2.1 Course Content

With the goal of cultivating innovative practical abilities to meet the demands of "future intelligent manufacturing technologies," we establish a student-centered teaching approach aimed at enhancing students' innovative practice capabilities and comprehensive skills. This approach continues to deepen the reform of the innovative practice system within the curriculum. For example, in the "Freshman Engineering Experience" course, interdisciplinary cross-fertilization is strengthened by integrating disciplines such as the Internet of Things (IoT), artificial intelligence, and others [16, 17]. Additionally, the course content incorporates the development of real-world system projects, adapting to the practical needs of the course. Tasks such as using small development boards for actual project development are introduced, where students are encouraged to select topics and design multiple systems.

Figure 2 The systematic intelligent manufacturing innovation talent cultivation framework, with "five goals to lead, three platforms to support, double-loop synergy, four-step evaluation, four-level curriculum" as the core structure, has constructed a whole chain education system from goal orientation to implementation, and provided a replicable reform paradigm for the cultivation of talents in the field of intelligent manufacturing.

The "Freshman Engineering Experience" course is divided into theoretical and practical sessions, with theoretical knowledge and practical skills reinforcing each other. This structure facilitates a step-by-step learning process, progressing from foundational to advanced levels. The course system, as depicted in Figure 2, aims to enhance students' professionalism and comprehensive abilities across various domains, with the following objectives:

This study proposes a systematic framework for cultivating intelligent manufacturing innovation talents, integrating five core educational objectives (theoretical mastery, innovative thinking, practical skills, application competence, and professional capability) with three supporting platforms (theory-practice integration, blended learning, and disciplinary-cultural convergence). The framework features a dual-loop synergy mechanism that bridges theoretical and practical instruction, complemented by a four-phase evaluation system (objective-based, pre-course, formative, and summative assessments) for comprehensive quality monitoring. Implementation is achieved through a progressive four-level curriculum system, ranging from introductory engineering experiences to interdisciplinary capstone projects. This integrated approach demonstrates rigorous alignment among educational goals, support infrastructures, quality assurance mechanisms, and instructional delivery, offering a replicable model for advanced manufacturing education that effectively addresses the theory-practice divide while fostering interdisciplinary innovation capabilities.

First, based on comprehensive theoretical foundations, a teaching model of "internal and external synthesis" is constructed. Within the discipline, this model integrates theoretical teaching, experimental operation, and practical application through multi-dimensional teaching resources. Leveraging the discipline's comprehensive practice courses, the curriculum knowledge and basic skills are systematically summarized and integrated, enabling a personalized educational trajectory [18]. This approach aims to establish a more complete system of disciplinary knowledge and skills. At the interdisciplinary level, the "Freshman Engineering Experience" course facilitates the deep integration of multidisciplinary knowledge and skills, promoting a shift in educational philosophy from pure "knowledge acquisition" to "competence development." This transformation is achieved through the following instructional contents, aligning with the educational concept of fostering competence rather than solely focusing on knowledge mastery [19].

Secondly, an "iterative and progressive" path for capability cultivation is established, guided by problem-solving and practical application. The development of capabilities should adhere to the principle of gradual progression, with subsequent practical teaching sessions designed based on the outcomes of preceding ones. The teaching content of the following four practical courses utilizes the overall engineering system as the framework, with a series of interconnected design tasks serving as the main teaching line. This approach transitions from simple to complex task, from discrete operations of individual modules to the joint collaboration of multiple modules, and from basic unit-level skills training to the comprehensive application at the system level. These tasks are divided into task-based, subject-based, and problem-based projects [20], transforming the stage-by-stage development of competence into a hierarchical, systematic, and coherent process.

Upon completion of the theoretical study and practical exercises in each chapter, students will engage in a comprehensive, systematic practice. At this stage, they will design and implement a complex automation and intelligent system project, integrating all previously learned knowledge and skills. For instance, students may design a smart home system that collects environmental data (such as temperature, humidity, and light) through Arduino microcontrollers and sensors, processes data and makes intelligent decisions using core computing equipment, and realizes a user interface display and remote-control function via a WeChat applet. This comprehensive system practice not only serves as an application of the knowledge acquired in earlier chapters but also acts as a comprehensive assessment of students' overall abilities and innovation.

2.2 Assessment Indicators

In the teaching process, activities such as "literature search and report," "academic knowledge speech contest," and "innovation contest defense" are incorporated. These activities provide students with course-related topics, which they then prepare in groups and share their learning outcomes with the class. This approach effectively cultivates students' abilities in literature search, reading, teamwork, and speech expression. The "Creator Innovation Competition" and similar activities promote talent development within the competition-course integration model by leveraging competitions to drive teaching and learning [21]. This strategy enhances students' initiative in learning, solidifies their knowledge base, and broadens their understanding of the subject matter.

The adoption of a comprehensive assessment methodology has fundamentally transformed the evaluation paradigm, significantly diminishing the weighting of terminal examinations within the overall course assessment framework. This pedagogical shift has been characterized by an increased emphasis on formative assessment strategies, prioritizing the progressive accumulation of knowledge and competencies throughout the instructional period. The conventional grading system has been restructured to incorporate multiple evaluative components, including but not limited to attendance records, homework assignments, literature review and report composition, academic presentation competitions, and experimental outcomes. The assessment ratio has been established at 4:6 for continuous evaluation versus final assessment, with specific weightings allocated as follows: attendance (5%), homework completion (10%), experimental performance (10%), and report quality (25%).

The terminal evaluation comprises two principal components: the "Creator Innovation Competition Defense" and the comprehensive final examination. The defense mechanism is subjected to rigorous scrutiny by a panel of experts comprising both industry professionals and academic supervisors, who conduct a multidimensional evaluation of team presentations, individual contributions, and innovative entrepreneurial competencies. This comprehensive assessment framework, through its structured distribution and multifaceted approach, effectively incentivizes students to engage in autonomous learning, develop effective learning methodologies, identify novel research problems, acquire new knowledge domains, and enhance their theoretical understanding, practical skills, and cross-cultural competencies, thereby fostering a more holistic educational experience.

2.3 Introduction of Cultural Content

Based on the staged and systematic nature of undergraduate education, as well as the unique characteristics of automation majors, this study focuses on the undergraduate students enrolled in the "Freshman Engineering Experience" lectures as the research subject. Data was collected through a questionnaire survey, followed by in-depth analysis. The study identifies key aspects of professional cultural education, aiming to highlight the factors of cultural education that should be considered in fostering engineering students' engagement in activities and preparing them to solve problems [22]. The primary goal is to inspire the integration of cultural education factors in the development of engineering students and their problem-solving capabilities.

Table 1 presents some of the cultural and educational elements integrated into the "Freshman Engineering Experience Course."

This study conducts a comprehensive analysis of the constituent elements of professional culture across multiple educational contexts, encompassing undergraduate admissions processes, academic curricula, extracurricular student organizations, and research-oriented competitive platforms.

3.1 Students' Works on Display

1) Electronics and Embedded System Category:

The "Lighting Matrix" created through the Gluttony Snake mini-game demonstrates a breakthrough in traditional design. This homemade gaming device showcases the creative application of electronic components and software programming.

2) Mechanical Design and Manufacturing Category:

The "Weight Lifting Robot" as depicted in Figure 3, focuses on the design and manufacturing of the mechanical structure, including components such as the mechanical arm, grasping mechanism, and support structure. The design process involves careful consideration of material selection, mechanical analysis, and structural optimization to ensure that the robot can withstand heavy loads and perform lifting operations with precision.

Figure 3 Weight-lifting robot.

The weightlifting robot case study serves as a robust validation of the proposed talent cultivation framework's scalability, demonstrating its efficacy in addressing core mechanical engineering competencies (structural integrity, dynamic stability, and precision control) through a systematic four-tier curricular progression (from foundational engineering experiences to advanced interdisciplinary integration). This implementation exemplifies the framework's dual adaptability: vertical specialization through progressively sophisticated content integration (e.g., finite element analysis in upper-division courses) and horizontal expansion via cross-disciplinary synthesis (e.g., mechatronic systems combining control theory with advanced materials science). The modular instructional design, coupled with a multi-phase assessment protocol, establishes a replicable yet customizable pedagogical model for intelligent manufacturing education, effectively bridging the gap between theoretical knowledge and practical engineering applications while maintaining flexibility for discipline-specific customization.

3) Automation and Control System Category:

The "Small Car Model Transformed into an Automatic Door" as shown in Figure 4, utilizes sensors to enable intelligent opening and closing of the door, as well as people counting. This project, closely related to real-life applications, demonstrates the students' initial exploration of integrating mechanical structures with sensor technologies.

Figure 4 Small car model transformed into an automatic door.

The "Radar Scanning and Mapping Cart" as depicted in Figure 5, is equipped with radar sensors that facilitate environmental scanning and mapping through data processing algorithms and embedded systems. The cart is capable of autonomously avoiding obstacles and generating a two-dimensional map of its surrounding environment.

Figure 5 Radar scanning plotter cart.

This study systematically validates the scalability of the proposed smart manufacturing talent cultivation framework through two representative case studies: an automatic door trolley and a radar mapping trolley. The automatic door project serves as an ideal introductory platform for freshman engineering courses, effectively establishing fundamental interdisciplinary knowledge integrating mechanical, electronic, and control systems. In contrast, the radar mapping project provides an advanced comprehensive practice that demands mastery of sensor technologies, sophisticated data processing algorithms, and embedded system development. These complementary cases demonstrate the framework's "theory-practice" dual-loop mechanism, exhibiting a clear pedagogical progression from basic sensor applications to complex algorithmic implementations. The adaptable four-step evaluation scheme accommodates varying project complexities, ranging from fundamental functional verification to comprehensive multidimensional assessment encompassing algorithm design, system integration, and performance optimization. Through this tiered project structure and modular technical components, the framework successfully bridges foundational knowledge with innovative practice, thereby confirming both its universality and scalability in smart manufacturing education.

3.2 Overall Description of Student Work

The objectives of the Freshman Engineering Experience course are to foster students' interest in hands-on practical skills, to provide an understanding of the professional training goals, and to equip students with the theoretical knowledge and methods necessary for addressing social needs and practical applications. The students' projects are closely aligned with these goals, demonstrating their proficiency in mechanical design, sensor technology, and the application of electroniccomponents. For instance, the weightlifting robot utilizes sensor technology for intelligent control, with the structure of the work shown in Figure 6.

Figure 6 Weightlifting robot works architecture.

Similarly, the radar scanning and mapping trolley autonomously avoids obstacles and generates a map of the surrounding environment, as illustrated in Figure 7. These projects reflect the students' understanding of automation and its application in enhancing convenience in daily life.

Figure 7 Radar scanning and mapping vehicle architecture.

3.3 Student Achievement Statistics

Statistical analysis of student grades in the "Freshman Engineering Experience" course for the 2022-2023 academic year revealed that the grades followed a normal distribution, with a concentration in the 70-90 point range. Additionally, the experimental results had a significant impact on the overall evaluation, with students demonstrating superior experimental abilities generally achieving higher overall scores. The statistical distribution of student results in the "Freshman Engineering Experience" course is presented in Figure 8. The peak of the kernel density curve is located in the 80-90 point range, which corresponds to the highest bar in the histogram, emphasizing the concentration of the majority of students' scores in this interval.

Figure 8 Statistical distribution of student grades in the freshman engineering experience program.