individualization of educational services.

Driven by technological innovation, new quality productive forces place higher demands on the overall competence of the labor force, thereby assigning new contemporary connotations and missions to innovation and entrepreneurship education in higher vocational colleges. This paper examines the practical challenges confronted by such education within this emerging context. The findings indicate several prominent issues: a misalignment between curriculum design and industrial needs, insufficient innovation and entrepreneurship capabilities among faculty, inadequate depth in practical training platforms and industry-education integration, and a limited guiding function of existing evaluation mechanisms. To address these challenges, this paper proposes a set of systematic optimization strategies: reconstructing the curriculum system based on the integrated development of science–education–industry; cultivating “dual-qualified” faculty who possess both theoretical knowledge and practical experience; building collaborative practical training platforms that involve government, industry, academia, research, and application sectors; and establishing diversified evaluation mechanisms that emphasize innovative outcomes. The study concludes that higher vocational colleges must actively align with the development requirements of new quality productive forces, deepen the reform of innovation and entrepreneurship education, and cultivate high-quality technical and skilled talents who demonstrate innovative thinking, entrepreneurial awareness, and creative problem-solving capabilities.

Amid the global trend of the digital-intelligent economy and industrial transformation, skill-oriented universities have emerged as a crucial force driving urban innovation and development. With the evolution of new-generation information technologies, strategic emerging industries, such as artificial intelligence, integrated circuits, and intelligent connected vehicles, are witnessing exponential growth in their demand for highly skilled technical talent. However, traditional models of skills training continue to face deep-rooted challenges, including misalignment between academic disciplines and industry needs, fragmented university-enterprise collaboration in talent development, and insufficient integration of digital and intelligent technologies. By examining the development trajectory, classification, and existing issues of skill-oriented universities, this study provides a systematic analysis of their transformation and upgrading, with the aim of offering theoretical insights and practical references for cultivating world-class talent in technical and vocational fields.

The construction of workers in the construction industry in the new era is the key link to promoting the transformation from “migrant workers” to “industrial workers” and promoting the transformation of industrial workers from “workers” to “craftsmen”. In view of the present situation and problems of industrial workers ‘ skill quality improvement, under the background of high-level specialty group construction, Guangzhou City Construction College explored a set of ‘ double representative ‘ vocational education modes. Professional groups set up a special training team, to explore vocational education more closely with the construction industry workers’ professional practice, for the societyto cultivate professional skills, and skilled, excellent quality of construction industry worker’s practice research. Through the analysis of the questionnaire results of 312 construction workers ‘ training visits, the ways and methods of industrial workers ‘ team reform are put forward from the perspective of vocational training. It is suggested that the training of industrial workers in the new era needs the coordination of the government, industry, enterprises, schools, and individuals. The training process can adopt the ‘ double belt table ‘ mode, and pay attention to the improvement of workers ‘ practical skills, and the online and offline training methods are the most appropriate.

Abstract The Luban Workshop represents a quintessential model of China’s international vocational education cooperation. From the perspective of structuration theory, this study conducts an in-depth analysis of the key elements underpinning the high-quality development of Luban Workshops globally and explores effective pathways for international vocational education collaboration through this initiative. The findings hold significant implications for strengthening China’s proactive stance in opening-up and advancing higher-quality global engagement. The research identifies three critical success factors for Luban Workshop to be a distinguished international vocational education brand: institutional development, resource allocation, and multi-actor participation. Regarding institutional frameworks, Luban Workshops have established comprehensive formal systems alongside effective informal mechanisms. In terms of resource development, human capital, information networks, cultural assets, and technological resources collectively form the essential foundation for their high-quality operation. The ecosystem features diverse stakeholders, including sovereign states, administrative bodies, coordination agencies, participating institutions, multinational and local enterprises, and civil society actors who constitute the core collaborative network driving the workshops’ development. These elements collectively represent actionable pathways for cultivating globally recognized vocational education partnerships.

The rapid development of technologies and their application in all branches of the economy calls for digitalization of education as a prerequisite of improving the quality of vocational training. Digital technologies in their turn allow to diversify the mode of training according to the needs arising under various circumstances. In some countries like Australia and Canada, online and blended learning are the only possibly form of training due to learners’ remotedness to schools. But as recent experience shows, introduction of online education was the only way out to sustain it under the conditions of the COVID-19 and now by the wartime and absence of access to educational facilities. In this was, the necessity of digitalization of education is constantly growing together with its increasing range of applicability. Now all production processes and processes of the service sector are under the influence of digital technologies, because modern machines are operated by computers. Modern military equipment is also digitally based and operated. Thus, working in modern industries and services requires a high level of digital literacy, which presents a challenge for the system of vocational education. Under modern conditions, irrespective of their positive or negative origin, vocational schools (VS) should be ready to train specialists for various spheres of industry capable of working with constantly changing digital technologies. This fact puts forwards certain requirements to digital literacy of both students and teachers, who have to cooperate through digital devices and software to attain the set educational goals. All these circumstances require the equal level of digital literacy of both teachers and students to provide educational institutions with the latest material base and digital resources.

The digital transformation of the working world has been bringing profound impacts on German vocational education and training (VET). This study analyzes the challenges that German VET is experiencing in the context of digitalization as well as the strategies to overcome these challenges. Based on the concept of sustainable cooperation between vocational schools and companies, this study proposed a theoretical framework for preserving the sustainability of VET in the digital era from three dimensions: the capability of industrial service, attractiveness, and adaptability. Meanwhile, through the content analysis method applied to the study of official research and statistical reports, policy documents, journal articles, etc., three key challenges for German VET are found: the insufficient service capacity of German VET for industrial digitalization, the decreasing attractiveness of VET, and the low level of application of digital competencies. German federal agencies have developed multiple strategies in response, including (1) strengthening the capability of training digital talents through the modernization of the training regulations and framework curricula in 2021; (2) reshaping VET as a more promising track for individuals via information support and expanding development pathways; (3) enhancing the willingness to participate in and the capacity to provide vocational training of companies through financial measures; (4) promoting the digital transformation of VET through the financial support of projects and development of practical assistance.

Abstract Existing research on digitalization and Industry 4.0 consistently shows a significant and lasting impact on social coexistence, economic development and work design. It is therefore becoming a central issue to analyze the technological, economic, social and work-related consequences in more detail in order to gain a deeper insight into the requirements to be expected. In this context, TVET (Technical Vocational Education and Training) becomes highly relevant to train skilled workers and make them fit for the changing industry. Answers should indicate which occupations and competences are relevant to the mentioned workers. The knowledge identified via empirical work will be used to draw conclusions about the effects of the changes of work on vocational training and leads to proposals for a future-proof and practice-oriented design of occupations in industry. The core of the qualitative and quantitative empirical survey was based on four research questions. For the study itself, occupational scientific instruments were used for surveys on the shop floor and qualitative interviews were conducted with the selected companies.

Developments of Industry 4.0 require a set of multidisciplinary digital competencies for future vocational teachers, consisting of specific knowledge, motivational aspects, cognitive abilities and skills to fulfill the demands of digitally interconnected work situations. The competence model that is adapted from future work scenarios of vocational apprentices in Industry 4.0 includes attitudes towards digitization and handling of digital devices, information literacy, application of digital security standards, virtual collaboration, digital problem solving as well as a demonstration of reflective judgment of one’s actions in an interconnected and digital environment. Structural equation modeling was used to assess N = 205 pre-service vocational teachers between 18 and 35 years of age. The findings indicate the relationship of the proposed dimensions, measured through external- and self-assessments validate the proposed structure of the multidisciplinary digital competencies. However, attitude towards digitization can predict the self-efficacy of the relevant Multidisciplinary Digital Competencies but not the actual achievement in an external assessed scenario. Nevertheless, this study confirms that self-assessed multidisciplinary digital competencies can predict achievement in an external and qualitative-assessed competence test. Fit indices show an acceptable model conception, the reliability and construct validity of the model were confirmed. Findings suggest that the attitude towards digitization and the application of digital security standards are important, whereas the ability to solve digital problems seems to have a weak relation to the general multidisciplinary digital competencies of pre-service vocational teachers.

The active development of the digital economy in all countries of the world presupposes the availability of specific digital competencies among employees. The purpose of the study is the formation and development of digital competences, which the digital society requires from the population. The research methodology involves the use of various methods and techniques, including: the historical method - for researching the development of digital competencies; graphic method - for a schematic representation of research results; comparative method - for comparing competencies in different countries; methods of analysis and synthesis - to create the Levels of digital competence proficiency scale and others. Researched the classification that exists in the EU contains three main categories of DSC for students / citizens: digital competence; special digital skills; digital skills for ICT professionals. The main competence areas of DigComp have been systematized. A Model of formation and actualization of needs for the development of digital competencies has been developed, which includes the following components: needs, conditions, motives and incentives, voluntary and coercive measures aimed at the formation and actualization of these needs. The main strategic directions for the development of digital competences in the conditions of digitalization of the economy have been developed. A general scheme for assessing the impact of digitalization of the economy on the demand and supply of jobs is proposed. The methodological approaches can help find answers to special and specific questions, in particular about the impact of digitalization of the economy on competencies and their combinations, the emergence of new professions, understand the expectations of the labor market by studying its demand for professional skills rather than skills listed in standard job descriptions, as well as develop substantiated proposals for improving labor market and field policies in Education.

… digitalisation has become a defining feature of education worldwide. This is particularly critical in Vocational Education and Training … is the relevant competence framework for educators…

Digital skills are thought to be a key competence of the twenty-first century. With the rapid growth of internet and communication tool (ICT) usage among both students and teachers, cooperative (co-op) education programmes, like other educational institutions, face the challenge of integrating and supporting digital skill development. However, little is known about how these skills are developed prior to entering cooperative education programmes. Against this background, a sample of 893 freshers, ranging from vocational students to co-op students, were tested according to their digital skills. The analysis shows that co-op students have a higher level of competence than vocational students. In addition, we found that in our sample social background has no impact on digital competences. The results are discussed and classified in the context of the current state of research.

… analysis of vocational education digitalization policies across … It utilizes a multi-dimensional framework to assess policy … and aligning vocational education with industry requirements is …

Modern society is characterized by a significant impact of information technologies on all spheres of human life. In a special way, the processes of digital transformation affect educational institutions, including vocational (vocational and technical) ones. Now vocational (vocational and technical) education occupies an important place in the sector of the country's economy, prioritizing effective training of highly qualified labourers in the state policy of Ukraine. Nowadays, the professional activity of labourers incorporates an intellectual component related to working with electronic devices, artificial intelligence systems, etc. Monitoring of the labor market shows that a skilled worker of the XXI century should be able to think critically, process information analytically, and work with mechatronics systems. The analysis of the European experience in training qualified workers reflects a certain lag of domestic institutions in terms of digital supply. At the same time, the level of teachers' digital competence at vocational (vocational and technical) education institutions needs improving. As a result, the issues of digital transformation for educational institutions are urgent and topical. Provision of modern digital equipment, formation and development of digital competence of all participants in the educational space are becoming the main tasks of teaching stuff in the current conditions. In a special way, the tasks set become relevant during the period of quarantine restrictions, when educational institutions mainly work on distance and mixed forms of teaching.

… change regulatory requirements for the level of professional training and the quality of professional competencies of specialists who implement and accompany the educational process. …

In the face of the COVID-19 pandemic, education in Indonesia has shifted from face-to-face learning to online learning via the internet and digital technology. Therefore, digital literacy is a skill needed by vocational students and teachers today. This study aimed to identify and analyze digital literacy competency indicators to improve the quality of learning in high vocational education. This research employed a systematic review method, especially a qualitative meta-ethnographic approach, by reviewing various studies related to digital literacy competencies from various journal articles and conferences to then carry out the synthesis process. Meta-ethnography as part of the systematic review method integrates data across studies to obtain new theories and concepts with a deeper and more thorough understanding. The results showed four competency factors and 28 indicators to improve digital literacy competence. This research can be the basis of creating a digital literacy assessment model for high vocational education in Indonesia.

This study examines strategic approaches to advancing vocational education and skills development in response to the evolving demands of the modern workforce. The primary objective is to analyze how vocational education systems can be restructured to enhance graduates’ employability, adaptability, and alignment with industry needs in an era characterized by rapid technological transformation and globalization. The research employs a qualitative field approach, drawing on primary data collected through interviews, observations, and document analysis within vocational education settings. These data are supported by relevant peer-reviewed journal articles, policy reports, and institutional frameworks to enrich contextual understanding. The collected data were critically examined to capture diverse perspectives on vocational education practices across different contexts. Data were analyzed through thematic analysis to identify key patterns, challenges, and innovations in vocational education. The analytical framework integrates perspectives on competency-based education, industry collaboration, and lifelong learning paradigms, grounded in empirical findings from the field. The findings reveal that effective vocational education systems are characterized by strong linkages between educational institutions and industry, the integration of digital and soft skills into curricula, and the adoption of flexible, competency-based training models. Additionally, the study highlights the importance of continuous upskilling and reskilling mechanisms to address skill gaps caused by technological disruption. However, challenges persist, including institutional rigidity, limited industry engagement, and disparities in access to quality training resources. This study contributes to the academic discourse by proposing a conceptual model that emphasizes the synergy between curriculum innovation, stakeholder collaboration, and adaptive learning ecosystems. It offers practical implications for policymakers, educators, and industry leaders in designing responsive, future-oriented, and inclusive vocational education systems. Furthermore, the research underscores the need for policy integration and cross-sectoral partnerships to ensure sustainable workforce development. Future research is recommended to empirically validate the proposed model and assess its applicability across diverse socio-economic contexts.

The article analyzes the factors caused by the threat of spreading the coronavirus infection COVID-19 and introducing the martial law in Ukraine which affect the state of the vocational education. Taking into account the modern challenges and problems based on the analisys of the legislation the main directions of the vocational education development were determined. In particular, improving qualifications and professional development of teachers’ staff, enriching material and technical base of the vocational education institutions and educational programmes as well. Trendwatching of the modern labour market made it possible to single out its main trends: a change in the structure of employment, primarily an increase in the variability of employment; lifelong learning; automation and robotics; age diversity; forming hard skills, soft skills, digital skills; multipotentiality, background, interdisciplinarity. In order to solve the urgent problems and ensure the reorientation of the vocational training of qualified workers and improving its quality, special measures were suggested, including participating in the projects financed from the EU funds; developing educational modules and special courses for promoting lifelong professional development of teachers, improving educational programmes to enable improvement of the material and technical base of the vocational education institutions and professional development of teachers.

… systems [5, 6, 14, 15, 16] and find out what competencies become … their professional tasks at the age of digitalization (Table 1). … Vocational education will face the situation of rapid …

One of the needs for competence in the world of work in the 21st century and the era of the industrial revolution 4.0. is competence in using digital technology. Vocational education is required to provide digital competencies to students through their learning. The maturity level of digital technology competence is divided into five levels, namely caring, literacy, capability, creativity, and being critical of using digital technology. This study aims to analyze the maturity level of vocational education teachers and students in mastering digital technology in learning. The survey research uses a design developed by Rea & Parker. A total of 233 vocational high school students were included as the research sample. Data were collected using a questionnaire technique with a four Likert scale questionnaire instrument. The collected data were analyzed using descriptive statistics and inferential statistics t test. The results show that the maturity level of digital technology for teachers and students is sequential, starting from awareness, literacy, capability, creativity, and being critical of using digital technology. All levels of maturity are included in the low category. Various trainings and learning innovations that are relevant to the relevance of digital technology mastery competencies are very important to be improved.

High-Ievel specialised training has specific requirements such as facility transformation and upgrading, social service improvements and optimisation of dedicated teaching resources. On the basis of existing advanced industrial clusters in Taizhou and forecasts for professional growth and industrial supply chain needs, Taizhou Vocational and Technical College has formed a specialised group for intelligent manufacturing technologies to meet future demand. Various innovations have been made in aspects of specialised construction, exploration of international paradigms, local talent cultivation, professional teaching reform, recruitment of high-level teaching staff, and integration of production and education. These innovations provide vocational schools with experience to learn from and practical cases to refer to for improving high-level specialised manufacturing education.

In order to satisfy the demand of high-level technical personnel with Craftsman Spirit against the backdrop of Intelligent Manufacturing, this paper studies the construction of craftsman spirit cultivation scheme for students major in mechanical and electrical profession. It takes the Craftsman Spirit as the orientation to optimize the training objectives of mechanical and electrical specialty. Based on the spirit, carry out the talent training model with school-enterprise integration. Finally, it puts forward four talent cultivation systems integrating craftsman spirit, that is, subject teaching system, practice teaching system, culture and professional quality system and innovation and entrepreneurship system. In a word, this paper constructs originally a training mode for mechanical and electrical talents with Craftsman Spirit. Students cultivated by the training mode are more persistent and meticulous in treating technical skills than previous students. Practice has proved that the program has achieved the goal of cultivating high level technical talents who are major in mechanical and electrical engineering and are keep improving and seeking technological innovations. Keywords—Craftsman Spirit; mechanical and electrical profession; cultivation scheme

The history of rise and fall of ancient Chinese craftsmen is briefly reviewed, and it is point out that craftsmanship can’t be developed isolated from the skill cultivate of craftsman. Based on an idea that applies artificial intelligence scientific technology to craftsmen skill modeling, steps and movements for vocational education are presented. To increase the efficiency of vocational skill cultivating we recommend that not only top craftsmen are engaged as guidance teachers, but also modern artificial intelligence engineers are involved in the understanding and representation of craftsman skills which can only be sensed and not explained historically. As a result, the process of high level vocational skill cultivating becomes more and more achievable. Keywords—Spirit of the Craftsman; Scientific technology; Artifical Inteligence; Professional skills modelling; Vocational Education

… This article mainly studies the cultivation strategy of college students’ craftsman spirit in the … The cultivation of craftsman spirit meets the needs of colleges and universities to cultivate …

… vocational education and train more high-quality craftsmen. … It is a smart terminal device based on mobile Internet with … vocational education teacher training and training system, open …

… training environments stood at merely 8.3%, contrasting sharply with the 27.9% penetration rate of smart … evolution of technical standards and the talent training system. At present, the …

At present, the new quality productive forces enable China to vigorously develop the digital economy and strive to achieve Chinese-style modernization. Therefore, this requires high-quality technical and skilled personnel as an important support.This paper analyzes the characteristics, constituent elements of the digital economy and the adaptability of vocational talents, reveals the eight dimensions of the craftsman spirit of vocational students in the new era, proposes the enabling cycle mode of “internalized in the heart and consolidated in the practice” of the craftsman spirit, and deepens the fit degree between the quality of artisan talent training in vocational colleges and industrial development, and the supply balance between students’ skill literacy and vocational competitiveness. It has enhanced students’ sense of gain and vocational adaptability, improved vocational colleges’ social service ability and enterprise satisfaction, enriched vocational students’ craftsman spirit connotation and cultivation path research in the digital economy era, and expanded the theoretical cognition and practical cultivation system of vocational education craftsman spirit cultivation.

… In the future research, we will continue to deepen the indepth discussion and analysis of the training system, practice system, and assessment system of three subsystems of SMTE …

… for intelligent manufacturing have shifted from mechanical operation to intelligent system … For instance, the School of Intelligent Manufacturing has introduced digital production lines …

… , in the traditional curriculum of smart manufacturing big data … However, the digital twin and production management cloud … and fault prediction of the production line. Consequently, their …

Against the backdrop of industrial transformation and upgrading in Guangdong Province, and to address technological unemployment brought by artificial intelligence while meeting the talent demands for future industrial development, this study utilizes official data from the Guangdong Provincial Department of Human Resources and Social Security. By applying the Grey GM(1,1) model, it forecasts the demand for high-skilled talents in Guangdong Province from 2025 to 2030. The results show that the constructed model has high accuracy and predict a “significant surge” in the total demand for high-skilled talents over the next six years, necessitating corresponding adjustments in cultivation strategies.

Based on the fact that information technology will continue to be used in manufacturing projects and promote the development of Intelligent Manufacturing Engineering, this paper studies the application of information technology in intelligent manufacturing education. With the transformation of many enterprises towards intelligent manufacturing, the informatization of manufacturing industry, the virtualization of physical resources and the intellectualization of production process are developing continuously. More and more enterprises pay attention to the informatization and intellectualization of manufacturing industry. This paper takes the intelligent manufacturing productive training base as the carrier of deepening the integration of production and education, and combines the education supply and industrial demand of Intelligent Manufacturing Talents in China to study the cultivation and research of talents in higher vocational colleges, so as to serve the regional economic development.

… development industries. There is a gap of 3 million people in the posts of industrial robot maintenance, intelligent manufacturing … high-skilled talents, and clarify that high-skilled talents …

… of Things [5] and Smart Manufacturing [6]. Although different … surveyed by Global Talent Management and Rewards, 60% of … of talent training plans such as the “National High-Skilled …

… like manufacturing , utilities and transportation decrease due to increased automation and digitalization of work processes, high-skilled workers in these industries need to develop …

… skilled talents, improve the evaluation model of high-skilled personnel, and … production problems and complete work tasks”. Thus it can be seen that the four aspects of virtue, intelligence…

Genetic algorithm has powerful global search ability, which can be used to optimize neural network to improve algorithm performance. The genetic algorithm simulates the process of biological evolution, and goes through continuous reproduction and evolution from generation to generation to obtain the individual with the highest fitness. The demand for multi-disciplinary and inter-professional compound technical and skilled talents in intelligent manufacturing, intelligent control, multi-axis CNC machine tools, industrial robots, intelligent management and control platforms, cloud computing and big data is increasing day by day. Higher requirements are put forward for colleges and universities, especially vocational colleges and universities that focus on cultivating professional skills. It is necessary to strengthen the integration of production and education, school-enterprise cooperation, deepen the realization of a high degree of integration with relevant intelligent manufacturing enterprises, and complete the construction of intelligent manufacturing training bases with the help of enterprises. With the in-depth development of my country's industrial transformation and upgrading, the industry's demand for high-skilled talents has become more and more urgent, and the important position and role of vocational education has become more and more prominent. Through the application and practice of the training base, it is expected to be strengthened and supplemented in the aspects of teaching system, teaching practice resources, teachers'applied technical ability, and talent evaluation. However, the traditional genetic algorithm itself also has some problems such as local optimum and premature. To overcome the premature phenomenon and improve the local search ability, the genetic algorithm is improved, and then the improved algorithm is used to improve the performance of the genetic optimization neural network. In this paper, aiming at the genetic optimization neural network in the context of today's intelligent manufacturing, higher vocational schools should strengthen the integration of industry and education, improve the construction of training bases, and promote the comprehensive improvement of students'professional technology and skills, innovation ability and other abilities in the light of the needs of social development in the new era.

… how intelligent manufacturing affects corporate human capital upgrade. We employ China’s intelligent manufacturing … , we find that intelligent manufacturing is positively associated with …

Vocational education plays a critical role in equipping learners with practical skills aligned with industry demands. However, rapid technological advancements and evolving job requirements necessitate frequent updates to curriculum content. Traditional curriculum design methods often fail to address these dynamic needs, leading to mismatched learning experiences and inadequate skill development. This research focuses on developing an Intelligent Recommendation System (IRS) for vocational education curriculum content, leveraging Artificial Intelligence (AI) technologies to create personalized and industry-relevant learning pathways. The system utilizes a dataset comprising vocational curriculum content records (e.g., course titles, descriptions, skill categories, and industry relevance) and student profiles (e.g., learning preferences, academic performance, and career goals). Interaction logs are also incorporated to track user engagement with recommended courses and materials. The data undergo pre-processing, including tokenization and stop word removal, followed by feature extraction using Word2Vec to capture semantic relationships between terms. The core of the system is a Refined Gorilla Troop Optimized Deep Neural Network (RGTO-DNN) model, designed to enhance recommendation accuracy and efficiency. Experimental results demonstrate the effectiveness of the proposed system in improving recommendation accuracy and efficiency, with performance metrics showing high levels of accuracy (97.2%), precision (94%), recall (95.4%), and F1-score (96.3%). The IRS significantly enhances student engagement, learning outcomes, and curriculum design by providing a data-driven approach to modernizing vocational education. These findings highlight the potential of AI-driven recommendation systems to revolutionize vocational education by delivering a more personalized, efficient, and industry-relevant learning experience.

The exponential growth in artificial intelligence (AI) and automation technologies is changing industries, creating a niche for a digitally competent workforce. Technical and vocational education (TVET) and training institutions are at the center of this transformational wave, with their role of equipping individuals with the competencies required for the digital era. The integration of AI and automation into the TVET curriculum and practice was explored as a game-changer for vocational education and training. AI-powered tools are used for personalized learning, intelligent tutoring systems, and virtual simulation of hands-on skills acquisition. The challenges and opportunities in using the technologies were explored to mitigate the digital divide, update instructor capabilities, and ensure inclusive access to modern training resources. Based on the results, TVET institutions can educate students, aligning with the need for Industry 4.0/5.0. Strategic frameworks for policy, curriculum design, and industry partnerships must be established to ensure that TVET continues to play a pivotal role in sustainable and equitable digital transformation.

Vocational education emphasizes the development of practical skills aligned with industry needs. In today's digital era, English proficiency combined with the ability to adapt to technological advancements such as Artificial Intelligence (AI) is essential. AI-powered tools have begun to transform English language learning by offering personalized, adaptive, and interactive experiences. This systematic review aims to examine and synthesize the characteristics of AI-powered tools and their implementation in English language learning for vocational students, focusing on how these technologies support communication, industry-specific language use, and learner autonomy. This systematic review follows the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to ensure a comprehensive and transparent review process. Data were gathered through searches in electronic databases including Scopus, ERIC, Google Scholar, and Web of Science using keywords such as “AI in language learning,” “vocational students,” “ESP,” and “English learning technology.” After screening based on inclusion and exclusion criteria, 20 studies published between 2018 and 2024 were selected for analysis. A narrative synthesis was used to extract and organize key themes. The review identified the following characteristics of AI-powered tools used in vocational English education: real-time feedback, adaptive content delivery, speech recognition for speaking practice, and chatbot-based conversation simulation. These tools were mostly applied through mobile apps, web platforms, and LMS integration. The outcomes showed positive impacts on students’ speaking fluency, vocabulary acquisition, motivation, and engagement. AI-powered tools offer significant potential for enhancing English language learning in vocational settings by providing personalized and flexible learning pathways.

AI's rapid development offers new opportunities for China's vocational education. This study (experiments + interviews) across five colleges (eastern, central, western) highlights key breakthroughs: AI learning analysis improved skill pass rates by 22.7% (36.3% for underperforming students), virtual simulation cut costs by 89.6%, and AI platforms enabled cross-regional resource flow, allowing western colleges to surpass eastern ones in VR training hours. Challenges include high AI customization costs (over 1 million yuan), limited teacher AI training (15% trained), data security risks, and industry gaps. The paper proposes a “technology adaptation-talent support-mechanism guarantee” ecosystem: lightweight technologies, regional equipment sharing, teacher training, enhanced data security, and policy-backed collaboration (subsidies + real-time data links) to shift vocational education from “standardized” to “precision” training.

Vocational education (VE) is one of the important components of the global development of skilled workforces. Incorporating emerging technology into Vocational education is essential to creating a skilled work force and providing people with the practical skills needed for a variety of industries. Vocational and regional colleges play an important role in preparing students with more practical skills that enables them to compete in the global economy. A paradigm shifts in the way skills are taught and learned is necessary, nevertheless, as the demands on vocational education have increased dramatically due to the growing automation and technological power of the global economy. VE is being revolutionized by artificial intelligence (AI), which provides creative ways to improve instruction, training, and skill development by changing pedagogy and learning approaches. This chapter examines how AI is changing vocational programs, emphasizing how it might improve teaching and learning methods and equip students for the changing needs of a workforce powered by AI.

AI provides TVET students with specialized education through adaptive teaching which integrates automated administrative processes into Technical and Vocational Education and Training (TVET). Student engagement increases and learning memorization improves and workforce readiness improves through AI-powered learning tools that employ intelligent tutoring systems with virtual simulations supported by machine learning algorithms. The implementation of AI in TVET faces several challenges since it affects data privacy through algorithms while needing advanced systems and costs substantial funds and remains inaccessible to people who lack digital capabilities. Using Socio-Technical Systems Theory and Diffusion of Innovations Theory and Skill-Biased Technological Change the study investigates TVET Artificial Intelligence development prospects including its operational challenges and business opportunities. The study underlines two crucial elements: both the development of moral AI frameworks and the establishment of effective teacher education together with digital technology and financial support to create inclusive AI systems. AI holds transformative potential for skill-based education provided organizations achieve ethical standard alignment in their planning activities and guarantee universal access to its advantages. Research efforts should prioritize both long-term projects about AI policy development and the establishment of fair practices and clear system operations with accessible services. KEYWORDS: AI in TVET, Artificial Intelligence in Education, Adaptive Learning, Vocational Training, Ethical AI Frameworks, Digital Divide, Teacher Training, Workforce Readiness, Intelligent Tutoring Systems, Educational Technology Policy

The future of work is speculated to undergo profound change with increased automation. Predictable jobs are projected to face high susceptibility to technological developments. Many economies in Global South are built around outsourcing and manual labour, facing a risk of job insecurity. In this paper, we examine the perceptions and practices around automated futures of work among a population that is highly vulnerable to algorithms and robots entering rule-based and manual domains: vocational technicians. We present results from participatory action research with 38 vocational technician students of low socio-economic status in Bangalore, India. Our findings show that technicians were unfamiliar with the growth of automation, but upon learning about it, articulated an emic vision for a future of work in-line with their value systems. Participants felt excluded by current technological platforms for skilling and job-seeking. We present opportunities for technology industry and policy makers to build a future of work for vulnerable communities.

Background: The pressures of Industry 4.0 have driven the incorporation of artificial intelligence (AI) in Technical and Vocational Education and Training (TVET) to improve the development of practical skills. Nonetheless, there is still a lack of empirical agreement regarding the effects and implementation of AI. Methods: We conducted a literature review using databases like IEEE Xplore, Scopus, ERIC, and Google Scholar, as well as grey literature from conference proceedings and UNESCO-UNEVOC reports, to find empirical studies on AI in Technical and Vocational Education and Training (TVET). Our search included keywords such as "artificial intelligence," "machine learning," and "vocational training." After screening titles/abstracts and full texts against our inclusion criteria (focused on TVET settings with measurable outcomes), we identified 11 studies published between 2021 and 2025. Each study was coded by methodology, AI technology type, vocational domain, country, and reported outcomes. Results: Evaluations in vocational trades show AI-driven simulators enhance hands-on skills. Lee et al. found that an AI-guided XR welding trainer improved welding accuracy and learning rate over traditional VR instruction. An Indonesian "AI teaching factory" boosted students' technical proficiency, efficiency, and industry readiness. Surveys indicate high student satisfaction: Malaysian polytechnic students using an AI-powered robotics trainer saw increased understanding and confidence, while TVET students with ChatGPT reported improved comprehension and engagement. Analytical studies highlight curriculum alignment: a decision analysis in the End-of-Life Vehicle sector identified AI integration, tool training, and industry partnerships as priorities for employability. Discussion: Overall, AI applications promise to enhance vocational skill acquisition and engagement. However, much of the research focuses on short-term pilots or perceptions rather than long-term outcomes. Ongoing challenges include limited infrastructure and inadequate teacher preparedness. Future efforts should prioritize rigorous, longitudinal evaluations of AI-enabled TVET interventions using standardized skill and employment outcomes metrics.

This study addresses critical limitations in traditional vocational education assessment systems by integrating value-added assessment theory with artificial intelligence (AI) to develop a Two-Orientation Four-Dimensional (TOFD) evaluation model. Targeting environmental monitoring courses in higher vocational education, the proposed system overcomes fragmented evaluation dimensions, static monitoring, and delayed feedback inherent in conventional methods. The TOFD framework employs AI-driven analytics to track longitudinal student growth across four dimensions: knowledge acquisition, technical skills, professional literacy, and career development. Leveraging multi-source data from academic platforms, simulations, and industry partnerships, the model enables real-time competency profiling and dynamic feedback. A study with 97 students showed the value-added group outperformed the traditional-evaluation group, with 12.59% rise in vocational skill certification rates; 11.14% higher competition awards; and 10.92% improved employer satisfaction. The process-oriented metrics demonstrated a 29.18% relative value-added rate in final project scores compared to initial benchmarks for individual cases, while the class-wide average reached 26.27%.Results validate the system's efficacy in bridging skill gaps, enhancing self-efficacy, and aligning vocational training with industry needs. The study establishes a replicable AI-powered assessment paradigm that shifts vocational education evaluation from terminal certification to competency development, offering actionable insights for curriculum reform and digital transformation in technical education.

The research examines Virtual Simulation along with Artificial Intelligence (AI) Technologies to develop methods for updating educational curricula in higher vocational education by using adaptive learning plans tailored to each student. The proposed system improves training quality through Natural Language Processing and deep learning and virtual simulation tools that generate better skills development and improve student-focus and interactive checking. AI-powered virtual assistants focus on reviewing various educational resources containing simulated training materials along with course materials and interactive examinations to create personalized effective learning situations. Educational content turned into vector spaces at different dimensions through an ordered knowledge base system produces better query understanding and more suitable response solutions. The web-based cyberinfrastructure functions as a unified platform that powers simultaneous collaboration between students and faculty members through integrated multiple platforms. AI material quality improvements come from advanced error prevention technologies along with hallucination detection systems. Learners can independently direct their education through the system while accessing experiential training together with specific knowledge feedback to ensure equitable efficient learning. The study defines how artificial intelligence systems used with virtual simulators establish workforce competency systems across disciplines for future skill development in vocational teaching.

Amid the ongoing integration of industry and education, post-practice instruction in higher vocational colleges faces persistent challenges, including limited student engagement and suboptimal resource utilization. To address these issues while aligning with technological advancements, this paper presents an AI-driven dual-helix model that leverages large language models, LSTM networks, Q-Learning, and blockchain smart contracts to optimize resource allocation and foster self-directed learning. Empirical results demonstrate an 87% core skill attainment rate (29% higher than controls) and a 61% increase in collaborative engagement. The model's scalability is enhanced through cloud-based resource sharing, with future applications exploring generative AI and VR/AR for immersive training environments. This work provides a replicable framework for vocational education innovation through advanced AI and blockchain integration.

This integrative literature review (ILR) examines the influence of artificial intelligence (AI) on vocational training, specifically focusing on unequal access to AI-powered resources and the ensuing inequities in education. The study seeks to analyze the impact of AI on vocational training and employability, offering insights into the advantages and difficulties related to integrating AI technology into educational institutions. The study's conceptual framework is grounded in three primary pillars: AI-driven innovation, challenges, and perspectives. This research is essential for providing valuable insights that can guide strategic planning and policy-making to improve vocational training programs and ensure that they remain effective in preparing students for the changing job market. The ILR methodology entailed integrating theoretical and empirical literature and collecting and evaluating relevant scholarly materials to provide a thorough comprehension of AI's function in vocational training. The results emphasize the capacity of AI to enhance educational achievements using tailored learning, adaptable platforms, immediate feedback, and simulations. However, there is a risk of widening educational inequalities due to biased algorithms. The study highlights the necessity of making significant investments in infrastructure and providing ongoing professional development for educators to incorporate AI successfully. It also suggests the establishment of distinct positions inside vocational training institutions, such as Vocational AI Curriculum Developer (VACD), Vocational AI Data Protection Specialist (VAIDPS), and Vocational AI Sustainability Facilitator (VAISF), to tackle these difficulties effectively. The conclusions highlight the revolutionary capacity of AI in vocational training, soliciting strategic investments and evoking the creation of specialized positions to promote fair and efficient deployment of AI. The study's findings underscore the significance of continuous research and improvements in practice to promote positive societal change and better educational fairness.

… Based on this, this paper proposes a new intelligent talent cultivation paradigm for the network and new media disciplines, viewed from the perspective of human-machine collaboration. …

… With an increased focus on human-machine (HM) collaboration, researchers are beginning … , including AI literacy training, emotional intelligence development, and initiatives to mitigate …

Generative AI has presented a dual opportunity to increase the efficiency and innovation of the new media advertising education, but the depth of its integration with the goal of talent cultivation has not been fully explored. Based on the theory of "human-machine collaborative creation" and "AI dynamic assessment", this research puts forward a new framework for cultivating talents: "Technology Empowerment — Capability Development — Ethics Shaping." Through the development of a two-loop teaching model, which includes "creative idea-content production-strategy optimization," and the integration of a multidimensional AI assessment system, the experimental results show that the model not only reduces the duration of the project, but also improves the students' technical application skills, cross-disciplinary cooperation, and ethical awareness. The research suggests a deep integration of AI tool chain with talent training goals, using dynamic feedback mechanism and cooperation platform between school and enterprise.

The Industrial Revolution (IR) involves a centuries-long process of economic and societal transformation driven by industrial and technological innovation. From agrarian, craft-based societies to modern systems powered by Artificial Intelligence (AI), each IR has brought significant societal advancements yet raised concerns about future implications. As we transition from the Fourth Industrial Revolution (IR4.0) to the emergent Fifth Industrial Revolution (IR5.0), similar questions arise regarding human employment, technological control, and adaptation. During all these shifts, a recurring theme emerges as we fear the unknown and bring a concern that machines may replace humans’ hard and soft skills. Therefore, comprehensive preparation, critical discussion, and future-thinking policies are necessary to successfully navigate any industrial revolution. While IR4.0 emphasized cyber-physical systems, IoT (Internet of Things), and AI-driven automation, IR5.0 aims to integrate these technologies, keeping human, emotion, intelligence, and ethics at the center. This paper critically examines this transition by highlighting the technological foundations, socioeconomic implications, challenges, and opportunities involved. We explore the role of AI, blockchain, edge computing, and immersive technologies in shaping IR5.0, along with workforce reskilling strategies to bridge the potential skills gap. Learning from historic patterns will enable us to navigate this era of change and mitigate any uncertainties in the future.

Abstract Industry 5.0 heralds a new era of human–machine collaboration (HMC) that promises to revolutionize industries and societies. This chapter explores the strategies essential for fostering effective human–machine partnerships. By examining the symbiotic relationship between humans and machines, the chapter highlights the importance of a skilled and adaptable workforce, ethical considerations, and the role of education and training. Additionally, it underscores the need for collaboration between academia, industry, and government to shape the future of work and innovation. Finally, this chapter offers insights to maximize the benefits of HMC, leading to a sustainable, equitable, and prosperous future.

… for human-machine collaboration in the era of Industry 5.0, and explores the skill requirements … at the level of technology application and automation development, and there is a lack of …

The integration of automation technologies and artificial intelligence into production and logistics is transforming work organisation for human and machine agents. Beyond the scope of classical collaborative task allocation problems, studies on social aspects, especially the mutual learning of humans and intelligent machines during interactions, remain scarce. By enhancing cyber-physical production and logistics systems to become intelligent, learnable, and social, human–machine symbiosis can be fostered to enhance their complementary strengths. Despite studies addressing the potential of this bidirectional learning process in the form of reciprocal human–machine learning (RHML), this concept remains ambiguous and lacks a comprehensive knowledge base in production and logistics. Therefore, in this study, a systematic literature review was conducted to gather and categorise the existing knowledge on RHML in different disciplines. Further, efforts were made to (i) consolidate existing design components of RHML into a taxonomy; (ii) describe current design patterns of RHML with classified RHML archetypes; and (iii) apply the resulting taxonomy and archetypes to discuss the potential of RHML concepts in production and logistics. This interdisciplinary approach aims to extend the existing design concepts in cyber-physical production and logistics systems. In addition, initial discussions on the future research agenda are provided.

… , implementation strategies for digital talent cultivation are proposed. These strategies … , where human-machine-object intelligence interactions drive collective evolution, collaborative …

The popularization of intelligent machines such as service robot and industrial robot will make human–machine interaction, an essential work mode. This requires employees to adapt to the new work content through learning. However, the research involved human–machine interaction that how influences the employee’s learning is still rarely. This paper was to reveal the relationship between human–machine interaction and employee’s learning from the perspective of job characteristics and competence perception of employees. We sent questionnaire to 500 employees from 100 artificial intelligence companies in China and received 319 valid and complete responses. Then, we adopted a hierarchical regression for the test. Empirical results show that human–machine interaction has a U-shaped curvilinear relationship with employee learning, and employee’s vitality mediates the curvilinear relationship. In addition, job characteristics (skill variety and job autonomy) moderate the U-shaped curvilinear relationship between human–machine interaction and employee’s vitality, especially the results of moderating effects varying with employee’s competence perception. Exploring the mechanism of the effect of human–machine interaction on employee’s learning enriches the socially embedded model. Moreover, it provides managerial implications how to enhance individual adaptability with the introduction of AI into firms. However, our research focuses more on the impact of human–machine interaction on employees at the initial stage of AI development, and the level of machine intelligence in various industries will reach a high degree of autonomy in the future. The future research can explore the impact of human–machine interaction on individual’s behavior at different stages, and the results may vary depending on the technologies mastered by different individuals. The study has theoretical and practical significance to human–machine interaction literature by underscoring the important of individual’s behavior among individuals with different skills.

The industry-education integration (IEI) is one of the strategies to develop vocational education. The concept of IEI is the basis for the development of vocational education proposed by the Ministry of Education of China in 2011, which mainly refers to the integration of industrial system and education system. The integration is an important measure to promote the reform and development of vocational education and an effective way to train high quality skilled personnel in vocational and technical colleges (VTC). Vocational and technical education should respond to the strategic education development programme of the Chinese government and comply with the basic requirements of IEI in vocational and technical education. This paper aims to develop the conceptual framework for IEI to serve the vocational and technical college students better. The VTC will focus on training social service personnel as the goal, through the reform of teaching content, inspire students to innovate learning mode in the learning process, the combination of demand-driven and IEI, to enrich students' practical experience and professional work ability. In the course of vocational and technical education, some training subjects of scientific research should be added to cultivate students' ability of independent work and innovation. Through the application of the Internet technology of modern science and technology to improve the teaching environment, to achieve the quality of talent training for the goal of teaching methods and teaching modules, to provide enterprises with elite talents. The students will most probably benefit from the industry-driven education initiatives.

Under the dual impetus of industrial upgrading and higher education quality enhancement, it has become a common consensus to construct a student competency evaluation tool that can reflect the entire “teaching–learning–application” chain. However, existing studies remain insufficient in terms of system integrity and quantitative operability. Guided by the CIPP evaluation model (Context–Input–Process–Product), this study follows the logical progression of “context–input–process–output.” Through a combination of literature review, expert interviews, and the Delphi method, an initial set of indicators was developed. The Analytic Hierarchy Process (AHP) was then employed to determine indicator weights, and a fuzzy comprehensive evaluation approach was integrated to construct the quantitative model. The results indicate that the established system effectively balances process monitoring and outcome orientation, emphasizing university–industry collaboration, authentic learning contexts, and ability transferability, while demonstrating strong interpretability and diagnostic value. The final framework includes 4 primary indicators, 11 secondary indicators, and 68 tertiary indicators. The expert authority coefficients for the two Delphi rounds were 0.840 and 0.845, respectively, with Kendall’s coordination coefficients of 0.182 and 0.244. The AHP consistency test yielded CR < 0.1, confirming reliability. Using a sample of 132 students from the 2019 cohort of the Mechanical Engineering program at a “Double First-Class” university, model application results showed that 79.6% of students achieved an overall competency level of “good” or above. Among the first-level dimensions, the expected values of process evaluation and input evaluation outperformed those of context evaluation and output evaluation, suggesting the need to further strengthen institutional reputation building and graduate quality feedback mechanisms. The findings demonstrate that the proposed indicator system and evaluation model can effectively mitigate ambiguity and subjectivity in competency assessment. It possesses high applicability and promotional value in supporting teaching quality diagnostics, talent training program optimization, and deep university–industry collaboration.

… This process allows students to demonstrate initiative, resilience, and a proactive attitude towards learning, effectively translating their acquired knowledge and technical skills into prac…

PurposeWhile the industry–education integration has achieved significant results, it also faces many prominent problems. The current problems include some projects prioritizing research and development over education, insufficient breadth and depth of cooperation and a lack of quality monitoring and evaluation mechanisms. Breaking through these problems to deepen industry–education integration is an important issue that urgently needs to be studied.Design/methodology/approachTaking the second batch of 10,283 industry–education integration projects of the Ministry of Education in 2019 as a case study, the problems existing in the Chinese industry–education integration projects are analyzed. We should make full use of the advantages and resources in the era of digital economy to seek the right path to deepen the integration of industry–education.FindingsThe study finds that governments can leverage the advantages and opportunities of the digital economy to deepen the reform of industry–education integration.Originality/valueThe policy suggestion is to deepen the mechanism of multi-party linkage and collaborative education, actively build an industry–education integration service platform and promote the two-way docking of industry education supply and demand.