Cultivating application-oriented talents with innovative ideas and strong comprehensive ability is the key to the current reform of mathematics teaching in colleges and universities. Based on the simulation and practicality of the case teaching method, this paper introduces it into the teaching of mathematical modeling courses. In order to investigate the role of case teaching method on the establishment of students' application consciousness, two classes with basically close starting levels are selected to carry out teaching experiments, and the teaching effect of mathematical modeling course based on case teaching method is evaluated by means of course tests and questionnaires. After the teaching practice, the test scores of the experimental students were improved by 7.34% compared with those before the experiment, and 3.40% compared with the control students, and 31.23%~47.93% in the cultivation of mathematical application consciousness was obtained, which confirms the role of the case-based teaching method in helping the students' academic performance and mathematical application consciousness. The application of actual case teaching method in mathematical modeling course is beneficial to cultivate students' mathematical thinking and innovation ability, and is a kind of teaching method that effectively improves the teaching effect of mathematical modeling.

The development of applied talents in the corn industry cluster during the new era is a comprehensive effort involving various interactions of multiple factors. Precise determination of the critical influencing factors forms the essential prerequisite for promoting talent development in this specific area. Using the DEMATEL approach, this paper measures the effects of each factor and determines the core influencing factors. Based on the core factors, this paper analyzes the questionnaires relevant to the examples of applied talent cultivation in the new-era corn industry cluster using the combination of non-competitive analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA). The results show that the core influencing factors include government, industry, education and research, quality assessment, cooperation and exchanges, and capital support. The configuration analysis finds no necessity, and there are four talent cultivation pathways, which can be classified into three models, namely “Strong Habitual Type,” “Domain-Habitual Type,” and “Habitual-Balanced Type.” This research provides a valuable reference to facilitate the deep integration of applied talent cultivation and civic-political education in the corn industry cluster.

Addressing current challenges in the teaching process--including students 'weak theoretical foundations, monotonous theoretical content, and insufficient practical experience--we integrated the OBE project-based teaching approach, aligned with the university's educational philosophy of "cultivating high-quality, interdisciplinary, and application-oriented talents" and the specific characteristics and realities of the Fundamentals of Electronic Technology course. Implementation results demonstrate enhanced students 'engineering project thinking, practical skills, and overall course teaching quality, contributing positively to the institution's talent development and significantly improving educational outcomes.

Cybersecurity threats are becoming increasingly complex and diverse. Cultivating applied professionals with practical skills has become a key task for higher education. This paper proposes an innovative talent development system, centered on localized Retrieval-Augmented Generation (RAG) technology and integrating multiple technologies to promote the deep integration of technology and teaching. First, a knowledge integration and update mechanism based on localized RAG is constructed to automatically integrate authoritative vulnerability libraries such as NIST NVD, CNVD, and CWE. Machine learning techniques are applied for data cleansing and feature extraction to ensure the continuous acquisition of timely and accurate knowledge, laying a solid foundation for teaching and case generation. Second, personalized case generation technology is applied. By combining pattern recognition and machine learning algorithms to analyze student competency models, learning history, and the latest threat intelligence, Large Language Models (LLMs) are used to dynamically generate targeted attack and defense scenario descriptions, reproduction steps, and detection/defense solutions based on deep learning methods. This system meets differentiated learning needs and effectively improves students’ ability to cope with real-world threat environments. Furthermore, a natural language interactive teaching support system is designed. Relying on knowledge base engines (such as AnythingLLM), it realizes multi-format document analysis (including PDF, Markdown, Word, etc.) and efficient ingestion and vectorized storage, and combines with the Ollama artificial intelligence big model for intelligent retrieval and text generation to enhance the comprehensibility and interactivity of teaching content. In knowledge base management, efficient document analysis, pattern recognition and vectorization technologies are used to ensure storage and retrieval efficiency, and private intelligent cloud solutions (such as Infortres) are used to achieve secure remote access to local data and artificial intelligence services to meet compliance requirements and provide convenient support. Practical verification shows that the system significantly improves students’ offensive and defensive practical ability and problem-solving ability, and provides teachers with efficient and flexible teaching methods. In summary, the system realizes the deep feedback of technology and education, and opens up a new path for the cultivation of application-oriented talents in network security. In the future, we will optimize the case generation strategy, expand the scope of the knowledge base, and explore more artificial intelligence teaching applications (such as adaptive learning path recommendation) to continuously improve educational effectiveness.

With the development of society and the progress of science and technology, the demand for applied talents is increasing. In this background, the teaching reform of applied undergraduate universities is particularly significant. As a widely applied mathematics course, the teaching reform of probability theory and mathematical statistics aims to enhance students’ practical application ability and innovation ability. This paper discusses the teaching reform strategies in probability theory and mathematical statistics courses in applied undergraduate colleges, including the integrated teaching of science and reality, the teaching of rethinking, and case teaching. Through the integrated teaching of science and practice, theoretical knowledge is combined with practice to enhance students’ data analysis ability; through the teaching of focusing on ideas, the understanding of the ideological methods of probability statistics is emphasized rather than the mere derivation of theorems; through the teaching of case studies, practical problems are combined with theoretical knowledge to enhance students’ sense of application and problem-solving ability. Studies have shown that these reform measures can significantly improve students’ academic performance and practical ability, and provide strong support for the cultivation of application-oriented talents. Future teaching reforms need to constantly summarize experiences and improve measures to adapt to the changing social needs and technological progress.

The formation and development of new quality productive forces depend not only on technological breakthroughs but also on high-quality application-oriented talents who master new knowledge, new technologies, and new processes. As the intersection of the Northern Guangdong Ecological Development Area and the undertaking ground for industrial transfer from the Pearl River Delta, Qingyuan City faces dual challenges in the process of promoting the digital, intelligent, and green transformation and upgrading of its manufacturing industry: a structural shortage of application-oriented talent supply and the poor operation of the "Government-Industry-University-Research" collaborative mechanism. Based on the connotation and characteristics of new quality productive forces, this paper analyzes the new requirements for the quality of application-oriented talents. It examines the realistic dilemmas in the current local "Government-Industry-University-Research" collaborative training mode, such as "divergent government guidance, involution of enterprise participation, lagging adaptability of universities, and inefficient conversion rate of scientific research." Based on the "Quadruple Helix" innovation theory and collaborative governance theory, this paper constructs a new "Government-Industry-University-Research" collaborative mode centered on the deep integration of the "industrial chain, innovation chain, education chain, and talent chain." Combined with the construction of the "Provincial Vocational Education City" in Qingyuan and the practice of the "Hundreds, Thousands, and Ten Thousands Project," specific innovation paths are proposed, such as co-constructing modern industrial colleges, creating regional industry-education consortia, and building a full-life-cycle talent service ecosystem. The aim is to provide theoretical support and a practical paradigm for underdeveloped areas to drive the development of new quality productive forces relying on the talent engine.

Under the strategic goal of the Education Powerhouse, the cultivation of applied talents in universities is facing new opportunities and challenges. This article proposes a systematic optimization path across five dimensions: model innovation, curriculum development, faculty capacity building, evaluation reform, and support systems. It aims to promote the construction of an application-oriented talent training system in universities that is demand-oriented, which is characterized by deep industry-education integration. The ultimate goal is to provide high-quality talent support for the construction of the education powerhouse.

This study examines the discrepancy between big data talent training and industry demand. The study analyzed 85 training programs and over 10,000 job postings from two job boards in China (51job and Zhaopin). Using content analysis, social network analysis, and the BERTopic-TOPSIS model, it mined implicit information from training programs and labeled key competencies in job descriptions. A key finding was a significant supply-demand misalignment: while “data application ability” was a stated goal in 52% of programs, only 11% of graduation requirements specified concrete, measurable skills to achieve it. The study identified three primary employment pathways for big data management and application majors: data management, data analysis, and data platform development. Institutions such as Peking University and Hefei University of Technology were identified as best practices. The study then delineated a cultivation path for the major by integrating the characteristics of these employment pathways, and optimised general knowledge and compulsory courses, core courses, graduation requirements, and the cultivation objectives of the major.

Principles of engine is one of the car class specialized compulsory core courses, for engine by learning this course hopes to develop the industry more engine design and application talents, with the rapid development of information technology, the traditional blackboard writing + courseware teaching methods can't guarantee the quality of teaching and the teaching effect, In order to improve the teaching quality and teaching effect of engine principle course, this paper first introduces some theoretical knowledge of micro-lesson, and then discusses the specific application of micro-lesson in engine principle teaching.

With the rapid development of informatization in the construction industry, Building Information Modeling (BIM) technology has become an essential tool for advancing digital and intelligent transformation. In intelligent construction, BIM technology significantly enhances the efficiency of design, construction, and operation, offering new directions for industry development. Traditional architectural education now faces challenges in aligning with industry demands. Integrating BIM into higher education to cultivate skilled, application-oriented talent is crucial. This paper explores how to innovate architectural engineering practice teaching and proposes a BIM-based intelligent construction model, validated through case studies. The findings show that this model improves students' practical abilities and prepares them to meet the industry's evolving needs.

The current engineering education in universities still generally faces problems such as insufficient interdisciplinary mechanisms, redundant course content, and a disconnect between theory and practice, making it difficult to meet the demand for composite talents in the new engineering field. This paper focuses on the interdisciplinary integration of different engineering majors in the construction and implementation of the course "Signals and Systems". It constructs a modular curriculum system, teacher collaboration mechanism, and teaching resource co-construction, which can ensure the characteristics of each major and maximize resource efficiency, providing a replicable paradigm for the integration of interdisciplinary courses in engineering education; Based on the overall architecture of the course groups of "Fundamentals of Circuit Analysis", "Signals and Systems", and "Digital Signal Processing", course collaboration is achieved through knowledge chain integration and ability gradient cultivation, achieving seamless integration of course group content; By conducting engineering cases and practical research, we aim to solve the problem of strong theoretical knowledge and weak engineering applications, which can meet the innovative needs of new engineering teaching. The teaching team has conducted relevant teaching reform attempts and explorations in teaching practice, promoting the improvement of teaching quality and effectively assisting in the cultivation of innovative, versatile, and application-oriented talents, which has broad promotion value.

Against the backdrop of the rapid development of artificial intelligence technology and the increasing prevalence of microcontroller unit (MCU) technology, traditional teaching models are struggling to meet the current societal demands for the cultivation of application-oriented talents. This paper takes MCU teaching as an example to delve into the challenges in the current cultivation of application-oriented talents and the new opportunities brought about by AI empowerment. It elaborates on the innovative application pathways of AI technology in key aspects of MCU education, such as teaching, practical training, and capability evaluation. By constructing an AI-empowered MCU talent cultivation model, it achieves personalized teaching, intelligent practical guidance, and precise capability assessment, effectively enhancing students' comprehensive quality and innovative abilities in MCU system design and application development. The research results indicate that the AI-empowered educational model can significantly improve the efficiency and quality of MCU talent cultivation, providing new ideas and methods for the principles of MCU and the cultivation of application-oriented talents. It holds significant theoretical value and practical significance for promoting educational modernization and aiding industrial upgrading.

As science and technology advance rapidly, smart sensors and 5G communication technology have become important forces in promoting innovation and change in all walks of life. In the context of emerging engineering education, the integration of intelligent sensors and 5G technology not only offers fresh avenues for nurturing science and engineering talents but also presents new opportunities for cultivating innovative liberal arts professionals. Taking this backdrop into consideration, this paper delves into the potential applications of intelligent sensors and 5G technology within the field of liberal arts education and constructs the corresponding application-oriented talent training mechanism. The training mechanism of new liberal arts applied talents integrating intelligent sensors and 5G technology is elaborated in detail. This mechanism emphasizes market demand-oriented, and cultivates applied talents with solid basic knowledge of liberal arts, familiarity with intelligent sensors and 5G technology applications, and good innovation ability and practical ability through Collaboration between enterprises and educational institutions, fostering an integration of industry and education. Simultaneously, the mechanism also focuses on the optimization of the curriculum system and the innovation of teaching methods to meet the needs of technological development.

In an era defined by profound digital transformation, China's national strategy for vocational education reform calls for talent cultivation models that are not only deeply integrated with industry but are also inherently forward-looking. This paper presents a descriptive and theoretical case study of an evolved pedagogical framework for Business English majors: the Post-Course-Competition-Certificate-Intelligence (PCCCI) model. This five-dimensional, synergistic framework enhances the established four-pillar integration of Professional Posts, Competency-based Courses, Skills Competitions, and Industry Certificates with a crucial fifth element that serves as its core: Digital Intelligence. This new dimension represents the systematic infusion of digital literacy, data analysis capabilities, and intelligent technology application across the entire educational ecosystem, transforming it from a linear process into an adaptive, dynamic system. The study eschews empirical pedagogical data, focusing instead on a rigorous theoretical and structural analysis of the PCCCI model's design and conceptual underpinnings. We analyze its direct alignment with contemporary educational policies, such as the "1+X" certificate system, and its capacity to address the escalating demands of the global digital economy for multifaceted, tech-savvy, and application-oriented talent. The conceptual foundations of each of the five pillars and their dynamic interplay are explored in depth, arguing that the PCCCI model provides a holistic and replicable pathway for cultivating future-proof Business English professionals. A detailed narrative description of the model’s conceptual graph is provided to visually articulate the integrated workflow and the student's developmental trajectory within this enhanced framework. Ultimately, this case study contributes a detailed blueprint to the discourse on vocational education reform, offering a cohesive, competency-driven educational model that not only bridges the persistent gap between academic learning and professional practice but also strategically prepares students for the future of work in an age of intelligence.

In the pursuit of educational excellence, universities have begun adopting innovative models that integrate creativity, innovation, entrepreneurship, collaboration, and application into the talent cultivation process. This paper introduces the Five-in-One Talent Cultivation Model that aligns with the educational reforms within Chinese higher education, focusing on applied talent development, industry collaboration, and regional service. Specifically, it examines the rapid growth of student participation in national and provincial competitions, the alignment of academic programs with national and regional strategies, and the establishment of collaborative industry-academia research platforms. The paper also discusses the dynamic development of smart education systems and the structural optimization of professional courses to create highly skilled and market-ready graduates.

This study aims to construct a Teaching Management System (TMS) and develop an efficiency evaluation index system for computer science-based applied talent training in higher education institutions. The TMS integrates advanced technologies such as artificial intelligence (AI) and machine learning (ML) to enhance teaching and learning processes. Through requirement analysis, modular design, and agile development practices, the system is built to meet the specific needs of computer science education. The efficiency evaluation index system covers multiple dimensions, including system functionality, user satisfaction, teaching effectiveness, and data management. Using the Ana-lytic Hierarchy Process (AHP), weights are assigned to each indicator to provide a comprehensive assessment framework. Empirical data from participating universities validate the model and offer insights for system improvements. The results show that the TMS significantly improves the efficiency and quality of educational delivery, while the evaluation framework provides a scientific basis for continuous enhancement. Future work will focus on expanding the application scope, refining the evaluation system, and exploring further technological integrations to continuously improve teaching management and student learning outcomes.

As a core general education course in higher education, College English plays a crucial role in implementing the “student-centered” educational philosophy and cultivating practically competent and application-oriented talents. Guided by The Guidelines on College English Teaching (2020 Edition) and integrating Professor Wen Qiufang’s theory of Teacher–Student Collaborative Assessment (TSCA) within the framework of the Production-Oriented Approach (POA), this paper addresses several persistent issues in current College English teaching, such as one-way knowledge transmission, the imbalance between input and output, insufficient integration of ideological and political education, and the monotony of evaluation systems. Based on these challenges, the paper constructs a College English teaching model that combines reading and writing and promotes learning through assessment. The model integrates process writing pedagogy and TSCA into a closed-loop design that includes a detailed review of typical samples before class, collaborative assessment during class, and peer review and reflection after class. Ideological and political elements are also embedded throughout, supported by digital teaching tools that enable dynamic tracking and multi-dimensional evaluation across the learning process. The practice results show that this model effectively stimulates students’ motivation to learn English, enhances their ability to use the language in practice, and improves their intercultural competence. Furthermore, it provides a practical reference for the integration of ideological and political education into College English and for broader teaching reform under the framework of “New Liberal Arts.”

With the deepening of economic globalization, China’s economic, cultural, and political exchanges and cooperation with other countries in the world have become increasingly frequent, which has driven the development of business and trade and led to a strong demand for application-oriented business English talents. Against this backdrop, universities should actively promote the reform of business English interpretation teaching to improve students’ English listening and interpretation abilities and enhance their employability. This paper analyzes the necessity of reforming business English interpretation teaching under the background of cultivating application-oriented talents, examines the current situation of business English interpretation teaching, and proposes that it is necessary to improve the textbook and curriculum system, innovate the practical teaching methods of business English interpretation, carry out business English interpretation teaching jointly by universities and enterprises, and improve the teaching evaluation system, so as to comprehensively enhance the quality of business English interpretation teaching.

In view of the current issue of disconnection between the current training of security disciplines and the needs of complex safety governance, this paper proposes to construct an application-oriented talent training system of security disciplines with integrated information coupling of Air-Space-Ground (ASG) and Prevention-Reduction-Rescue collaboration of the whole industry chain. Combined with the integration of scientific and technological innovation and industrial development, the transformation of safety discipline from the experience to the technology-data-intelligence driven is implemented, and a talent training curriculum system with professional characteristics is constructed. Through the integration of satellite remote sensing, unmanned aerial vehicle monitoring, ground sensing network and other technologies, the intelligent coupling of multi-source data is realized. At the same time, it breaks the traditional single-link training model of safety disciplines, and establishes a collaborative training mechanism for the whole industry chain covering risk prevention, disaster mitigation, and emergency rescue. It cultivates more high-quality and innovative safety talents for safety disciplines, and provides strong talent support for ensuring social security and stability and promoting sustainable economic and social development.

Industry-education integration, a strategic bridge connecting the realms of education, talent development, industry dynamics, and innovation initiatives, stands as the pivotal pathway in resolving the inherent structural contradictions between talent cultivation and the evolving needs of industries. This study delves into the intricate and enduring collaboration between Hanshan Normal University and ChaoZhou Three-circle (Group) Co., Ltd., employing a case study approach to meticulously dissect the systematic reform initiatives undertaken by both entities. Areas scrutinized include the establishment of collaborative educational mechanisms, the revamping of curriculum frameworks, the innovation in practical teaching methodologies, the reciprocal empowerment of teaching faculty, and the multidimensional expansion of educational platforms. Not only does this study analyze the tangible outcomes of these reforms in bolstering students' practical expertise, elevating the quality of talent nurture, catalyzing the transfer of research outcomes into practical applications, and enhancing societal engagement capabilities, but it also delves into the entrenched impediments and challenges present at various levels such as collaborative frameworks, resource allocation dynamics, and factors influencing the motivation of educators and students. Building upon these insights, a series of precise and implementable optimization strategies are delineated, with the primary aim of providing replicable and widely applicable paradigms and theoretical perspectives for akin institutions seeking to deepen industry-education integration and establish robust frameworks for cultivating top-tier applied talent.