Ideological And Political Education Research Articles

Design a Platform for Sharing Educational Resources for Student Based on Dual Attention Graph Convolutional Networks

A key component of raising educational standards is always the sharing of educational resources throughout higher education institutions. The development of digital and network infrastructure among colleges and universities can propel the sharing and exploitation of excellent educational resources to new heights. Nevertheless, there is a lack of an ideal platform for resource selection and integration in the current crop of information-based teaching tools. To overcome this drawback, the methodology used in this study was described in this research in order to classify student and teacher data more precisely. Ideological and Political Education (IPE) is the source of the data collection. The Modified Hamilton filter is used to preprocess the data during the pre-processing step. The excellent course videos, classroom performance, and interactions are all successfully classified by Dual Attention Graph Convolutional Networks (DAGCN).The neural network's weight parameter is optimized using the Lotus Effect Optimization Algorithm (LEA) to improve the DAGCN. The suggested DAGNN-LEA used with the MATLAB platform. The suggested approach was calculated using performance measures such as accuracy, precision, sensitivity, F-score, computation time, and recall. In comparison to the existing method, the suggested DAGNN-LEA method yields better results in terms of high accuracy 16.65%, 18.85%, and 17.89%, high sensitivity 16.34, 12.23%, and 18.54%, high precision 14.89%, 16.89%, and 18.23%, and low computing time 82.37%, 94.47%, and 87.76%.

Strategies of Infiltrating Psychological Fitness Education Into Ideological and Political Education

As the cradle of cultivating talents, universities are facing great opportunities and challenges in their education. Among them, IPE (ideological and political education), as an important foundation for the future growth of university students, is of great significance. This paper discusses the relationship between IPE and psychological fitness education in university teaching. This paper expounds the necessity and feasibility of playing the role of psychological fitness education in IPECU (ideological and political education in colleges and universities). Based on this, this paper gives the strategy of infiltrating psychological fitness education into IPE. This paper combines NN (neural network) method to construct an assessment model of IPE quality. In this paper, MATLAB is used for simulation and comparative analysis. The final experiment shows that the RMSE of this algorithm is 0.512, MAE is 1.089, and the accuracy of the algorithm is 0.958.

Analysis of the Path to Improve the Effectiveness of Ideological and Political Education in Universities Based on Information Fusion Technology

Abstract This paper firstly constructs a reasonable education resource model according to the features of Civic Education Resources (CERs) and proposes an integration scheme of CER Library in universities based on information fusion technology. Secondly, the storage structure of Lucene’s inverted index is optimized for the management features of the CER Model, and a full-text index library of educational resources for resource retrieval is constructed. Then the advantages and features of information fusion techniques are used to provide college students with exclusive, practical, personalized and customized Civic Education measures to innovate the concept of ideological and political education (IPE) in colleges and universities. Finally, through the subject index of ideological education resources constructed based on the LDA model, the semantic processing of user queries, the design of effective experimentations to confirm the accuracy of the retrieval of ideological education resources, and its evaluation indexes are considered comprehensively from several aspects such as retrieval speed and accuracy rate. The results show that the maximum P @ N value of improved Lucene index retrieval is 1, which is 0.4 larger than that of traditional Lucene-based index retrieval, and the average performance of improved Lucene index retrieval is improved than that of traditional Lucene-based index retrieval in P @ N indexes. This study helps universities to innovate the concept of IPE to retain the ideas up to date and retain pace with the times.

Organic integration of ideological and political education and entrepreneurship education based on artificial neural network

Entrepreneurship is a systematic project, and it needs entrepreneurial knowledge, skills, psychology and many other basic qualities. Therefore, it is imperative to educate college students on entrepreneurship. IPE (Ideological and political education) courses offered by universities should adhere to the spirit of the Chinese dream and integrate with 2E (Entrepreneurship Education), which will not only provide more theoretical guidance for college entrepreneurs in practice but also promote their practical experience to theoretical innovation and promote their all-round development. Therefore, this research is based on ANN (artificial neural network) to study the organic integration of IPE and entrepreneurship education. According to the practice of carrying out quality education in our university, a set of index systems suitable for comprehensive quality evaluation of students in engineering colleges is established. Use BPNN (BP neural network) method to construct the test model, and IL (Input layer) is responsible for receiving external input information. Through the learning rules in HL (Hidden layer), this paper refers to the weight values of various quality indicators, transforms the input values, and adjusts the deviation of test results. OL (Output layer) is responsible for outputting calculation results, that is, evaluating students' comprehensive quality information. The results of BPNN show that the actual value and the expected value are within a reasonable range, and the maximum relative error is 1.607 %, which meets the accuracy requirements. The established evaluation index system of 2E is reasonable and effectively reflects students' innovation and entrepreneurship abilities.

Research On the Optimization of Ideological and Political Education in Universities Integrating Artificial Intelligence Technology Under the Guidance of Curriculum Ideological and Political Thinking

Using the association rules among both data mining (DM) and Artificial Intelligence (AI) technology, this paper proposes concepts and techniques for enhancing the curriculum environment based on the modernization of the educational field curriculum scheme of Ideological and Political Education (IPE) classes in universities and colleges. The study analyze the inter-subjectivity concept to the model development from the conceptual level, the benchmark value of the whole setting, multidimensional spacetime, and the leading importance of the Internet governance idea to the reformation of IPE in the colleges and universities. The findings assess the issues with IPE transformation and development in colleges and universities and suggest solutions, as well as four mechanisms of "methodical design underlined in the overview, team-work cooperation of team development, augmentation of environmental development, and double endorsement of quality management”. The concept of developing a” three-stage full atmosphere" network IPE architecture for universities and colleges is presented as one of the remedies to enhance the efficiency of the IPE in universities. This idea is based on experience summary, theoretical analysis, and empirical study. The timeliness concerns of IPE transformation in universities and colleges are resolved by using in-depth comprehension and evaluation of the necessary knowledge of DM-AI, which is then used to apply the appropriate DM-AI methodologies. This allows the relevant administrators to quickly learn the crucial data in complicated problems and suggest solutions for subsequent decision-making.

Methodology for evaluating the ideological and political education quality of chinese universities based on fuzzy number intuitionistic fuzzy multiple-attribute decision-making

The quality evaluation of Chinese universities ideological and political (IAP) education has gone through the stages of defining tasks, proposing standards and exploring and carrying out, and has completed the stage tasks and accumulated practical experience. To construct the quality evaluation system of IAP education of Chinese universities in the new era, it is necessary to find the quality positioning in the fundamental task of establishing moral education and pay attention to the synergy between the internal and external parts of the quality of IAP education of Chinese universities. The IAP education quality evaluation of Chinese universities are the multiple-attribute decision-making (MADM) issue. In this paper, we extend the geometric Heronian mean (GHM) operator to fuzzy number intuitionistic fuzzy numbers (FNIFNs) to propose the fuzzy number intuitionistic fuzzy weighted geometric HM (FNIFWGHM) operator. Then, the MADM method are built on FNIFWGHM operator. Finally, a numerical example for IAP education quality evaluation of Chinese universities and some comparative studies are used to prove the built methods’ credibility and reliability.

Cinergeticheskij process razvitiya ideologo-politicheskogo vospitaniya i formirovaniya psihologicheskogo blagopoluchiya studentov vuzov v epohu novyh media

The article discusses the integration and coordinated development path of university students IPE (ideological and political education) and psychological well-being education in the new media era. The article discusses the psychological and ideological problems of contemporary university students, analyzes the necessity and principle of the integration of IPE and psychological well-being education.

The Innovation of Ideological and Political Education Integrating Artificial Intelligence Big Data with the Support of Wireless Network

ABSTRACT Artificial intelligence (AI) and big data profoundly impact people’s way of life and way of thinking, and college ideological and political education (IPE) has gradually entered the era of online education. On account of this, this study designs an online education algorithm based on AI technology to help teachers better understand the situation of students’ online IPE teaching and improve the management of IPE in universities. Firstly, the learning features of students are extracted through the Back Propagation Neural Network (BP) model. This model summarizes the shortcomings of feature extraction in machine learning, and can simultaneously obtain depth information from the signals of multiple sensors, thus increasing the overall algorithm classification accuracy. Secondly, combined with the human behavior recognition model, the status and behavior of students’ IPE teaching can be obtained in real-time from students’ listening devices. Finally, the algorithm’s classification performance is evaluated by experiments and compared with the designed model. The results reveal that the recognition accuracy of the designed classification algorithms for the sample students is 98.59%, 98.99%, 99.21%, 100%, 97.10%, 95.61%, and 100%, respectively. In addition, comparing the algorithm with similar recognition algorithms, its index values of accuracy and precision are 97.83% and 97.82%, respectively, which are better than similar classification algorithms. Finally, through the experimental samples, the accuracy of the human recognition model is tested and compared with other recognition models. The results reveal that the designed model has high recognition accuracy. This study is of great significance for improving teachers’ innovative IPE methods and optimizing the management level of online IPE teaching.

Prodvizhenie ideologicheskogo i politicheskogo vospitaniya v studencheskih obshchezhitiyah v ramkah modeli «Bol'shaya mysl' i politika»

This article expounds the significance of strengthening ideological and political education (IPE) in university student apartments under the background of “big thought and politics”, and discusses how to give full play to the IPE function of apartment management in the stage of student apartment management.

Active participants but confused minds: university students’ perceptions of citizenship learning experiences in Chinese higher education

PurposeThere is widespread debate about the nationalistic top-down approach of citizenship education. By using the notion of cultural citizenship as a useful theoretical lens, citizenship education research tends to focus on the process of subjectivity construction among students’ citizenship learning process. The Communist Party of China plays a dominant role in cultivating citizens in the form of ideological and political education (IaPE) in Chinese universities. The research problem thus focuses on the dynamics and complexity of how Chinese university students construct their subjectivities regarding citizenship learning through IaPE. The main purpose of the study is to provide some research directions for understanding students’ citizenship learning today.Design/methodology/approachWith the case study of one university in China and interview data from 25 students, this paper examines the ways in which students understand and respond to dominant discourses.FindingsThe findings revealed there is a deficit of citizenship learning in IaPE, and students felt ideologically pressurized. This study suggests students’ complex subjectivities of active participants but confused minds as a phenomenon in Chinese higher education, in which they must involve in IaPE for personal academic and career development, while they adopted covert strategies for self-conscious citizenship learning expectations. These strategies took the form ranging from obediently completing basic curriculum requirements and distancing away by studying abroad, to actively searching for learning opportunities from other courses and media society.Originality/valueThis paper contributes to citizenship education research by recognizing the complexities of how subjectivities are formed in formal university settings.

Red Boat Spirit and Social Entrepreneurship Education in China

Economic development and community revitalization can benefit from youth entrepreneurship; however, insufficient guidance for youths may weaken this beneficial effect. The Ministry of Education of the People’s Republic of China organized entrepreneurship events in China’s tertiary education institutes. With the aim of helping youths at university to clearly perceive social–entrepreneurship value and steadily form moral business motives, events were guided by the core of the Red Boat Spirit (RBS) and through the specific program Youth Red Dream Building Journey (YRDBJ). Youths have been part of the nation’s evolution via their contributions to various fields, including initiatives to improve the appearance of the countryside; modern innovations in agriculture; providing health and medicine supplies to alleviate poverty; and the cultural spread of RBS. Ten million university students have joined the program since 2017. Incorporating RBS and Social Entrepreneurship Education (SEE) into the special Ideological and Political Education (IPE) in China’s tertiary education, the program, YRDBJ, significantly influenced the Chinese youth in terms of social entrepreneurship at university. With this analytical approach, this study employed Marxist theories to analyze the relevant theoretical literature on entrepreneurship in order to discover the mechanism underlying the success of the program. This paper reveals the theoretical framework of YRDBJ and analyzes the factors that favorably formed the framework; moreover, it also proposes a new conceptual model bound with YRDBJ, which enriches the theoretical development of IPE and SEE. This paper also notes the limitations of YRDBJ and subjects it to scrutiny; then, we provide new ideas to improve the relationship between SEE and YRDBJ.

Optimization of Ideological and Political Education Courses for College Students and Strategies for Mental Health Education.

Most college students are still in the growth stage in the complex network environment. Therefore, it is necessary to consider measures for ideological education and psychological training. Firstly, by citing literature, this work explains the current network environment college students face and the adverse effects on their psychology. Secondly, the relationship between the ideological education work of college students and the network environment is expounded. Finally, the sampling survey method is adopted to analyze the use of the internet, information contact behavior, and the psychological status of college students at the present stage. The results showed that: (1) those with a college degree or above accounted for 47.1%. The data show that college students are at the forefront of internet use. They bear more social responsibilities than other groups. (2) About 90% of people have different degrees of depression and anxiety. The data show that psychological training and ideological and political education (IPE) for college students is necessary. This paper aims to sum up the obstacles existing in IPE and psychological training through the influence of network environment and bad information on IPE of college students. Based on the survey results, this paper can find a solution to create a good IPE environment for college students.

Research on Ideological and Political Education Mode Based on the Cultivation of Innovative and Entrepreneurial Talents

Under the background of enterprises in the new era, business startups and innovation education for university students is the key to the growth of university students into the talents that enterprises really need. The cultivation of business startups and innovation ability is also of key significance to universities. Although many university students will choose to start their own businesses when they graduate, most of them still lack practical experience. Therefore, it is need to analyze the relevant influencing factors, effectively cultivate students' innovative and entrepreneurial ability, so as to improve the success rate of university students' entrepreneurship. It is an indispensable link to integrate IPE with university students' business startups and innovation education, and it is an important guarantee to cultivate outstanding talents. On the basis of analyzing the advantages and disadvantages of university students' business startups and innovation under the background of enterprises in the new era, this article discusses the measures for the integration and growth of ideological and political education (IPE) in colleges and universities (IPECU) and business startups and innovation education, so as to improve the quality and ability of university students, lay a solid foundation for business startups and innovation after graduation, and have special advantages.

Comparative analysis of CR of ideological and political education in different regions based on improved fuzzy clustering

Abstract Vigorously developing ideological and political education (IPE) is the only way to boost talent training, and scientific and technological progress, and lead to the upgrading of the economic structure. Therefore, by analysing the internal relationship between the current social and economic growth and the development of IPE in colleges, this article introduces the investment of IPE into the social production function model where the gravity search method is used to optimise fuzzy clustering, and the classified data sets of each province in China are determined by genetic algorithm. In addition, the calculation model of contribution rate (CR) of IPE in different regions based on an improved fuzzy clustering algorithm is established, and the influence of IPE on regional economic development in eastern, western and central regions is compared and analysed, which is helpful to realise the optimal allocation of educational resources in China.

Job stress and burnout among ideological and political education teachers during the COVID-19 pandemic: A moderated mediation model.

Job burnout among ideological and political education (IPE) teachers in China is a complex problem and rewarding area of research. This study explored the relationship between job stress and burnout among ideological and political education (IPE) teachers in the context of the COVID-19 pandemic. The cross-sectional design included a sample of self-report measures sampled from 362 university IPE teachers. Using multiple line regression analysis, our main findings were as follows: first, job stress had a significant predictive effect on work-family conflict and job burnout; second, work-family conflict mediated the relationship between job stress and job burnout; and finally, resilience productively moderated the relationships between job stress and both work-family conflict and burnout. These results suggest that resilient IPE teachers are less likely to suffer from burnout. They indicate the need to systematically foster resilience in trainees and experienced instructors as a means of coping with adverse work conditions.

IAPE Exploration under the International Communication Environment Based on Big Data Analysis of Social Network.

Social network (SN) plays an important role in issue focusing, public opinion filtering, and scheme policy making in the dissemination of ideological and political education (IAPE), which promotes it towards a more accurate and safe public health direction. After studying the information dissemination process and diffusion mode of IAPE, this paper puts forward the UECSR model of its information dissemination model of blockchain SN, adds the unique consensus node state of that, and redefines the information state transition process and dissemination probability calculation. Finally, the influence of the propagation probability of blockchain is discussed through experimental simulation classification, which can verify the model's validity and rationality.

Text Score Analysis under the IPE Environment Based on Improved Transformer.

In order to improve the accuracy of ideological and political education (IPE) text scoring, an improved short-text similarity calculation model based on transformer is proposed. This model takes the DSSM model as the basic framework and uses the Bert model to realize text representation and solve polysemy problem. The transformer encoding component is used to extract the characteristics of the text and obtain the internal information of the text. With the help of the encoding component, the two texts can interact with information on multiple levels. Finally, the semantic similarity between two texts is calculated by concatenation vector inference.

Influence of the Integration of Aesthetic Education by Zhu Xi's Neo-Confucianism on the Ideological and Political Education and Internalized Psychology of College Students.

The purpose is to study the influence of Zhu Xi's neo-Confucianism on the ideological and political education (IPE) of college students. Firstly, the aesthetic connotation of Zhu Xi's Neo-Confucianism is studied. Secondly, an interview is performed with teachers of the IPE course in a university in Xi'an, and a questionnaire survey is conducted on some students of the IPE course in the school. It aims to investigate the current situation of college students' IPE, and the impact of integrating aesthetic education into IPE of college students on the improvement of students' overall quality and internalized psychology. Finally, the reasons for this situation are analyzed and solutions are given. The survey results reveal that the aesthetic education thoughts based on Zhu Xi's neo-Confucianism are integrated into the construction of college students' internalized psychological mechanism, and most students think that their mental health status has changed a lot. The proportion of boys who choose “improved” is 57.95%, and the proportion of girls is 53.45%. The aesthetic education is integrated into the IPE of college students, and the proportion of students who think “no effect” after integration and before integration has decreased by 2.01%. The proportion of the number of people who chose the three indicators of “increasing the innovation of teaching methods”, “advancing aesthetic ability”, and “improving the effectiveness of ideological education” increased by 5.88%, 5.5%, and 3.98%, respectively. It demonstrates that the effect of IPE on college students has been greatly improved after integration into aesthetic education.

Evaluation of College Students' IPE Environment Based on User Rating Sparsity and Big Data Technology.

Big data improves opportunities for enhancing and improving university students' IPE. In order to improve the accessibility of IPE for university students, this study integrates big-data techniques into the IPE (Ideological and Political Education) model of university students and builds the IPE platform. This study presents the idea of user rating sparsity and employs a two-step training strategy to address the issues of user cold start and sparse data in light of the drawbacks of conventional methods. This algorithm produces a very small data structure, which saves a lot of storage space. This study also uses hybrid recommendation technology, which effectively enables platform users to select customized update resources based on their interest information. According to test results, this method's suggestion accuracy can reach 95.69%, and it has a high user rating. This demonstrates that the method is reliable and accomplishes the desired result. This paper fully utilizes mega data to improve the accessibility of IPE for university students.

Optimization Algorithm for Ideological and Political Curriculum Environment in Colleges Using Data Analysis and Neighborhood Search Operator.

In the context of the new era, the distinctive function of BD (big data) analysis and prediction also introduces a new way of thinking to university IPE (ideological and political education), broadens the domain of university IPE, and enhances the curricular offerings of IPE universities. In order to enhance the intelligence and personalization of the intelligent teaching system, this paper describes in detail the design and implementation processes for each component of the system. It also uses the association mining rule algorithm of data mining. To maintain population diversity, a population initialization method and a neighborhood-based search operator are used, both of which are based on a thorough consideration of the characteristics of complex networks. The neighborhood search strategy enhances the local search capability of the TLBO (Teaching-Learning Based Optimization) algorithm. The optimized TLBO algorithm presented in this paper achieves the highest average modularity value of 0.5238 through testing on real-world data sets. The outcomes demonstrate that the algorithm performs well and is successful in identifying problems in the community.