Research on Informationized Teaching Resources Integration of Talent Cultivation Mode in Higher Vocational Innovation and Entrepreneurship Education Promoted by Industry-Teaching Integration

First of all, the objectives of the industry-education integration model for skilled personnel have been clearly defined under the guidance of system science theory. The system science theory advocates a comprehensive and systematic analysis of problems, so the goal of the model is not only to cultivate students’ vocational skills, but should also include a deep understanding of the industry and the education system. Such a goal aims to cultivate students with a holistic view and systemic thinking, so that they can better adapt to and lead the development of the industry in their careers. Secondly, the objectives guided by the system science theory emphasize the cultivation of sustainable development and innovation ability. Through the integration of industry and education, students should be able to learn and innovate continuously by having a forward-looking mindset for the future career field while accumulating experience in practice. The aim of this goal is to enable students to respond flexibly and remain competitive in a rapidly changing social and technological environment.

By using well-designed practical projects, students can apply their knowledge in real-life scenarios, combine theory with practice, and improve their professional skills. For example, in engineering majors, field trips and simulated engineering projects can be used to directly challenge students to develop practical problem-solving abilities. Such practical teaching links can not only enhance students’ practical skills, but also cultivate their analytical and problem-solving abilities, laying a solid foundation for future practice. In addition, in the actual operation, the problems faced by students are often diverse and complex, requiring them to flexibly apply what they have learned and propose innovative solutions. By encouraging students to participate in real projects and implement innovative practices, they can be inspired to think critically about problems and have the courage to challenge traditional concepts. For example, in business majors, students can be allowed to refine their sense of innovation in practice by conducting field research on the market and formulating entrepreneurial plans, so as to cultivate their qualities of proactive exploration and courageous experimentation in unknown fields. This innovative teaching mode can help break the constraints of traditional teaching and stimulate students’ creativity and entrepreneurial spirit.

First of all, the concept of integration of industry and education emphasizes the in-depth integration of education and industry, so that students can better adapt to the needs of social development by combining school education with actual production and application. Under the perspective of system science, the integration of industry and education is not only a simple superposition of industry and education, but also an organic integration. This integration is an organic integration through the establishment of a feedback mechanism to continuously adjust the content and methods of education, so as to make it more in line with the actual needs of industrial development. At the same time, the concept of integration of industry and education also focuses on cultivating students’ innovative thinking and practical operation ability, through the participation of real projects, so that students can continuously improve their comprehensive quality in practice. Secondly, school-enterprise cooperation, as a concrete practice of integrating industry and education, is an important way to deepen the integration of industry and educational resources. By establishing strategic partnerships with enterprises, schools can better understand the needs of the industry, adjust the curriculum, and optimize the teaching plan. The participation of enterprises can also provide students with a more practical learning environment, allowing them to better integrate into the workplace. Under the vision of system science, school-enterprise cooperation builds a more complex and organic cultivation system, forming a close information feedback loop between schools and enterprises. This kind of cooperation not only helps to cultivate students’ skills, but also provides enterprises with more adaptable talents to meet market demands. Finally, in the construction of the industry-teaching integration model for skilled personnel, adhere to the concept of industry-teaching integration and strengthen school-enterprise cooperation to build a more perfect quality assurance system. In the traditional education system, quality assurance mainly depends on the internal teaching evaluation and supervision mechanism. In the mode of integration of industry and education, because of the participation of enterprises, a more comprehensive quality assurance mechanism can be established.

In clarifying cultivation objectives, the comprehensive approach of system science can be used, and the cultivation objectives of skilled personnel can be carried through the entire evaluation system. By setting up clear evaluation indicators, the comprehensive quality of students in the industry-teaching integration environment can be assessed comprehensively. At the same time, these indicators must be quantifiable and operable to ensure the objectivity and accuracy of the evaluation. System science theory emphasizes comprehensiveness and wholeness, so it is necessary to consider both the qualitative performance of students and introduce quantitative data for assessment in the evaluation system. This can be done by designing comprehensive evaluation items, including actual case analysis, project practice, thesis writing, etc., while combining quantitative indicators such as skill assessment scores and practical operation data, in order to comprehensively reflect the cultivation of skilled personnel. This kind of comprehensive evaluation can not only fully utilize the advantages of system science, but also ensure the scientific and objective nature of the evaluation results. In addition, system science also focuses on emphasizing cyclic feedback and dynamic adjustment. Therefore, in the industry-teaching integration model of skilled talents, the evaluation system should have a timely and effective feedback mechanism.

Establishing the relationship between the name of resources, operator grade, and type of operation skills can provide the basis for the classification and integration of teaching resources in information technology. In this paper, the knowledge graph is used to build the relationship between the name of teaching resources and the grade of operator and the type of operating skills, which provides the basis for the classification and integration of resources [21].

Informational teaching resources are stored in the file server, through the metadata resource information stored in the Mysql database to achieve the management of teaching resources call, the classification and integration method designed and implemented in this chapter is essentially a classification and integration of resource information stored in the Mysql database to complete the classification and integration of resources, from the Mysql database to obtain resources to be classified integration of resource information from the Mysql database, and finally save the classification and integration results in the Mysql database through the metadata structure. Object-relational mapping (ORM) can complete the conversion between program objects and database data, solving the mismatch between object-oriented and relational databases [22]. Resource extraction in this paper uses Peewee technology, Peewee is a lightweight ORM framework implemented in Python language.

The name of the resource is not all in line with the format of the knowledge graph entity, which may contain irrelevant information such as resource format, letters, numbers, symbols, etc., and at the same time there is a garbled resource name, for this type of content to carry out the pre-processing of the resource name, to clean the irrelevant information, and to improve the efficiency of the program operation.

The name of the resource has been preprocessed, the construction of the knowledge graph has been completed, the necessary information required for the classification and integration of resources have been available, the classification and integration of resources through the name of the resource to match the knowledge graph in the operation of the process entity, through the existence of a target relationship with the entity of the classification results of the classification and integration of resources.

After the classification and integration of resources, they have new attributes, and the original metadata structure in the database can no longer store the classified and integrated resources, so it is necessary to re-design the metadata structure, and store the results of classification and integration in a persistent manner.

For the industry knowledge graph, the industry terminology and industry data are relatively clear, and a top-down approach can be used to construct the knowledge graph, which first determines the data model of the knowledge graph, and then supplements the data according to the framework agreed upon in the data model to complete the construction of the knowledge graph [23].

The design of the knowledge graph for the classification and integration of teaching resources is mainly composed of three parts: entities, entity relationships, and entity attributes.

Unstructured teaching resources are stored in file servers, and their basic information, such as file name, file size, resource format, resource source, creation date, file server storage location, etc., are stored. are stored in the Mysql database, in order to carry out the classification and integration of the resources, the first step is to extract the resource information from the Mysql database as a program object before it can be processed.

In this method, the object-relational mapping technique of ORM is used to convert the resource information in the Mysql database into classes in the program, and each piece of resource information is an object, and the correspondence between the resource information and classes in the database is shown in in Table 1.

The processing of resource names is mainly a cleaning process to remove the resource format, punctuation, spaces, alphanumeric, and other disturbing information contained in the resource names. Part of the pseudo-code for the program design is shown below [24].

Direct entity matching of knowledge graph using resource names can accomplish the classification and integration of resources. In order to match the options that match the target resource name from the knowledge content of the multi-objective talent cultivation model. Based on the specialized knowledge of talent cultivation models, a Chinese similarity matching algorithm based on AC automata and word frequency has been designed for entity matching.

The implementation of the algorithm is based on tire tree construction, and the specific steps of the Chinese similarity matching algorithm based on AC automata and word frequency are shown in Algorithm 1.

Algorithm 1 Chinese similarity matching algorithm based on AC automata and word frequency

Input: short Chinese text string to be matched (the following algorithm is called string 1)

Output: the most matching short text string

Step1 performs word splitting, iterates over the words, and matches all the results containing words from the name of the talent development model process (Note 1).

Step2 the results are saved in a Hashmap with the talent development model process name as the key and the value as the number of word matches in the string.

Step3 If there is no result in the Hashmap at this time, jump to Step6, if there is a unique result with the largest value result in the Hashmap, then the unique result is used as the most matching short text string, jump to Step5, and otherwise proceed to Step4.

Step4 calculate the similarity between string 1 and multiple strings by Edit Distance Algorithm (Note 2), take the result with the highest similarity, if the result is unique, take the unique result as the most matching short text string and jump to Step5, otherwise jump to Step6.

Step5 returns the most matched short text string.

Step6 returns the empty result.

The solution flowchart of this algorithm is shown in Fig. 2.

Figure 2.

Algorithm solution process

After classifying and integrating the resources through the knowledge graph, the next step is to store and manage the information of the classified and integrated resources. Metadata is an important data structure in resource management, through the structured metadata the information of informatization teaching resources is stored in Mysql database, the program can complete the management of resources call through the resource information in metadata, the classification and integration of resource information is also completed the classification and integration of informatization teaching resources. The metadata data structure is shown in Table 2.

For the test of the overall effect of innovation and entrepreneurship, this study takes the main quality points required in the process of innovation and entrepreneurship as the test indexes, and a total of 14 quality points are designed in this study as the main indexes for the test of the effect of innovation and entrepreneurship education. After determining the test indexes, this study designs a questionnaire based on these 14 indexes using Likert scale to measure and test whether the students’ own innovation and entrepreneurship ability is improved before and after the course is taught. The Likert scale of the questionnaire for evaluating the cognitive level of innovation and entrepreneurship ability of higher vocational students is shown in Table 3. Among them, each index is designed with five grades as follows: 1 point (very unresponsive), 2 points (unresponsive), 3 points (average), 4 points (responsive), and 5 points (very responsive). When conducting the assessment, students can score based on the current degree of compliance with their innovation and entrepreneurship ability.

Next, this study carries out the validity test of the “questionnaire for evaluating college students’ cognition of innovation and entrepreneurship”, and the statistics of the validity test indexes of the questionnaire for measuring the cognition of innovation and entrepreneurship of higher vocational students are shown in Table 5. From the results of KOM test and Bartlett’s test of sphericity of the questionnaire, it can be seen that the validity test is effective, and through the test, the questionnaire can be used for the next step of the study.

Figure 3.

The number of people who are innovative and entrepreneurial

After the integration of teaching resources of the innovative and entrepreneurial education talent cultivation model using the method in section 2.2, this section analyzes the teachers’ use of optimized teaching resources.

Figure 4.

Common information digital resource type

Figure 5.

The most needed information teaching resources for teachers

There are many factors influencing the effective application of digital teaching resources, and the main factors influencing the application of information technology teaching resources are shown in Figure 6. As can be seen from the figure, teachers’ IT application abilities and teaching skills are the most critical factors affecting their use of digital teaching resources, accounting for 83.5%. Teachers with strong information technology application skills can find many digital teaching resources they need with their own cell phones, find ways to integrate information technology with the curriculum, and are also able to apply the information technology teaching mode in the classroom to bring students into the information technology classroom. In addition, training in the application of digital teaching resources, students’ acceptance of and cooperation with digital teaching resources, the degree of matching between resources and teaching materials, the quantity and quality of resources, the unified resource management platform, the informationized teaching mode and method, the school’s guiding and incentive mechanism, the adequacy of hardware and software equipment and the network access conditions, and the teaching methods and habits of teachers are also factors affecting teachers’ application of digital teaching resources. Teachers’ use of digital teaching resources is also a factor that affects their use of digital teaching resources.

Figure 6.

The main influencing factors of informationization resource application