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Ideological and political education in colleges and universities is routinely burdened with the job of building morality and cultivating people, which is related to the cultivation of college students' ideals and beliefs, spiritual pursuits, and political literacy. Based on self-determination theory (SDT), this paper modeled different learning motivations in the early stage of ideological and political courses and analyzed the learning motivation of different student groups combining the Gaussian mixture model (GMM) and stacked autoencoder (SAE). Meanwhile, the study in this paper compared the participation characteristics of different learning motivation clusters, the differences between the ideological and political course performances of students with different learning motivations, and the potential link between learning motivation and learners' educational level. The experimental results show that students with extrinsic motivation will have better performance in the courses. The strength of extrinsic motivation is positively correlated with students' academic performance, and 70% of students with intrinsic motivation achieve excellent results. In addition, the χ2 test result of the two courses selected is 6.442, which confirms the effectiveness of the clustering model proposed in this paper from the side and provides effective theoretical support for the implementation and reform of ideological and political education strategies. [ABSTRACT FROM AUTHOR]

The current ideological and political (IAP) teaching has some disadvantages, such as emphasizing theoretical form over practical teaching, students' differences in personality and cognition, and lack of interaction between teachers and students. Therefore, this paper first analyzes IAP teaching based on VR communication and summarizes the disadvantages of current IAP teaching and the application advantages of VR technology. Based on the principles of interactivity, practicality, and richness, the IAP teaching system is constructed based on the double-center teaching mode, and the teaching content are designed. In addition, in order to provide a carrier for VR IAP teaching, this paper designs the functional module, development process, and framework of the development of VR venues with red theme, combining with red historical events. The IAP education system proposed in this paper can help to explore the potential and advantages of VR technology that applied to IAP education in colleges and realize the modernization of IAP education. [ABSTRACT FROM AUTHOR]

Monitoring and guiding instructional management require student performance evaluation. Traditional evaluation and analysis methods based on absolute scores, on the other hand, have certain flaws and are unable to fully reflect the information contained in student performance, thus limiting the impact of student performance evaluation on teaching and learning management. Data mining is regarded as the backbone technology for future information processing, and it introduces a new concept to the way humans use data. Schools must analyse and evaluate the performance of students in the same grade level and secondary school in a timely and staged manner. Clustering is a type of data mining that uses similarity rules to classify sample data into groups with a high degree of similarity. To address the difficulties caused by the wide variation in course difficulty in student performance evaluation, a method based on the K-means clustering algorithm is proposed. The K-means algorithm and the improved K-means algorithm with student information are investigated. The test results showed that the K-means clustering algorithm, the improved algorithm in this paper, and the fast global mean clustering algorithm all cluster the same randomly generated data set with noisy points, but the clustering time of the algorithm in this paper is only 0.04, which has obvious advantages. As a result, the clustering algorithm-based higher education management and student performance evaluation mechanism provides some insights for future research on student learning patterns. It is hoped that instructional administrators will gain a better understanding of students' learning characteristics so that they can better guide their teaching. [ABSTRACT FROM AUTHOR]

In order to promote the effect of college physical education reform, this paper combines the generalized Hough transform model to analyze the visual movement of physical education teaching. The idea proposed in this paper uses the position information of the edge image itself and the direction information of the curve segment to directly eliminate the impossible targets, which fundamentally alleviates the problem of invalid sampling and accumulation. Moreover, this paper greatly constrains the parameter space based on the results of each segment of the curve, which greatly reduces the search burden of high-dimensional parameters, and combines the improved algorithm to construct a sports teaching video action analysis system. The experimental research shows that the visual movement analysis system of physical education teaching considering the generalized Hough transform model proposed in this paper can effectively analyze the sports teaching actions and improve the efficiency of physical education. [ABSTRACT FROM AUTHOR]

In view of the inability to accurately analyze the application of deep learning in college physical education teaching design from the perspective of flipping classroom, this paper puts forward an improved deep learning method based on the integration of flipping classroom vision and deep learning, which can reduce the design ability of physical education teaching design in college physical education teaching design and improve the level of college physical education teaching design. Firstly, the initial data set is established by using the theory of flipping classroom horizon, so that the data meet the requirements of normal distribution and reduce the differences between teaching data; Then, the physical education teaching design is divided into different subdesigns by using the theory of flipping classroom horizon. Find the best design result in this domain in each subinstructional design; Finally, under the guidance of the theory of flipping classroom horizon, each subdesign realizes the optimal allocation of teaching resources. MATLAB simulation shows that under the conditions of initial design scheme and teaching resources setting, the improved deep learning method can improve the accuracy of physical education teaching design and shorten the convergence time of design, which is superior to the original deep learning method. Therefore, the deep learning method is used to analyze the instructional design of college physical education, which has a good design effect and is suitable for the instructional design of college physical education. [ABSTRACT FROM AUTHOR]

In order to understand the mental health status of contemporary college students, the research team of "College Students' psychological quality training" conducted mental health examination on nearly 6000 Chinese college students from 23 colleges and universities across the country. The results showed that about 16.51% of Chinese college graduates had serious mental health problems. The results of several recent studies on the mental health status of college graduates across the country show that the accuracy rate of mental behavior examination among college graduates across the country is about 16%, and the rate of people with unsound psychology or in a state of mental sub-health is higher, and there has been a psychological poverty group among college students. A large number of educational facts and scientific research have confirmed that sports are one of the most effective ways to promote students' physical and mental development, and it can be said that there is a very close relationship between college sports and the physical and mental health of college graduates. In order to promote the organic combination of college mental health education and college physical education, the research results will be based on in-depth investigation and understanding of the current situation of college students' psychological development under the new situation, and a systematic study of the relationship between college graduates' physical, sports, mental health knowledge, and psychological level. This paper establishes a theoretical model for the organic combination of mental health education and physical education in colleges and universities, and provides specific countermeasures for integrating psychological teaching into college physical education courses, providing a theoretical basis and reference for developing college physical education courses and improving psychological teaching. [ABSTRACT FROM AUTHOR]

Artificial intelligence is an emerging technology that revolutionizes human lives. Despite the fact that this technology is used in higher education, many professors are unaware of it. In this current scenario, there is a huge need to arise, implement information bridge technology, and enhance communication in the classroom. Through this paper, the authors try to predict the future of higher education with the help of artificial intelligence. This research article throws light on the current education system the problems faced by the subject faculties, students, changing government rules, and regulations in the educational sector. Various arguments and challenges on the implementation of artificial intelligence are prevailing in the educational sector. In this concern, we have built a use case model by using a student assessment data of our students and then built a synthesized using generative adversarial network (GAN). The dataset analyzed, visualized, and fed to different machine learning algorithms such as logistic Regression (LR), linear discriminant analysis (LDA), K-nearest neighbors (KNN), classification and regression trees (CART), naive Bayes (NB), support vector machines (SVM), and finally random forest (RF) algorithm and achieved a maximum accuracy of 58%. This article aims to bridge the gap between human lecturers and the machine. We are also concerned about the psychological emotions of the faculty and the students when artificial intelligence takes control. [ABSTRACT FROM AUTHOR]

As a training base for professional talents, colleges and universities continue to deliver high-quality service-oriented and technical-oriented talents for the country's production, construction, service, and other industries. College students will have to face higher-intensity and higher-density work in their jobs for the future. It requires college students to develop good exercise habits, learn sports knowledge, and build healthy physiques at the university stage so that they can adapt to heavy work in all walks of life. However, on the one hand, there is a relatively lack of research on the systematization of physical education management and the development of physical education resources; on the other hand, physical education in colleges and universities faces problems such as low level of physical education, low utilization of teaching resources, and declining teaching quality. In view of the above problems, this paper proposes the method of literature and materials to carry out the primary selection of the indicators of the evaluation system of physical education teaching environment in colleges and universities. Then, two rounds of screening are carried out for the primary indicators to determine the specific indicators of the evaluation system. Next, the analytic hierarchy process (AHP) is applied to construct the judgment matrix of the indicators at all levels, calculate the weight value of each indicator and do the consistency test, and establish a complete evaluation system of the physical education environment in colleges and universities. Finally, through empirical evidence, it is verified that the constructed evaluation system has operability and feasibility. The evaluation and measurement of colleges and universities carrying out physical education curriculum can ensure the correct and rapid development of physical education teaching and provide reference for the management of physical education resources in colleges and universities. [ABSTRACT FROM AUTHOR]

This paper establishes a hybrid education teaching practice quality evaluation system in colleges and constructs a hybrid teaching quality evaluation model based on a deep belief network. Karl Pearson correlation coefficient and root mean square error (RMSE) indicators are used to measure the closeness and fluctuation between the effective online teaching quality evaluation results evaluated by this method and the actual teaching quality results. The experimental results show the following: (1) As the number of iterations increases, the fitting error of the DBN model decreases significantly. When the number of iterations reaches 20, the fitting error of the DBN model stabilizes and decreases to below 0.01. The experimental results show that the model used in this method has good learning and training performance, and the fitting error is low. (2) The evaluation correlation coefficients are all greater than 0.85, and the root mean square error of the evaluation is less than 0.45, indicating that the evaluation results of this method are similar to the actual evaluation level and have small errors, which can be effectively applied to online teaching quality evaluation in colleges and universities. [ABSTRACT FROM AUTHOR]

Improving the quality of college physical education is of great significance to facilitating the integrated development of students' psyches and physical. Establishing a more systematic, effective, and social training needs of education quality evaluation hierarchy is also the centerpiece of the college physical culture education administration. Massive information technology provides new conception and methods to this, and supply advantage sustains for furtherance the education ecology development. Based on the network education system, this paper uses big data to quantify the evaluation indexes of physical education teaching, so as to actualize the timely dynamic evaluation of the process that is physical teaching and learning. This essay constructs the evaluation index system of college physical education teaching quality by combining mensurable and qualitative methods. On the basis of previous studies, an evaluation model of college physical education teaching quality based on artificial intelligence mass data calculation is designed. The experiment authenticates that the model evaluation risk coefficient is 1.93 lower than the optimized model. The experiment also proves that the model is conducive to elevating the education quality. [ABSTRACT FROM AUTHOR]

With the continuous development of social economy, education has received more and more attention. As an important part of higher education, it has been profoundly influenced by the era of data in recent years. In order to evaluate the impact of big data on higher education management, this paper introduced a time-varying lens algorithm (TLA) to analyze the business needs of teachers and education management by sorting out the business processes of education management, education thinking, and education practice. Through learning and mining the corresponding technology, improve the corresponding educational ability, and use big data to assist the management of higher education. The simulation results show that the time-varying clustering sampling algorithm is effective. [ABSTRACT FROM AUTHOR]