bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on the enhancement path of talent cultivation in the integration of dual-creation education and professional education for teacher training majors in colleges and universities based on multivariate statistical analysis
Authors: Ma Heyuan , Yang Xue , Qi Kaiyue 
Published: January 2024

Abstract
In today’s society, under the demand for high-quality talents, the professionals cultivated in colleges and universities should not only master professional skills but also need to have the spirit of innovation and entrepreneurial ability in professional aspects. In this paper, firstly, the multivariate statistical analysis method is explained, and the basic principles of the factor analysis model, principal component analysis method and systematic clustering method are given to analyze the data in the following article. Secondly, starting from the necessity of the integration of bi-initiative education and professional education of teacher training majors in colleges and universities, we constructed the 4344 specialized and innovative integrated talent cultivation model of teacher training majors and constructed an evaluation system to evaluate the effectiveness. Finally, based on the evaluation system, the data analysis of the specialized and creative integrated talent cultivation model was carried out using factor analysis, principal component analysis and systematic clustering method. The results show that in the factor analysis, the highest loading value of the first principal factor is 0.917, the contribution rate of the first principal factor is 39.67%, and the loading value of the principal component factor reaches the highest value of 0.925. The clustering analysis is based on the results of the factor analysis, and the respondents are divided into 4 clusters. The number of people in the 2nd category is more than 30 people, which accounts for about 31.41% of the total number of people. The method of multivariate statistical analysis can be used to analyze the data effectively for the specialized and integrated personnel training mode of teacher training in colleges and universities and also gives the path of specialized and integrated personnel training for teacher training.
Analyzing the Importance of International Law in Current International Relations Based on Linear Programming Models
Authors: Qin Siquan 
Published: January 2024

Abstract
International law is mainly the law between countries, which is the code of conduct for countries to conduct international interactions, and this paper researches the role of international law in international relations interactions. First of all, this paper combines the fuzzy set on the basis of the classical linear regression model algorithm, establishes the fuzzy linear programming model, and explores the fuzzy correlation analysis. Then, taking EU law as an example, the role of EU law in EU relations is analyzed through the theory of EU law, EU and the role of EU law in the EU embodied. Finally, based on the role of EU law, the importance of international law in international relations is studied through a fuzzy linear programming model, and the role of strengthening international law is considered. The results show that the countries consider the legitimacy of EU law to be above 0.9, and the countries’ participation in EU law also ranges from 0.9 to 1.0, and the countries’ self-identification increases by about 0.1 to 0.2 after the enactment of EU law. The correlation coefficients of international law on the construction of the identities of the 10 countries are all greater than 0.75, and the interests of the countries have increased by about 2.3, and international law promotes the order of international relations.
The Construction of Ideological and Political Diversified Education Mode in Colleges and Universities Based on Theory of Multiple Intelligences
Authors: Qiu Jie 
Published: January 2024

Abstract
This paper firstly constructs the ideological and political diversified education model of colleges and universities from the diversified view of Civic and political education, educational objectives, as well as educational evaluation on the basis of language, logic, space and music of the theory of multiple intelligences. Then, on the basis of multiple linear regression analysis models, the step-by-step regression method is used to obtain the key factors affecting the diversified education of ideology and politics and establish the regression model of education quality. Finally, through the establishment of the quality evaluation index system of the ideological and political diversified education model, the quality of the ideological and political diversified education is analyzed by ANOVA, correlation analysis and stepwise regression analysis, and the nature and effect prediction of the ideological and political diversified education model is explored. The results show that the correlation between the quality of education and diversified education ranges from 0.32 to 0.88 and is significant at the 10% level, the significance of the teachers is less than 0.05, the significance of the content of education is less than 0.05, and the significance of the form of education is less than 0.05. The students’ ideology in all dimensions has been improved by more than 1.3. The educational model based on this study can greatly improve the impact of ideological education.
Application of big data technology in traditional dance video movement recognition research
Authors: Sun Zhenyi 
Published: January 2024

Abstract
This paper proposes a multi-feature fusion approach for action recognition under big data technology with the goal of improving traditional dance video action recognition. By analyzing the basic method of dance action, the extraction process of dance action features is analyzed using both single-layer and hierarchical methods. Multi-feature fusion action recognition is chosen as the main method for action recognition. The image and audio features of the dance video are combined to improve the accuracy of recognizing dance actions. Use the optical flow algorithm to construct a histogram of the optical flow direction. The method’s feasibility is explored by applying the multi-feature fusion recognition method to traditional dance movement recognition. The results show that in traditional dance movement recognition performance, the performance of the method of multi-feature fusion recognition is improved by 7.6% compared to other traditional methods. The multi-feature fusion recognition method has more than 50% accuracy in recognizing different traditional dance movements and similar movements in terms of movement recognition accuracy. To a certain degree, this study enhances the efficiency of traditional dance movement recognition and conserves human and financial resources in dance movement recognition.
Artificial Intelligence Technology Boosts the Construction of English Intelligent Teaching Mode in Colleges and Universities
Authors: Zhang Yang 
Published: January 2024

Abstract
With the goal of improving the teaching effect of English in colleges and universities, this paper combines artificial intelligence technology with teaching and constructs an English-intelligent tutoring teaching model. By analyzing the main forms of artificial intelligence in the field of teaching, the advantages of intelligent teaching mode in college English teaching are explored from personalized teaching as well as teaching effect. Combining the RBF neural network to analyze the students’ learning data, the function approximation principle and interpolation method are used to improve the accuracy of the analysis of the students’ data. Using the form of network topology, the information transfer process in English intelligent teaching is explored. To improve the classification of students’ abilities and the prediction of their grades, judgment trees are added to the network. The English Intelligent Assisted Teaching model was applied to teaching to explore its feasibility and effectiveness. The results show that students’ satisfaction with personalized teaching is 0.85, and their satisfaction with personalized evaluation is 0.8. The students’ translation ability under the English Intelligent Assisted Teaching Model has improved more, from 75 to 90.
Application of Project-based Learning Model Based on GBDT Model in Higher Vocational Civics Classes at the Time of Innovation
Authors: Zhang Guanglei 
Published: January 2024

Abstract
In this paper, the TR graph is constructed by combining the advantages of the tree diagram and Nightingale’s rose diagram, followed by the use of the LR+GBDT fusion model for predicting students’ performance. For the shortcomings of the K-prototypes algorithm in the application of educational data, an improved K-prototypes algorithm for student group division and feature labeling, and finally, user portrait as a pivot will be the fusion of the three to solve the problem of multi-chart linkage and the integration of charts constructed the student portrait, assisting teachers to make scientific decisions to develop personalized learning strategies. Through the integration of social resources and the curriculum content of the ideological and political discipline, a project-based learning model is established to realize the goal of cultivating students’ core qualities in the discipline of the ideological and political discipline. After the project-based learning mode, the difference between the pre-test and post-test scores of the experimental class’ ideological and political character was −6.83, p=0.000<0.001, the difference between the pre-test and post-test scores of cultural literacy was −7.12, p=0.000<0.001, and the difference between the pre-test and post-test scores of the value concept dimension was −3.54, p=0.027<0.05. There was a significant difference between the pre-test and post-test scores of the three dimensions, and there was a significant difference in the pre-test and post-test scores of all three dimensions. Scores between the pre-and post-tests were significantly different. Therefore, the application of project-based learning in the teaching of Civics and Political Science plays an important role in promoting.
Exploring Collaborative Parenting Strategies for Civics and Student Management in Colleges and Universities Using Multiple Data Chain Networks
Authors: Kong Zengqiang , Chen Lingling , Jia Qiaoran 
Published: January 2024

Abstract
In this paper, the multivariate data chain network is used to obtain the lexical sequence of Civics and Political Education, which needs to be labeled considering the convenience of research and analysis. According to the C-RTT algorithm can reduce the number of synchronization time slots required for fine synchronization of Civic and Political Network Teaching, use the Transformer encoder to assign and define the model parameters, and then construct the automatic scoring model with the theme of Civic and Political Work and Student Management. Starting from the content of the research and evaluation of the Civics and Political Science Program, the research variables and measurements are determined, and the research on the evaluation of the Civics and Political Science Program in colleges and universities is designed. Initial data for research and analysis are obtained by distributing questionnaires, and simulation analysis and statistical analysis are used to empirically analyze the Civics education combined with a multivariate data chain network. The results show that on the model analysis, the P value of the model in this paper can be up to 80.6, the R value can be up to 85.7%, the F1 value can be up to 83.2%, and the accuracy rate can be up to 82.4%, and the automatic scoring model with the theme of Civic and Political Work and Student Management has achieved good results. On the analysis of the Civics course, the mean values of the seven topics of student management are in the range of 3.78-4.18, and the standard deviations are all greater than 0.84. This study skillfully applies the theory of Civics to student management and ultimately helps the students to establish the correct three views.
An empirical study on the effect of academic engagement on academic achievement of engineering students in colleges and universities
Authors: Liu Xia , Liang Mingwei 
Published: January 2024

Abstract
Based on the linear regression algorithm, this paper uses the basic linear regression algorithm and the kernel linear regression algorithm to construct the relationship model between academic input and academic achievement based on linear regression and to determine the independent variables, dependent variables and control variables in the model. The engineering students of East China Normal University are selected as the research object, the research instrument is determined, the research index is determined according to the survey, and the research hypothesis is proposed, and then the research and analysis design of the impact of academic input on academic achievement is completed. Using reliability and validity to test the validity of the questionnaire, the initial data of the study can be obtained by distributing the questionnaire, and correlation analysis and regression analysis are used to carry out an empirical study of academic input and academic achievement based on linear regression. The results show that the correlation coefficient between academic input and academic achievement of master’s degree students is R=0.892 and R2=0.792, indicating that the predictive variance of academic input on academic achievement is 89.2%. The effects of the dimensions under the academic input on the social adjustment dimension under the academic achievement were, in descending order, as follows: active cooperation > teacher-student interaction > educational enrichment > academic challenge > campus support. This study comprehensively analyzes the impact of academic engagement on academic achievement, and colleges and universities should change the test of students’ ability to memorize knowledge and skills to the test of students’ ability to analyze and solve problems by applying what they have learned.
Application of Weighted Comprehensive Evaluation Model in Teaching Quality Evaluation System of Computer Class Vocational Education
Authors: Yi Weihuan 
Published: January 2024

Abstract
This paper firstly constructs the entropy weight-TOPSIS weighted comprehensive evaluation model, uses the entropy weight method to determine the indicator weights, and establishes a standardized evaluation matrix to evaluate the evaluation object through the TOPSIS model. Then, the evaluation model of teaching quality of vocational education, including teaching environment, curriculum construction, teaching content, implementation effect and teaching support level, was established, and the weight teaching evaluation of each index was made by using the entropy weight-TOPSIS model. Finally, the quality of teaching in the school was measured and analyzed, and the expected and perceived mean of different indicators were compared and calculated. The results show that the gap between the perceived teaching quality of each dimension of the indicators is basically controlled between [-1.0,-0.7], and the overall teaching quality evaluation result is -0.86, and the teaching quality needs to be improved urgently. This paper examines the teaching quality of vocational education, finds its problems, puts forward reform opinions, and promotes the development of the vocational education talent force in the direction of higher quality.
Reflections on and Exploration of Academic Early Warning Management and Support for Students in Colleges and Universities
Authors: Feng Junli , Lian Xiaojie 
Published: January 2024

AbstractIn this paper, the feature increment can be regarded as a learning mapping function, and a non-equilibrium incremental learning (WILS) method for the academic warning is proposed, and the academic warning model of the non-equilibrium incremental learning method is constructed. The learning factor is regulated by introducing the Focal loss function, and the learned knowledge is integrated into the Focal loss as the final loss function. Finally, the three-dimensional indicators of social characteristics, personal characteristics, and student behavior were used to explore the influencing factors of academic performance and academic support strategies were explored in this way. The results show that the average value of the accuracy of the academic early warning model is 0.857, and the F1-Measure is 0.891, which indicates that the model can reasonably and efficiently provide prior warning of students’ learning situations and behavioral performance. This paper proposes countermeasure suggestions for managing academic early warning and academic support work, which enhances the purpose of talent cultivation quality.
Combining the Information Diffusion Model for the Propagation of Zhouyi Ideology in the New Era
Authors: Lv Jili 
Published: January 2024

Abstract
This paper examines the moral edification ideas in Zhouyi and looks at the contemporary value of Zhouyi ideology and ideology. The UAU-SIS multiple network communication model is constructed, and the information radiation model between cyberspace and real space is proposed, which has a positive impact on the dissemination of Zhouyi ideology. The Master differential equation of the degree distribution of spatial topological structure is established to provide a basis for the dissemination of information related to Zhouyi ideology. Analyze the communication carriers of Zhouyi thought and improve the communication effect of Zhouyi thought in the new era by combining it with information diffusion technology. Simulation experiments are used to examine the feasibility and performance of the proposed algorithm. Investigate the influence of Zhouyi’s thought dissemination on citizens’ moral education consciousness. The experiment shows that the diffusion range of the algorithm is improved from 100 to 600 after 16 iterations, and the increased speed decreases to 4879.13s, the dissemination effect is better, and the algorithm is feasible. The scores of 6 evaluation indexes of students’ moral edification are 0.76, 0.93, 0.71, 0.63, 0.91, and 0.53. The overall level is good, and there is still room for improvement in the awareness of moral edification. It can be seen that the spread of Zhouyi thought has a beneficial effect on the citizens’ consciousness of moral enlightenment.
The application of big data technology in the innovation and effect analysis of art teaching mode in colleges and universities
Authors: Han Bing 
Published: January 2024

Abstract
In this paper, for the common behaviors of students in classroom teaching, deep learning and the improved student behavior detection algorithm based on YOLOv5s are used to transform the source data into another high-level and high-abstract data expression to realize the detection of students’ behavior in class. Then, taking into account the real conditions of college students and the internal logic of deep learning and classroom teaching, we sort out the target conditions of college students’ deep learning and their brand-new requirements for college classroom teaching and innovate the art teaching mode in colleges and universities. The innovative art teaching mode is applied in the art classroom teaching of W College of Fine Arts, and the teaching effect is analyzed. The results show that the mean values of students’ evaluation in the five core literacy skills of image literacy, art expression, aesthetic judgment, creative practice, and cultural understanding increased by 12.6, 14.95, 17.66, 12.27, and 19.1 points after the innovation compared with those before the innovation. The above data show that the innovation of art teaching mode can enhance students’ motivation to learn and stimulate their creative passion, thus cultivating their creative ability, making students learn to inherit and carry forward the traditional culture of the Chinese nation, and enhancing their cultural self-confidence and national pride.
Research on the Reform of Ancient Chinese and Modern Chinese Language Teaching in the Context of Deep Learning
Authors: Lei Jingyang 
Published: January 2024

Abstract
In this paper, we use a deep learning algorithm to optimize the loss function of Chinese data, dynamically adjust the learning rate by gradient descent method, and adopt an exponential moving weighted average to deal with language information. The second-order information of the historical gradient is processed to calculate the change value of the objective function of the Chinese language variables, and the learning rate is scaled accordingly, which is inversely proportional to the teaching reform model. Ultimately, the error between the objective function value and the predicted value is optimized with a smaller learning rate, and the neuron learning rate is scaled to achieve the best solution for the language teaching reform of ancient Chinese and modern Chinese. The accuracy rate of the deep learning algorithm is verified to be as high as 0.9, which provides reliable technical support for teaching reform. The reform’s weighting of teaching content to 0.471 underscored its significance in teaching. Fifty-three percent of the students showed strong interest in the teaching method reform, highlighting the popularity of teaching mode innovation. The teaching rating before the reform increased by 6 points compared to that after the reform, showing the positive impact of the reform on teaching.
Design of a Competency Assessment System for English Teaching Positions Based on the SERVQUAL Model
Authors: Liu Fengmei 
Published: January 2024

Abstract
This paper first introduces the SERVQUAL model and establishes generalized indicators, including four aspects of moral character, integrity quality, work ability and work attitude. Subsequently, an information sampling model was constructed to obtain information on the job competence constraint parameters, which provided the necessary data support for the assessment. On the basis of information fusion and time series analysis, a quantitative recursive assessment of English education job competence was carried out using the gray model to obtain the feature extraction results of the job competence assessment and finally to determine the probability density generalized function of English teaching job competence. The assessment results show that the accuracy of the SERVQUAL model is up to 98%, and the combination weight value of interaction ability is the highest, reaching 0.1266. The correlation coefficient of teaching job competence reaches 0.925, and the overall importance evaluation of teachers’ teaching competence is the highest at 93 points, which highlights the high efficiency and accuracy of the assessment system.
A Screening of Tools to Measure the Quality of Financial Reporting
Authors: Dănescu Tatiana , Stejerean Roxana Maria 
Published: January 2024

Abstract
The main objective of this research is to identify and systematize tools for measuring the quality of financial reports, in order to support researchers considering this comprehensive area. By using the PRISMA system in as transparent a manner as possible, we also aimed to find potential gaps in all 89 articles and scholarly papers examined in the smallest detail. As the quality of financial reporting is ultimately aimed at mediating the relationship between the entity and the user, it is not a topic addressed individually, the secondary object of this paper is to expose the most common themes and discussions associated with this object of study, such as: characteristics of entities, adoption of International Financial Reporting Standards, shareholding structure, corporate governance and audit committee.