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In this paper, we filtered fused and integrated online teaching learning behavior data by collecting basic information of teachers’ and student performance information, generated comprehensive assessment, and established a model of students’ online learning process. Finally, an assessment scheme was developed and tested using the online teaching of civil law courses as a case study, and the total learning efficiency was evaluated. The results showed that the proposed scheme in this paper is reliable and reasonable for assessing the teaching effectiveness of online education. The research results of this paper provide new ideas and methods for assessing the effectiveness of online teaching in civil law, which can help teachers better understand students’ learning behaviors and learning effects and improve their teaching strategies promptly.

In this paper, the information sphere radiation model describes the diffusion process of information in cyberspace. In real space, the information ring radiation model represents how information diffuses through interpersonal transmission in social circles. Secondly, the degree distribution of nodes in the network is described by the spatial topology’s degree distribution function and how information diffusion in the network is constructed. Finally, the model’s effectiveness is verified through the simulation of the total number of nodes function Q(t) for the diffusion of information in Civic and Political Science teaching. The mean diffusion degree is around 1.2 according to the results when teachers and students are the main interactors. In the case of student-content interaction and hybrid interaction, the mean value of diffusion is around 2.3. In the exercise session, however, the student-student diffusion degree reached 3. Through the information diffusion model, this paper facilitates the development of a digital model for college Civics teaching.

In this paper, a digital education management information system (e-MIS) is constructed based on big data, which realizes the comprehensive processing of education administration and school management data. Through the fuzzy comprehensive evaluation model, the e-MIS system was evaluated and optimized. Then, the e-MIS system was practically applied to the fields of teaching effectiveness evaluation, teachers’ work assessment, scholarship evaluation and dormitory management. Finally, the significant impact of the e-MIS system on the enhancement aspects of new student enrollment education was empirically verified. The results show that the average score of freshmen’s school rules and discipline education is 4.35, learning culture education is 4.53, mental health education is 4.41, and life guidance education is 4.31, all of which are in the middle-upper level, as calculated by the e-EMIS evaluation model. This paper is a positive exploration of improving the efficiency of student education and management in local colleges and universities and promoting the overall development of students.

In this paper, we first construct the discourse knowledge structure of education in different disciplines so that the knowledge points in a certain cross-cutting area between different disciplines are finite sets called knowledge domains, and we use the network of the discourse field system to characterize the logical relations in the knowledge space. Secondly, by defining the elements of hypertext as a triadic structure, a specific chain of dependencies is constructed by combining the hypertext structure with the knowledge space. Finally, we conducted a comparative analysis of the knowledge structure of educational discourse in various disciplines. The results show that among 45 knowledge states, 15 attributes corresponding to the whole column have all 0 information values and the knowledge structure model based on the knowledge space can master the corresponding effective skills of students in different disciplines, which indicates that it realizes this learning process of knowledge learning from point to point, from concrete to abstract, and from part to the whole under different disciplines. This paper examines the use of discourse in various knowledge structures, which may provide insights into the teaching of English academic writing in China.

This paper is based on the big data survey under the strategy of science and education to develop the country and analyze the talent job skill demand. According to the social demand for education and the characteristics of the student source to design and formulate the talent training structure, through the cultivation of talents and social demand for game analysis, using linear programming methods to establish the game model of talent training mode. Game theory equilibrium theory can be used to solve on the basis of benefit function. The results of the teaching quality monitoring and evaluation system show that the students in this school achieved 9.7 in innovation consciousness and 9.5 in practical ability. The one-time signing rate reached 8.9, and the employment rate reached 7.7. It verifies that the talent cultivation strategy proposed in this paper can improve the quality, reduce the cost of talent cultivation of the enterprises and improve the practicability of the talents.

This paper firstly proposes the reform strategy and innovation direction of college dance education based on the Internet background of the era and adopts Webwork+Spring+Hibernate to build the overall architecture of the dance education system and designs the functional modules of the dance education system. Then, establish the dance teaching model based on association rules, use the association rule data mining algorithm to mine specific laws to improve the prediction model, and measure the standard of association rules by T test. Finally, the dance education system is tested for operation, compatibility, response time, and application analysis. The results show that the average score of students’ final exam before applying the dance teaching system is 75.23, and the average score of students’ final exam after applying it is 86.12, which is an improvement of 10.89 points, which shows that the dance education system constructed in this paper is able to improve the student’s academic performance, and promote the reform of dance education in colleges and universities effectively, and provide a new direction for the development of dance education in colleges and universities.

This paper explores how the synergistic effect of scale, structure and quality of Certain components can encourage postsecondary education for superior economic growth. Firstly, this study illustrates the synergistic effect of scale, structure, and quality factors in higher education by exploring the theoretical mechanisms of these elements in higher education to promote good economic development. Second, the conventional TOPSIS method is refined, and the entropy power-TO PSIS model is constructed by combining the entropy power method with the regression model built on the theoretical mechanism of the previous paper, and the empirical design is executed. The measurement of high-quality development of higher education and the economy is made possible by this. After building and finishing the evaluation index system for higher education and high economic, high-quality development, the development measurement is examined at the end. Based on the regression results, Analysis is done on the mediation and threshold effects of higher education for the establishment of high-quality economic growth, and pertinent policy recommendations are made. The scale structure and quality criteria of higher education are 40.1,303.1,9.9, and 60.2, respectively. The growth levels of the east, central, and west are 0.27,0.24, and 0.24, respectively, as is the proportion of the mediating influence to the total effect of 0.32 and 0.51. Through the factors of scale, structure, and educational quality, higher education works in concert to optimize technology and industry and, in turn, to foster the excellent growth of the economy.

It is advantageous for schools to realize exact education management, the cornerstone for developing abilities, by constructing higher vocational education teaching quality evaluation systems. The division of frequent item sets based on the modified Apriori algorithm under the association rule algorithm is used for the evaluation algorithm of this system to examine the evaluation data in the evaluation system, which is created in this work using data mining technology. Data validation was carried out from system performance and application analysis of association rules for the teaching quality evaluation system constructed in this paper. Regarding system performance, the highest response time of the system in this paper is 8.34s, which is about 56.94% and 40.68% shorter than that of the evaluation system based on AHP and gray correlation theory, respectively. This shows that using association rule algorithms can realize the operation of the evaluation system faster, improve evaluation efficiency, and use visual data to achieve precise education management in schools.

Empowering precision innovation through big data to improve the effectiveness of ideological and political education in colleges and universities can effectively promote cultivating the new generation of the times. Based on learners’ learning behaviors and quantified learning behavior indicators, this paper proposes a three-branch division model based on a cognitive level to reduce the “Matthew effect” of collaborative filtering algorithms in path recommendation and improve the cognitive level of online learners. Based on the three-branch decision theory, we select the decision with the highest expected utility as the final decision and recommend the learning content suitable for the learners’ development. The analysis of the functional requirements of the personalized learning recommendation system based on knowledge mapping, the overall structure diagram of the system, and the construction process of each component module are proposed. By analyzing the influence of ideological and political education on college students, about 80% of college students generally think that ideological and political education has improved political character, strengthened ideals and beliefs, enhanced national sentiment, standardized speech and behavior, improved comprehensive literacy, and enriched after-school knowledge. More than 80% of students, teachers, and leaders are satisfied with the personalized recommendation model proposed in this paper, and less than 10% are dissatisfied. Therefore, big data technology can help improve students’ Civics learning effect and has strong applicability.

This paper collates and fuses data from various aspects of university students and designs student evaluation indexes by combining the data. Based on the student behavior segmentation model of cluster analysis, the traditional k-means clustering algorithm is optimized, focusing on the optimization of content selection of initial cluster centers and distance optimization calculation to make a better clustering effect and classify students accurately. Then the K-nearest neighbor algorithm is proposed to solve the problem of timeliness and posteriority of student warning, by which the behavior of students can be predicted, and teachers can manage and help students in time. Finally, a student behavior characteristic category model is established to strengthen the prediction model of the K-nearest neighbor algorithm and improve the accuracy of predicting student behavior. The student data of a university were analyzed, in which the correlation pearson coefficient between the number of library admissions and grades ranged from 0.25-0.31, and the p-values were all much less than 1. It showed that the number of library admissions of students obviously affected students’ grades. In the analysis of the correlation between the early rising index and academic achievement, where the Pearson coefficient is 0.291 with a p-value of 5.61E-7. This indicator, which is not much associated with academic behavior, indicates that students’ early rising and timely breakfast can affect achievement to some extent. Therefore, the method of this paper can be refined using student data.