# Innovation of Network Ideological and Political Education in Universities Facing the New Era of Internet 5G

Authors: Yi Zhao
Journal: Mathematical Problems in Engineering
 (2022)

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## Abstract

Relying on the reform of the learning field curriculum system of ideological and political education courses in colleges and universities, the association rules between data mining and soft computing technology are used to mine the association relationship between the software professional courses of the department, and the ideas and methods of optimizing the course setting are proposed. Several approaches for analyzing difficulties in the reform and development of ideological and political education in colleges and universities, as well as proposing improvements and optimization strategies, have been offered. The countermeasures to improve the effectiveness of ideological and political education in universities are proposed to solve the timeliness problems of ideological and political education reform in colleges and universities. Here the 5G network can get initialized. Then, the input education details are preprocessed, and the clustering of the educational information is performed by using the hybrid fuzzyK-means approach. Then, the features can get extracted by using the extensibility ant component analysis. Then, the impact was evaluated by using the mixed ensemble approach. Then, after checking the information viability, it can be stored in the database for further analysis. Then, the viable information can be sent to the student ID through improved TCP. The findings demonstrate that the mechanism presented exceeds the other algorithms examined, by expressing high accuracy especially concerning viable education information generation and transmission.


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## Body

## 1. Introduction

The number of students in the college is expanding as the attendance ratio of colleges and universities expands, and the dispersion of scores obtained is getting increasingly complex. Conventional student scores can only give basic digital processing data like simple searches and statistics. It carries with it information. What influence does the relative order of almost any two programs have on studies on the success of political and ideological educational reforms? For example, which of the leading courses, if any, will have the biggest impact on the next class after it is learned? The instructor must determine the relationship between the prior course and the following course using the same method as before, based on the student’s grade distribution, and make course planning decisions appropriately. As a result, it is critical and practicable to identify the key laws or structures of courses’ hidden patterns using appropriate techniques in order to provide decision-making assistance. People’s ideological and behavioral ideals have shifted as a result of society’s rapid growth and major changes. This covers the detrimental consequences of globalization on people’s moral ideals. University students are the most affected since they are in a vital period of steady improvement of their ideological and moral conceptions. University students are the foundation of the human resource department since they are high-knowledge organizations. Their ideology and moral standards have a direct impact on whether they succeed or fail. This has some exemplary and good implications for increasing people’s general quality of life and constructing a peaceful socialist system.The twenty-first century will be characterized by fast expansion. The channel’s use has also spread beyond high-level, new, and complex scientific and technology disciplines to all facets of society, affecting households. With its benefits of simplicity, quickness, inclusivity, interactivity, and massive information, networking has also been a representation of the “4th generation communication.” However, this will not imply that new media has reached its limit because no new media will emerge. The introduction and wide applications of Internet media, on the other hand, have given additional fuel to the development of multimedia technology. This is demonstrated by the creation and growth of the most diverse and unique media in the “4th generation communication,” specifically, streamed media. Network multimedia teaching has emerged as a new and essential educational paradigm in the education field as a result of the widespread introduction of the Internet and the progress of instructional media. It is a mix of networking and media education, as well as a mechanism enabling multimedia teaching to propagate across the network. One of the main purposes of campus network design is to use the network system or network connection to develop multimedia teaching. The school’s teaching techniques will be more varied, the educational model will be more sophisticated, and the campus will be larger as a result of the network instructional media. Numerous colleges and organizations are now researching and developing remote access teaching platforms, and many related products have been established. The majority of these network platforms for remote learning are in the format of “network online schools.” Teaching content can be graphically shown in a variety of formats, including videos, sound, and electronic course materials, using media streaming technologies. Multimedia computers can be accessed remotely by students. Following the class, you can use apps like Star Scream Multimodal Network Classroom, Seth Multimodal Networking Classroom, and I Class Media Networks Lecture hall to learn on your own time. Teacher creates course-related audiovisual courseware and submits it to the “net online course.” Learners can study at any time by browsing online; if they do not understand something, they can leave a note on a non-real-time BBS in writing or voicemail. In order to more quickly identify the effects of learning and teaching, virtual online classrooms also can perform online assessments, professors can leave relevant assignments Internet, and learners can practice and register scores throughout online learning. It also has the ability to control user authorizations. Colleges and universities are increasingly adopting this type of integrated “network virtual classroom.”Therefore, the main focus of this article is on the reform of the modern teaching system of ideological and political education in colleges and universities, as well as an examination of the educational system. This paper tries to build a structured methodology for the ideological education of college students and the evaluation of the education systems. Here the 5G network can get initialized. Then, the input education details are preprocessed, and the clustering of the educational information is performed by using the hybrid fuzzyK-means approach. Then, the features can get extracted by using the extensibility ant component analysis. Then, the impact was evaluated by using the mixed ensemble approach. Then, after checking the information viability, it can be stored in the database for further analysis. Then, the viable information can be sent to the student ID through improved TCP.The remainder of this work is laid out as follows. Section2 discusses similar work. Section 3 discusses the issues and challenges faced by university students’ political and ideological learning in a 5G network. Section 4 discusses political and ideological education solutions for college students in a 5G network. The work is concluded in Section 5 with suggestions for future research.


## 2. Related Work

Experience overviews, theoretical analyses, and empirical research are some of the alternative strategies for improving ideological and political education at universities; one suggestion is to create a “final three environmental” ideological and political education system for universities and colleges [1]. It summarizes and reflects on current political and ideological Chinese universities, reveals the true importance of cultivating educators based on cultural self-confidence through curriculum setting, examines the relationship between college English language curriculum setting and political or ideological schooling, and suggests a path forward to improve significance 2, 3. The AI-IPL technique is used to help college students develop their intellectual and political views while also providing them with physical and emotional support. As a result of the AI-IPL technique, there are differences of opinion among certain students, and these differences define the IPL of the ultimate inclination towards new strategy and psychological education approach [4]. The examination of highly cited articles clarifies the key points of study in this area. To better understand the research process in China’s professional ethics education area, this article analyzes phrase co-occurrence to uncover the most pressing problems and time zone distributions to expose the field's historical background. To bridge one crisis to the next, recovery is a critical step in capital formation. Neoliberal reformers use crises to push privatization as a means of restoring the economy. Neoliberals place the burden of recovery on schools, instructors, and students instead of owning up to their role in generating crises.There is a strong appeal in this article for social justice activists, critical educators, and communities that have experienced crises to reject neoliberal notions of recovery and assert the collective power to end capitalism's inextricable cycle of crises and recoveries [5, 6]. This paper advances technology in the way of thinking, method of supervision, and educational mode of thought, emphasizing the role of ideological and political education workers in increasing data knowledge, improving the way of thinking, fully grasping big data analysis techniques, preparing for the big data era, groping in political and ideological schooling of law, and enhancing the quality of ideology and continuously improving their overall quality and professional skill set; they have been the driving force behind China's economic and social growth. There is an urgent need to address the theoretical and instructional needs for improving teaching practice in the present curriculum and reformation of political and ideological programs at colleges and universities. The use of computers and the Internet in learning and practice has grown in popularity. Depending on constructivist theory [7], this article utilizes computer-assisted political and ideological education services to expand avenues for political and ideological training and to support its productive and resilient growth [8].(a)
The virtualization platform supports normal migration of virtual servers, which is critical for the availability of the virtualization platform.(b)
The cloud computing simulation platform's primary purpose is to conduct fundamental correlation studies and so on.(c)
Through the incorporation of a supercomputing framework, the online guidance system is optimized [9]. This article offers a technique of interactive information processing in several modes for use in an online education system for ideological and political courses. We organize and conduct online learning courses using live broadcasting and communication processes, and we have knowledge about the world and practice online live broadcasting, internet question answering, discussion groups, bullet display interaction, real-time communication, as well as other teaching methods in order to achieve a genuine and effective educational impact [10]. Students and teachers collaborate in the political and ideological theory section of the course omnidirectional classroom instruction, thus strengthening theory learning, researching education, practice education, and networking education. JSP has been increasingly widely used in all types of JSP applications as an excellent dynamic web page programming language [11].


## 3. Proposed Methodology

The proposed methodology is for college students’ ideological education and the assessment of educational systems. The initialization of the 5G network can be done here. The input educational data are then preprocessed, and the educational information is clustered using a hybrid fuzzyK-means technique. Then, using the extensibility, the features can be extracted using ant component analysis. The impact was then evaluated using a mixed ensemble method. The information can then be retained in the database for subsequent study after it has been checked for viability. Then, using an upgraded TCP, the viable information may be sent to the student ID. The schematic representation of the suggested methodology is shown in Figure 1.Figure 1
Schematic representation of the suggested methodology.


### 3.1. Data Processing

The incoming data are unprocessed and may include duplicate packets and partial data. It has been cleaned and highly processed to eliminate repeated and duplicate occurrences, as well as missing data. Because the databases for the educational system are so large, sample reduced size techniques must be employed. Due to a large number of features in this dataset, extracting feature techniques are needed to eliminate irrelevant characteristics. The information may be normalized during the preprocessing step. The first stage of the normalizing process generates the s-score, which is defined by(1)S=Rs−δω,where δ represents data and φ represents standard.S is written as(2)S=Rs−R¯sSSD,where Rs¯ represents sample and SSD represents the sample standard deviation.The randomized sample is composed of(3)Si=β0+β1Rsi+εoi.Hereεoi is the error based on ω2.After that, the mistakes must be independent of one another, as follows.(4)ri∼Wrr2+w−1,where ri represents random variable.Following that, the standard deviation is used to standardize the variable’s changes.The moment scaling deviation is estimated using the following formula.(5)MSD=λmsc∅msc,where msc represents moment scaling.(6)λmsc=ExpRi−α^MSC,where Ri represents random variable and Exp represents expected value.(7)∅ms=ExpRi−αMSC2,rc=mscRi¯,where rc represents the variance of coefficient.By setting all variables to 0 or 1, the process of feature scaling is stopped. This is referred to as the unison-based normalizing procedure. The following is how the normalized equation would be expressed:(8)Ri′=r−rminrmax−rmin.Once the input has been normalized, the range and inconsistency of the data may stay constant. This phase’s objective is to minimize or eliminate data latency. The normalized data may then be used as an input to subsequent steps.


### 3.2. Clustering Using Hybrid FuzzyK-Means Approach

The data mining approach, i.e., hybrid fuzzyK-means clustering, is best suitable for the chosen dataset and is better than any other data mining approach because the college students’ interactional behavior is heterogeneous in nature, so it is necessary to form tighter clusters of students with similar interactional characteristics. In clustering, n samples are divided into k categories, where each input attribute belongs to one cluster and it may not be a part of other clusters. When the teacher evaluates the students, he can set up and complete the clustering based on the excavated information.The following steps are carried out forK-means clustering.(1)
Initialize starting condition by defining the number of clusters and randomly selecting the initial cluster centers. The Euclidean distance is used to observe the distance between the attributes:(9)da,b=a1−b12+a2−b22+…+an−bn2+i.e=∑i=1nai−bi2,wherea, b are the two points in the Euclidian space and d represents distance.(2)
Generate a new partition by assigning each data point to the nearest cluster center.(3)
Recalculate the centers for clusters receiving new data points and for clusters losing data points.(4)
Repeat steps 2 and 3 until a distance convergence criterion is met.


### 3.3. Feature Extraction

In order to determine which feature extraction method can improve clustering on 5G network connection data, the feature extraction method extracts new features from original dataset, and it is very beneficial when we want to decrease the number of resources required for processing without missing relevant feature dataset. Feature extraction can also decrease the number of additional features for an offered study. Feature extraction produces a remarkable transformation of first features to create more significant features. Feature extraction is a process for creating new features that depend on the original input feature set to decrease the high dimensionality of the feature vector.The transformation method is done by algebraic transformation, and according to some optimization criteria, feature extraction has the ability to handle essential information during dealing with high dimensional issues. These dimensionality reduction techniques aim to not lose a large amount of information during the feature transformation process by conserving the original relative distance between features and cover the original data potential structure.


### 3.4. Improved TCP Algorithm

The framework as a learning system is the direction of intellectual and social workers in the teaching practices adopted. It is a critical aspect of the ideas, hypotheses, and technical directions of IPL, including extreme social and academic concepts. The framework is the expert of theoretical and political education theories to produce improvements of thought, actions, and expression. The education governance framework is divided into knowledge-based reasoning, political education framework, and instrumental ideological framework. The framework of administration and the model of observation are represented asS1 and S2. The resemblance between the databases of the college students in the IPL is shown in the following equation:(10)Rs=2mS1+S2mS1+mS2,where m denotes the number of the module and is the resemblance between the database of college students. The data distribution between the IPL is shown in the following equation:(11)D=Rs∗K+L∗m∗mS1+mS2.Here, is the role of human interest and is the sense of tasks has blurred in an educational system, ideological and political education as a way of supplying countries in need of liberation, as opposed to the essence of IPL. The knowledge-based framework of ideological and political learning is an academic framework that correlates with defining the unreasonable development of a wisdom-based economy, which has lost its fundamental position in learning in life, and it is shown in the following equation:(12)Rs=αfmrR1+R2mr−1+R1mr−1+R2.The system is applied to the teaching of political and ideological courses in a freshman class at universities, to further clarify its application effect. There are 53 students in this class, and the ideological and political course conducted is the ideological and moral foundation and legal cultivation. In the teaching of this course in this class, the traditional teaching methods and the one using computer simulation systems for ideological and political teaching are adopted in this study. Then, a questionnaire survey is used to count the attitudes towards political and ideological courses of students and their mastery of ideological and political knowledge. The questionnaires used in this study are analyzed from the students’ attitudes towards political and ideological courses, the degree of satisfaction with classroom teaching, the acceptance of political and ideological courses, and their own learning situation. There are 4 question options for each part, and Likert’s five-point scoring method is adopted. The higher the score, the higher the acceptance to political and ideological courses, based on which the application of computer simulation systems for political and ideological teaching can be judged.


## 3.1. Data Processing

The incoming data are unprocessed and may include duplicate packets and partial data. It has been cleaned and highly processed to eliminate repeated and duplicate occurrences, as well as missing data. Because the databases for the educational system are so large, sample reduced size techniques must be employed. Due to a large number of features in this dataset, extracting feature techniques are needed to eliminate irrelevant characteristics. The information may be normalized during the preprocessing step. The first stage of the normalizing process generates the s-score, which is defined by(1)S=Rs−δω,where δ represents data and φ represents standard.S is written as(2)S=Rs−R¯sSSD,where Rs¯ represents sample and SSD represents the sample standard deviation.The randomized sample is composed of(3)Si=β0+β1Rsi+εoi.Hereεoi is the error based on ω2.After that, the mistakes must be independent of one another, as follows.(4)ri∼Wrr2+w−1,where ri represents random variable.Following that, the standard deviation is used to standardize the variable’s changes.The moment scaling deviation is estimated using the following formula.(5)MSD=λmsc∅msc,where msc represents moment scaling.(6)λmsc=ExpRi−α^MSC,where Ri represents random variable and Exp represents expected value.(7)∅ms=ExpRi−αMSC2,rc=mscRi¯,where rc represents the variance of coefficient.By setting all variables to 0 or 1, the process of feature scaling is stopped. This is referred to as the unison-based normalizing procedure. The following is how the normalized equation would be expressed:(8)Ri′=r−rminrmax−rmin.Once the input has been normalized, the range and inconsistency of the data may stay constant. This phase’s objective is to minimize or eliminate data latency. The normalized data may then be used as an input to subsequent steps.


## 3.2. Clustering Using Hybrid FuzzyK-Means Approach

The data mining approach, i.e., hybrid fuzzyK-means clustering, is best suitable for the chosen dataset and is better than any other data mining approach because the college students’ interactional behavior is heterogeneous in nature, so it is necessary to form tighter clusters of students with similar interactional characteristics. In clustering, n samples are divided into k categories, where each input attribute belongs to one cluster and it may not be a part of other clusters. When the teacher evaluates the students, he can set up and complete the clustering based on the excavated information.The following steps are carried out forK-means clustering.(1)
Initialize starting condition by defining the number of clusters and randomly selecting the initial cluster centers. The Euclidean distance is used to observe the distance between the attributes:(9)da,b=a1−b12+a2−b22+…+an−bn2+i.e=∑i=1nai−bi2,wherea, b are the two points in the Euclidian space and d represents distance.(2)
Generate a new partition by assigning each data point to the nearest cluster center.(3)
Recalculate the centers for clusters receiving new data points and for clusters losing data points.(4)
Repeat steps 2 and 3 until a distance convergence criterion is met.


## 3.3. Feature Extraction

In order to determine which feature extraction method can improve clustering on 5G network connection data, the feature extraction method extracts new features from original dataset, and it is very beneficial when we want to decrease the number of resources required for processing without missing relevant feature dataset. Feature extraction can also decrease the number of additional features for an offered study. Feature extraction produces a remarkable transformation of first features to create more significant features. Feature extraction is a process for creating new features that depend on the original input feature set to decrease the high dimensionality of the feature vector.The transformation method is done by algebraic transformation, and according to some optimization criteria, feature extraction has the ability to handle essential information during dealing with high dimensional issues. These dimensionality reduction techniques aim to not lose a large amount of information during the feature transformation process by conserving the original relative distance between features and cover the original data potential structure.


## 3.4. Improved TCP Algorithm

The framework as a learning system is the direction of intellectual and social workers in the teaching practices adopted. It is a critical aspect of the ideas, hypotheses, and technical directions of IPL, including extreme social and academic concepts. The framework is the expert of theoretical and political education theories to produce improvements of thought, actions, and expression. The education governance framework is divided into knowledge-based reasoning, political education framework, and instrumental ideological framework. The framework of administration and the model of observation are represented asS1 and S2. The resemblance between the databases of the college students in the IPL is shown in the following equation:(10)Rs=2mS1+S2mS1+mS2,where m denotes the number of the module and is the resemblance between the database of college students. The data distribution between the IPL is shown in the following equation:(11)D=Rs∗K+L∗m∗mS1+mS2.Here, is the role of human interest and is the sense of tasks has blurred in an educational system, ideological and political education as a way of supplying countries in need of liberation, as opposed to the essence of IPL. The knowledge-based framework of ideological and political learning is an academic framework that correlates with defining the unreasonable development of a wisdom-based economy, which has lost its fundamental position in learning in life, and it is shown in the following equation:(12)Rs=αfmrR1+R2mr−1+R1mr−1+R2.The system is applied to the teaching of political and ideological courses in a freshman class at universities, to further clarify its application effect. There are 53 students in this class, and the ideological and political course conducted is the ideological and moral foundation and legal cultivation. In the teaching of this course in this class, the traditional teaching methods and the one using computer simulation systems for ideological and political teaching are adopted in this study. Then, a questionnaire survey is used to count the attitudes towards political and ideological courses of students and their mastery of ideological and political knowledge. The questionnaires used in this study are analyzed from the students’ attitudes towards political and ideological courses, the degree of satisfaction with classroom teaching, the acceptance of political and ideological courses, and their own learning situation. There are 4 question options for each part, and Likert’s five-point scoring method is adopted. The higher the score, the higher the acceptance to political and ideological courses, based on which the application of computer simulation systems for political and ideological teaching can be judged.


## 4. Result and Discussion

When all users check in to the system, how does it work (Figures2–6)? It demonstrates that as the number of users increases from 10 to 500, the ideological and political education systems are able to display the PPT uploading, upload time, and course content normally.Figure 2
The system’s highest response time while serving the most concurrent users.Figure 3
Questionnaire score for improved TCP teaching system.
(a)(b)(c)(d)Figure 4
Median scores and disparities in the four aspects of political and ideological teaching statistics.Figure 5
The impact of the political and ideological method in practice.Figure 6
The enthusiasm of teachers to adopt the political and ideological teaching method.


## 5. Conclusion

This study focuses on the reform of political and ideological teaching and tests the performances and functions of the constructed system. At the same time, a questionnaire analysis method is used to evaluate the improved TCP for political and ideological teaching. The created system’s political and ideological courses courseware management, online discussion, and classroom feedback management functions can be used regularly on both the instructor and student terminals. In addition, the application effect of the system in actual teaching is relatively good. In the questionnaire analysis score, the score of the political and ideological teaching model using the proposed system is 0.76 points higher than the score using the traditional method. Therefore, the improved TCP based on the proposed system can effectively better the students’ attitudes towards political and ideological courses, improve the degree of satisfaction and acceptance of classroom teaching, and promote the mastery of ideological and political knowledge. This paper contributes to the intelligent development of ideological and political classroom teaching and has high practical application value and significance.



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*Source: 7439862-2022-06-25.xml*