97B20Telling the Multiple Logics of Common Wealth in Ideological and Political Courses in Colleges and Universities

Common wealth is the essential requirement of socialism. Speaking about common wealth in ideological and political education in colleges and universities helps to strengthen the ideological consensus of young students. Education is the cornerstone of national rejuvenation and social development, and colleges and universities shoulder the important responsibility of directly conveying newcomers of the times for the country [1-3]. In the new journey of realizing common wealth, it is especially important to play the function of political guidance and thought leadership of ideological and political education in colleges and universities. As an important guarantee for the continuous cultivation of vital forces for the construction of socialism with Chinese characteristics in the new era, ideological and political education in colleges and universities needs to talk about common wealth and live common wealth, so that young students have an accurate understanding of the central task of the country, and strive to grow up to be the new man of the times who can take on the important task of national rejuvenation [4-6]. In the ideological and political education of colleges and universities, to talk about common wealth is a rational call to follow the theme of the times, and it is based on the realistic needs of social development.

Comprehensively improving the quality of higher education talent training requires further enhancing the consistency between social demand and talent training, and common wealth is the kernel of social demand. Under the guidance of the theory of common wealth, higher education can more accurately connect with the society, enrich the professional categories and improve the training program from the demand, strengthen the theoretical teaching through practical teaching, realize the smooth transition of talents from school to society, and ensure the efficient operation of the collaborative system of government, industry, academia and research [7-9]. Ideological and political education is an important way for colleges and universities to implement the fundamental task of establishing moral character, and it is also a foothold for the integration of common wealth into higher education. Speaking of common wealth in ideological and political education in colleges and universities is not only of great significance to the promotion of high-quality development of education, but also capable of providing new ideas and injecting new content into the construction of ideological and political programs in colleges and universities. In the excellent traditional Chinese culture, we can see the flashing ideological glory of common wealth, and its evolutionary trajectory shows a certain degree of continuity, condensing valuable national wisdom, with rich ideological connotations, which provides important spiritual resources for ideological and political education in colleges and universities, and adds a lot of profound and vivid educational materials for ideological and political education in colleges and universities, which helps to enhance the ideological, theoretical, and proximity of ideological and political education classes [10-12]. At the same time, the common wealth also has the attribute of development, colleges and universities as a combination of theoretical excavation and practical exploration of the front line, through the “theory practice theory” transformation, for the further enrichment of the scientific connotation of the common wealth to provide a living force. Ideological and political education in colleges and universities plays an important leading role, ensuring the basic direction of the theoretical excavation and the main goal of practical exploration of common prosperity in higher education, which is an important bridge to communicate between theory and reality, the present and the future, and the society and the school [13-15].

In this paper, we first sorted out the path of speaking common wealth ideology in ideological and political classrooms of colleges and universities, constructed the evaluation index system of common wealth ideology from three aspects of knowledge understanding, application and migration, and took “willingness to accept” and “sense of access” as the mediating effect variables. The two aspects of “willingness to accept” and “sense of access” are taken as the mediating effect variables of the evaluation index system. Next, the normalization of the data is completed before the data preprocessing, and the importance of the characteristics of the evaluation subject is estimated based on the random forest algorithm, which is an important basis for the selection of indicators. Subsequently, data preprocessing, determining the structure of the ID-CNN-based evaluation model of the common wealth ideological identity, adopting the mean square error to measure the predicted and true values of the indicators, and deciding the coefficient to maintain the fit of the model were carried out in sequence. Finally, an evaluation system for teaching common wealth identity in colleges and universities is established, and empirical measures are conducted to measure the common wealth understanding identity and acceptance willingness of college and university students. From the teaching effectiveness as well as students’ learning attitudes, it reflects the teaching effect of speaking the concept of common wealth in the Civics program in colleges and universities.

2

The Path of Speaking Good Common Wealth Thought in Ideological and Political Courses of Colleges and Universities

2.1

Enhance the level of ideological cognition and deeply explore educational materials

On one hand, teachers of Civics should continue to learn and master the contemporary meaning and important value of the concept of common prosperity, and enhance their understanding of the concept of common prosperity. On the other hand, teachers should further explore and integrate cases and materials embodying the idea of common prosperity in the Civics teaching materials, and integrate the idea of common prosperity into all aspects of teaching. At the same time, they should actively innovate the form of teaching, and utilize modern information technology to collect and integrate relevant teaching resources, so as to make students further understand the achievements of common wealth at the present stage, and to improve the interest of the Civic and Political Science class.

2.2

Innovate the way of Civic and Political Education and spread the idea of common wealth

First, we need to build a discourse system of “Great Civic and Political Science Class” to support the integration of the idea of common wealth in the Civic and Political Science Education, taking into account the characteristics of different students. With the development of society, students’ individuality is obvious, teachers should completely change the traditional didactic teaching, and flexibly integrate the idea of common wealth into the teaching of Civics and Political Science, so as to cultivate students’ interest in learning. Secondly, teachers should take advantage of the new era of network information technology to build an online platform for Civic and Political Education, and build a communication matrix integrating microblogging, microblogging and micro-video, so as to publicize the idea of common wealth. For example, the idea of common prosperity can be integrated into the campus culture construction, set up a student preaching team, declare the common prosperity idea research topics, and teachers can use online and offline hybrid teaching methods to strengthen the teaching innovation of the common prosperity idea.

2.3

Cohesion of the educational forces of all parties and construction of a collaborative pattern of educating people

Integrating the idea of common prosperity into civic and political education requires schools to strengthen cooperation with other educational forces, integrate resources from all sides, and form a synergy of educating people, so as to speak well of the idea of common prosperity. Specifically, schools can combine the advantages of the discipline of Civics and Political Science to offer practical courses on Civics and Political Education on the topic of common prosperity, invite famous experts and scholars to schools to carry out thematic lectures, and discuss and exchange with students the contemporary value and connotation of the idea of common prosperity. Strengthen cooperation with social organizations, and organize teachers and students to watch the results of the construction of the Common Wealth Demonstration Zone, so that they can experience and understand the realization path of the idea of common wealth. Organize class meetings on the theme of “Realizing Common Wealth”, where teachers and students discuss the social mission of teachers and students in the context of common wealth, and so on. Schools should mobilize teachers, social scholars, social organizations, and institutions to spread the idea of common prosperity in a multi-dimensional and diverse manner.

3

Construction of the evaluation system for teaching the idea of common wealth

3.1

Preliminary construction of evaluation indicators

3.1.1

Construction of first-level evaluation indicators

The development of students’ ability to “cognitively recognize the concept of common prosperity” is mainly based on their understanding, application and transfer of existing experience and knowledge. In the study of ideological and political subject ability based on students’ core literacy, some scholars have specifically operated the discipline ability into three dimensions: “learning and understanding ability”, “application and practice ability” and “transfer and innovation ability”. Based on the cognitive process of Bloom’s taxonomy of educational goals, combined with the division of ideological and political discipline competency elements and the level requirements of cognitive literacy of the concept of common prosperity, this study divides the first-level indicators of cognitive literacy of the concept of common prosperity into three first-level evaluation indicators: “learning and understanding”, “application practice” and “transfer and innovation”.

The first indicator represents the understanding of common and diverse ideas. The second indicator reflects the ability of students to understand their own understanding, and should be analyzed in the actual case. The third indicator reflects whether students can integrate and apply their understanding of common prosperity to other concepts.

3.1.2

Construction of secondary evaluation indicators

On the basis of the initial definition of the level of “reasoning and cognition” literacy after the classification of the indicators of the first level of evaluation, the indicators of the second level of evaluation and their specific requirements have been classified on the basis of the criteria for the evaluation of the first level of indicators. The second-level indicators under the dimension of “learning and understanding” are collecting information, categorizing information, identifying concepts, and interpreting and applying them. The secondary indicators under the dimension of “application and practice” include reasoning, analyzing data, inferring and predicting, and combining quantitative and qualitative aspects. The dimension of “transfer and innovation” includes constructing mind maps, transferring knowledge, and innovative thinking.

3.1.3

Mediating effects

This paper uses the S-O-R model as the theoretical model constructed in this study. The essence of college students’ success in identifying with the concept of common wealth in ideological education is the process of S (stimulus)-O (individual)-R (response). The psychological state of “individual O” as a mediator variable is mainly manifested in the two aspects of “willingness to accept” and “sense of acquisition” in the course teaching. This model can effectively analyze the cognitive state of students and take into account the individual differences of students.

3.2

Establishment of the evaluation system for the quality of common affluent teaching in colleges and universities

Data preprocessing is an important step for data analysis. This study will produce certain null values in the process of enriching the sample set, firstly, the median is used to fill in the missing values, secondly, the course number data are removed, then the features are divided into values, and the individual data are to be normalized before discretization, and finally, the dataset used in this chapter is formed. The normalization formula is as follows: (1) $X = \frac{x - \min}{\max - \min}$

Where X is the normalized value, x is the initial value, min is the minimum value and max is the maximum value.

Random Forest is an integrated learning algorithm based on a tree model that progresses through the layers from the root node to the leaf nodes, thus enabling fast decision making for complex problems. All data will eventually fall to the leaf nodes, which can be used for both classification and regression problems. The construction of the decision tree consists of a training phase and a testing phase, in which the focus is on the training phase, mainly for feature selection, generating the decision tree by recursion, simplifying the decision tree by branch reduction, and preventing overfitting.

The main algorithms for decision tree feature selection are information gain (ID3), information gain rate (C4.5), and CART. The first two use entropy as a measure, and the CART algorithm uses the GINI coefficient as a measure. Random forest method uses CART tree as base learner and Gini index to indicate the level of confusion. If there is K classification and the chance of a sample point belonging to the k nd classification is said to be p_k, then the Gini index can be used to characterize this probability distribution: (2) $G i n i (p) = \sum_{k = 1}^{K} p_{k} (1 - p_{k}) = 1 - \sum_{k = 1}^{K} p_{k}^{2}$

The main branches of integrated learning algorithms are Bagging, Boosting and Stacking.Using Bagging integrated learning, the Random Forest method can integrate multiple trees so that multiple classifiers can be trained in parallel and averaged, assuming that the number of tree models is M, which is given by the formula: (3) $f (x) = \frac{1}{M \sum_{m = 1}^{M} f_{m} (x)}$

In the paper, a way of evaluating the importance of features based on random forests is given, which uses the Gini index, which calculates the amount of contribution of each feature on different decision trees and normalizes it to assess the importance of features. This approach can effectively help us to better understand the importance of features and can be ranked according to the amount of contribution to better evaluate the value of features.

The feature importance score is denoted by VIM. Feature importance can be measured by calculating the amount of change in the mean value of each feature A_j in a random forest, i.e., the Gini index score $V I M_{j}^{G i n i}$ , which allows an assessment of the feature’s impact on the classification accuracy of the random forest. Assuming that there are J t features A_j(j = 1,2,...,J) and t decision trees T_i(i = 1,2,...,t) and considering K categories, feature importance can be evaluated by $V I M_{j}^{G i n i}$ identifying the nodes in the random forest more accurately. In this process, the impurity of the nodes q of the i th tree is estimated using the Gini index as follows: (4) $G i n i_{q}^{i} = 1 - \sum_{k = 1}^{| k |} {(p_{q k}^{i})}^{2}$

In Eq. K represents K categories and p_qk denotes the proportion of category k in node q.

The importance of feature A_j in node q of tree i, i.e., the difference in Gini index of node q before and after branching is: (5) $V I M_{j q}^{(G i n i) (i)} = G i n i_{q}^{i} - G i n i_{i}^{i} - G i n i_{r}^{i}$

In Eqs. $G i n i_{i}^{i}$ and $G i n i_{r}^{i}$ each represent the Gini indices of the two new nodes after branching.

If feature A_j is used as a node of set Q in decision tree T_i, then the importance of A_j in the ith tree can be expressed as: (6) $V I M_{j}^{(G i n i) (i)} = \sum_{q \in Q} V I M_{j q}^{(G i n i) (i)}$

If there is t tree in a random forest, then the importance of feature Aj in this forest can be expressed as: (7) $V I M_{j}^{(G i n i)} = \sum_{i = 1}^{t} V I M_{j}^{(G i n i) (i)}$

By normalizing the obtained importance evaluation, the importance feature can be obtained, denoted as: (8) $V I M_{j}^{(G i n i)} = \frac{V I M_{j}^{G i n i}}{\sum_{j' = 1}^{J} V I M_{j'}^{(G i n i)}}$

This study adopts the random forest method to assess the importance of the features of multiple evaluation subjects, and to assess the importance of the first-level indicators of expert evaluation separately, as a component of the construction of the indicator system as well as the basis for the screening of the features in the subsequent network model.

3.3

ID-CNN-based cognitive evaluation model of common wealth in colleges and universities

3.3.1

Data pre-processing

In order to reduce the impact of outliers, this paper uses data normalization to process the data, calculated by the formula: (9) $X^{'} = \frac{x - \bar{x}}{σ}$

Where x is the original value, $\bar{x}$ is the mean and σ is the standard deviation.

In practice, you can directly call the Standard Scaler in the sklearn. Preprocessing library for normalization.

3.3.2

Determining the model structure

The ID-CNN-based model for evaluating the teaching quality of common affluent ideas in college civics classrooms is depicted in Figure 1. This study uses a multi-channel input layer containing a fixed amount of indicator features based on the classical Lenet network. The input layer receives one-dimensional evaluation data as input. The convolution layer extracts local features of the evaluation data by sliding one or more one-dimensional convolution kernels. The pooling layer is used to reduce the dimensionality of the output of the convolutional layer, thus reducing the number of model parameters, and this model uses maximum pooling, where the maximum value within the pooling window is output as the feature value. The fully connected layer is to arrange the feature vectors obtained from the last layer into one-dimensional feature vectors by rows or by columns as a fully connected layer. The output layer is formed by the evaluation data of experts on learning understanding, application practice, and migration innovation.

3.3.3

Indicators for model assessment

The mean square error (MSE) was used as a loss function to measure the difference between the predicted and true values. The coefficient of determination R² is used to measure how well the model captures the amount of information on the data, i.e., the goodness of fit, and the closer R² is to 1, the better the independent variable explains the dependent variable. The correlation formula is as follows: (10) $M S E = \frac{1}{m} \sum_{i = 1}^{m} {| y_{i} - {\hat{y}}_{i} |}^{2}$ (11) $R^{2} = 1 - \frac{\sum_{i = 0}^{m} {(y_{i} - {\hat{y}}_{i})}^{2}}{\sum_{i = 0}^{m} {(y_{i} - \bar{y})}^{2}}$

Where y_i represents the true value of the i nd training sample, while ${\hat{y}}_{i}$ represents the predicted value of the ith training sample, m is the total number of samples, and $\bar{y}$ is the mean.

The smaller the MSE, the more accurate the model fits the sample data: the closer R² is to 1, the better the model fits the data and the better the fit.

3.4

Construction of the evaluation system for the quality of common affluent teaching in higher education institutions

Based on the cognitive evaluation model of common wealth proposed in this paper, the indicators proposed in subsection 3.1 were screened. Three rounds of expert consultation were conducted for the revision of evaluation indicators, and two rounds of expert consultation were conducted for the revision of the level division of secondary evaluation indicators, so that a total of five rounds of expert consultation were conducted for the evaluation indicator system, and the evaluation indicator system for the “Common Wealth Concept Teaching and Learning Cognition” quality was finally determined, as shown in Table 1.

Table 1.

Index system

Primary indicator	Secondary indicator	Indicator
Learning comprehension(A)	Collection data(A1)	1.The students collect relevant information based on common and rich problems
	Collection data(A1)	2.The students are based on the identification of data and the data of the data
	Cognitive understanding(A2)	3.Students know common common affluence
		4.Students know the relationship between common and rich phenomena
		5.Students can understand the common rich idea and explain the specific meaning
Applied practice(B)	Direct inference(B1)	6.Students can conclude with a simple reasoning on a single, dominant common and rich phenomenon
		7.The students analyzed the problem based on multiple evidence
		8.Students can make the correct conclusion based on the transformation and analysis of multiple logic
	Application analysis (B2)	9.Students can choose the right way to deal with the problems of the common rich implementation process
	Application analysis (B2)	10. Students can illustrate the scope of the common rich concept in various situations
Migration innovation(C)	Indirect reasoning(C1)	11. Students can conclude by reasoning reasoning based on complex and implicit evidence
		12. Students can illustrate the relationship between evidence and conclusion
		13.The relationship between the students can be summarized and the conclusion is summarized
	Knowledge transfer(C2)	14.Students can express the idea of common prosperity in a written way
		15. students are based on a reasonable solution to the problem of common prosperity
		16. Students can use common and rich ideas to solve other similar problems

4

Analysis of the Effectiveness of Common Wealth Teaching in Civics Courses

4.1

Students’ understanding of the concept of common wealth and willingness to accept it

4.1.1

Measurement tool design

The purpose of this study is to understand the current status of the education of the concept of common wealth under the teaching of Civics courses in colleges and universities by investigating the college students’ recognition of the concept of common wealth under the teaching of Civics courses in colleges and universities as well as the factors influencing it. The data of the study includes both objective indicators such as gender, grade, school category and specialty of the respondents, and subjective evaluation indicators such as learning attitude, willingness to accept, and sense of access to the teaching of the respondents. In this study, a questionnaire was chosen as the main measurement tool to investigate the basic situation of studying undergraduates’ learning of Civics and Politics courses, supplemented with semi-structured interviews. The questionnaire should be based on the purpose of the study, theoretical framework, and hypotheses, and the questions posed should be able to reflect the topic and theme of the study, and strive to be clear and concise in order to facilitate the respondents’ understanding and answers. In terms of the questionnaire design, this study initially formulated the questionnaire items based on the evaluation model mentioned above, combined with relevant literature and information. Subsequently, the questionnaire was further revised according to the suggestions of relevant experts, and finally, a pre-survey was conducted to improve the questionnaire content based on the feedback from the respondents.

4.1.2

Measuring tool structure and inspection

The design of the questionnaire mainly includes three parts: “basic information of students”, “common prosperity concept identity scale of ideological and political teaching” and “ideological and political teaching influencing factors scale”, the second and third parts of each item are in the form of declarative sentences, and the questions are scored by Likert five-point method, 1 is very inconsistent, 5 is very consistent. Refer to the relevant discourses of “attitude triad”, and also refer to the “Cognitive Needs Scale”, “Learning Emotion Scale”, “Involvement Scale”, “Willingness to Accept Scale”, “Acquisition Scale”, etc. The “Pre-test Scale” is in the form of a five-point Likert scale, and the answer options are “strongly disagree, not compliant, generally agreeable, compliant, very much compliant” and assigned “1, 2, 3, 4, 5”.

4.1.3

Based on the empirical analysis of college students’ understanding and identification of common wealth

1)

Descriptive Analysis

In this section, we will analyze the results of the questionnaire on “the recognition of the concept of common wealth in the teaching of Civics”, which can be concluded that the current college Civics teaching of college students on the recognition of the concept of common wealth. Using the data as a basis, we can give a qualitative description of the university students’ recognition of the teaching of Civics, and grasp the differences in their recognition of the teaching and analyze and discuss them. Figure 2 shows the comparison of the indicators of “Civic politics common wealth concept identity”.

Firstly, we analyzed and compared the concentration (mean) and difference (standard deviation) of the degree of recognition of the concept of common wealth in the teaching of Civics courses in colleges and universities, and the mean score of the six indicators was 3.308, indicating that the degree of recognition of the teaching of Civics courses in colleges and universities on common wealth is at a medium level. Among the six observed indicators, the indirect reasoning identity (M=3.455, SD=0.085) and the utilization analysis identity (M=3.364, SD=0.009) are slightly higher, and the knowledge transfer score is the lowest (M=3.165, SD=0.008), indicating that the college students are slightly satisfied with the indirect reasoning and the utilization analysis part of the teaching of college Civic and Political Science Class, while their knowledge transfer still needs to be strengthened.

The empirical results show that college students have medium degree of identification with the teaching of Civics and Political Science courses in colleges and universities as a whole, in which college students are more satisfied with the indirect reasoning and application analysis of Civics and Political Science courses, while their knowledge transfer is slightly insufficient. In recent years, Civics has received unprecedented attention, major universities have made a lot of practice and exploration in enhancing the effectiveness of Civics, schools continue to improve the learning environment at the same time, Civics teachers have reformed and innovated a variety of teaching modes, problematic, inquiry-based, cooperative, and combined with information technology and other forms of teaching discourse successfully attracted the attention of the students, won the love of the students. However, the results of the survey show that students’ knowledge transfer is slightly insufficient, which indicates that students’ knowledge and behavior are not transformed enough, and the effectiveness of Civic-Concern classes is still far from the expectation, and the medium level of acceptance confirms that there is still room for further improvement of the acceptance of the concept of common wealth in Civic-Concern classes in colleges and universities.

2)

Comparison of the effect sizes of each variable in the model

Through calculation, the effect value of each variable in the model on “agreement” can be obtained, and Table 2 shows the comparison of the effect values of each variable in the model. Among them, the total effect size of “sense of acquisition” on “recognition” was the highest (0.465), followed by “application analysis” (0.239) and “knowledge transfer” (0.165). The effect of each variable on “identity” was as follows: “acquisition > application analysis> knowledge transfer> data collection> direct reasoning> cognitive understanding> acceptance intention >indirect reasoning”.

Table 2.

Compare the variable effect values of the model

Influencing factor		Action path	Direct effect	Indirect effect	Total effect	Normalized effect
Influencing factor	Data collection	Data collection→recognition	0.125	-	0.158	11.40%
		Data collection→Acquired sense→recognition	-	0.026
		Data collection→Accept will→Acquired sense→Recognition	-	0.007
	Cognitive understanding	Cognitive understanding→Acquired sense→Recognition	-	0.084	0.098	7.07%
	Cognitive understanding	Cognitive understanding→Accept will→Acquired sense→Recognition	-	0.014
	Direct inference	Direct inference→Recognition	0.145	-	0.145	10.46%
	Application analysis	Application analysis→Recognition	0.156	-	0.239	17.24%
		Application analysis→Acquired sense→Recognition	-	0.065
		Application analysis→Accept will→Acquired sense→Recognition	-	0.018
	Indirect reasoning	Indirect reasoning→Acquired sense→Recognition	-	0.023	0.032	2.31%
	Indirect reasoning	Indirect reasoning→Accept will→Acquired sense→Recognition	-	0.009
	Knowledge transfer	Knowledge transfer→Recognition	0.165	-	0.165	11.90%
Mediation factor	Acquired sense	Acquired sense→Recognition	0.465	-	0.465	33.55%
Mediation factor	Accept will	Accept will→Acquired sense→Recognition	-	0.084	0.084	6.06%

4.2

Effectiveness of Civics Teaching and Students’ Learning Attitude

4.2.1

Analysis of teaching effectiveness

This study conducted a descriptive statistical analysis of the learning readiness, learning drive, learning plan, learning interaction, learning engagement, strategy application, task completion and learning gain of the learners of the common wealth concept in the Civics education classroom of colleges and universities, and analyzed the effectiveness of the teaching of the Civics common wealth concept to the four grades of the students of the L colleges and universities with the sample of L colleges and universities as shown in Fig. 3. By counting the mean value of each dimension of learners’ learning quality, it can be found that the mean value of the eight dimensions of learners’ learning quality of Civic Common Wealth Concept education with L college as a sample is below 4.00, which, combined with the numerical meaning of the Likert five-point scale, indicates that the average level of the dimensions of the learning quality of learners’ learning quality of the Civic Common Wealth Concept education of the colleges and universities is in the middle level. Taking first-year students as an example, comparing the mean values of the dimensions of learning quality, it can be learned that learners have the highest mean value of strategy application (M=3.85), followed by learning readiness (M=3.8) and learning interaction (M=3.78). Whereas, the mean levels of learning engagement (M=3.45) and learning planning (M=3.33) were lower than the 3.5 level.

4.2.2

Learning attitudes of students of different majors towards the concept of common wealth

Table 3 shows the analysis of learning attitudes of students in different majors, and the results of one-way ANOVA show that the differences in the total scores of the scales among students in different majors are statistically significant (P < 0.05). In terms of different dimensions, except for affective and cognitive ability dimensions, the differences in the scores of the rest of the dimensions among different majors were statistically significant (P < 0.05), in which in value judgment, the scores of the law students were significantly different from those of the international trade as well as the ideological and political education students M = 35.88, S = 4.65, P < 0.05. Law students scored significantly lower than students in International Economics, Trade, and Civic Education.

Table 3.

Analysis of learning attitude of different professional students

Majors	Affections	Cognitive ability	Value judgment	Difficulty score	Interest	Degree of effort
1.The international economy and trade	32.26±4.25	26.66±3.45	37.69±4.26	30.25±4.26	22.35±3.64	18.16±3.24
2.logic	32.46±4.26	27.65±3.33	38.45±5.33	32.75±3.64	18.56±4.56	17.58±3.26
3.Ideological and political education	33.15±3.14	25.64±2.98	37.66±3.36	30.64±4.26	23.45±3.971.2.	16.54±3.152.
4.law	33.54±3.66	25.66±4.26	35.88±4.651.3.	32.34±3.78	18.59±3.451.3.	18.25±3.141.3.
5.Applied psychology	33.26±5.56	26.78±4.26	36.45±3.68	31.64±3.46	20.26±3.484.	17.75±3.26
6. Chinese language and literature	32.45±4.56	27.36±3.68	38.46±2.621.3.	32.45±3.55	18.55±3.543.	18.66±2.981.3.
FIH Value	0.975	1.752	3.165	2.755	3.221	3.345
P Value	0.442	0.156	0.006	0.018	0.006	0.004

Note: ^1.The difference between the international economy and the trade is statistically significant. 0.05,^2. There are statistical significance compared to logic. 0.05,^3. means that there is a statistical significance compared to the ideological and political education. 0.05,^4. The difference between the law and the law is statistically significant. 0.05.

5

Conclusion

In this paper, after screening the common wealth ideological identity impact indicators and mediating effect indicators, the degree of importance of the evaluation indicators is estimated through the random forest algorithm, which provides a reference basis for the construction of the indicator system. After sequentially carrying out the steps of data pre-processing, determining the model structure, and evaluating the indicators, the construction of the evaluation index system for common wealth teaching identity in colleges and universities is completed. Through the method of case measurement, the identity of the common wealth idea and the effect of ideological education are empirically analyzed. Students in colleges and universities have a high degree of agreement with the indirect reasoning and the use of the analysis link of the teaching of the idea of common wealth, which are 3.455 and 3.364, respectively, while the score of knowledge migration, which has the lowest score among the six measurement indicators, is only 3.165, and the subject colleges and universities still need to be strengthened in the knowledge migration link. In the comparison of the effect value of each indicator, excluding the mediating effect, “application analysis” and “knowledge transfer” have the highest agreement, which are 0.239 and 0.165, respectively. The effectiveness of teaching in the four grades of students in the test colleges and universities was analyzed. The dimensions of learning engagement and learning plan are below 3.5 points, and there is still room for improvement. At the same time, there are differences in learning attitudes towards the concept of common wealth among students of different majors. For example, in the value judgment of common wealth teaching, the mean value of law students and international trade as well as Civic Education students is 35.88, the standard deviation is 4.65, P value <0.05, there is a significant difference between law students and international trade as well as Civic Education students in terms of value concept.

Funding:

Fund Project: The Educational Science Planning Project of Hubei Provincial Department of Education in 2019.

Project Name: “Research on the Characteristics of Ideological and Political Work of Private Colleges and Universities and the Innovation of Educational Mechanism”.

Project No: 2019GB102

Language:: English

Publication timeframe:: 1 times per year
Journal Subjects:: Life Sciences, Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics, Physics, other

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97B20Telling the Multiple Logics of Common Wealth in Ideological and Political Courses in Colleges and Universities

Shujun Zhang

Shan Lu

Published Online: Mar 17, 2025

Received: Oct 19, 2024

Accepted: Jan 31, 2025

DOI: https://doi.org/10.2478/amns-2025-0242

KeywordsRandom forest, ID-CNN model, Common wealth identity, Evaluation index system

© 2025 Shujun Zhang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
Random forest, ID-CNN model, Common wealth identity, Evaluation index system