Teaching Resources In Colleges Research Articles

Integration and Optimization of Educational Teaching Resources in Colleges and Universities Based on Clustering Algorithm

The paper presents Centroid Ranking Optimized Clustering (CROC), a novel approach aimed at enhancing educational teaching and resource optimization through advanced clustering techniques. CROC integrates centroid-based clustering with ranking optimization strategies to segment students or educational resources into meaningful clusters, facilitating personalized learning experiences and targeted interventions. Experimental analysis conducted on real-world educational datasets demonstrates that CROC outperforms traditional clustering algorithms in terms of clustering quality, accuracy, and interpretability. The findings suggest that CROC holds significant promise for informing data-driven decision-making in educational settings, enabling educators to better understand student performance patterns, identify at-risk students, and tailor instructional strategies to meet diverse learning needs. Experimental analysis on real-world educational datasets reveals that CROC achieves a Silhouette Score of 0.75 and a Davies-Bouldin Index of 0.40 on the MathScores dataset, outperforming traditional algorithms such as k-means (Silhouette Score: 0.68, Davies-Bouldin Index: 0.53), Hierarchical (Silhouette Score: 0.62, Davies-Bouldin Index: 0.57), and DBSCAN (Silhouette Score: 0.45, Davies-Bouldin Index: 0.78). Similarly, on the EnglishTest dataset, CROC attains a Silhouette Score of 0.82 and a Davies-Bouldin Index of 0.35, surpassing k-means (Silhouette Score: 0.74, Davies-Bouldin Index: 0.47), Hierarchical (Silhouette Score: 0.68, Davies-Bouldin Index: 0.52), and DBSCAN (Silhouette Score: 0.53, Davies-Bouldin Index: 0.68). These findings underscore the effectiveness of CROC in clustering educational data, enabling personalized learning experiences and data-driven decision-making in educational settings.

The Growth of Contemporary Music Subject and the Reform of Music Teaching in Universities

In order to promote the growth of contemporary music and the reform of music, this article designs an improved collaborative filtering (CF) algorithm to solve the problem of sparse matrix in traditional recommendation algorithms. The data matrix is dimensionally reduced to find the nearest neighbor, so as to realize personalized recommendation of music teaching resources in colleges and universities. The test results show that the accuracy of the proposed teaching resource recommendation algorithm is improved by 22.56% compared with the traditional CF algorithm. The improved CF algorithm can provide more accurate prediction, and the recommendation effect of the improved algorithm is better than the original algorithm, which can effectively avoid the sparse matrix problem faced by the CF algorithm, and provide technical support for the development of contemporary music discipline and the reform of music discipline.

Informatization Construction of Civic Education in Colleges and Universities under the Integration of Big Data Technology

Abstract Education informatization is the application of modern information technology in the field of education, this paper uses the method of clustering and factor analysis in big data technology to analyze the main contents and influencing factors of the informatization construction of the Civic and Political Education in colleges and universities. Studying the application of multimedia technology in the field of education, constructs the main framework of the informatization construction of Civic and Political Education in colleges and universities. The method of factor analysis is used to derive the number of factors affecting the construction of informationization of civic and political education, and the main construction direction of the informationization of civic and political education is proposed according to the variance explanation rate of the factors. Combined with cluster analysis, we explore the effect of computerized teaching resources on the digitization of Civic and Political Education in colleges and universities. The informationization of Civic and Political Education in colleges and universities is reflected in the two aspects of the development degree and utilization degree of the digital resources of Civic and Political Education in colleges and universities. The results show that informationized teaching resources such as Civics multimedia materials, Civics online courses, various types of CAI courseware, Civics e-books, and other informationized teaching resources are the most frequently developed informationized teaching resources in colleges and universities. 80%, 75%, 60%, and 65% are the development degrees that correspond to each other.

Research on Intelligent Development and Practice of Accounting Laboratory Courses in Colleges and Universities in the Context of Interdisciplinary Cooperation

Abstract In this paper, an innovative solution is proposed to address the problems of single content design, lack of relevance and specialized training in traditional accounting laboratory courses. In interdisciplinary cooperation, an efficient intelligent assistance model for accounting laboratory courses is constructed by combining the collaborative filtering recommendation model and K-Means clustering algorithm. The model significantly improves the recommendation accuracy and computational efficiency by optimizing the cosine similarity calculation and introducing the similarity-weighted average, combined with the enhanced dichotomous K-means algorithm. After dataset testing and practical application verification in a university, the model effectively improves the quality of personalized recommendation of teaching resources. In particular, students’ mastery of knowledge points K2 and K3 is more adequate through the model recommendation, while their mastery of K8 is significantly improved. In addition, the model successfully identifies the similarity between students, which lays the foundation for providing more personalized learning resources. Overall, the model solves the traditional problem of accounting laboratory courses and provides a practical methodology for intelligent recommendation of teaching resources in universities.

Research on Teaching Resource Management in Colleges and Universities Based on Multiple Data Chain Networks

Abstract In this paper, we first take the datalink network as the entry point and construct a university teaching resource management model based on a multivariate datalink network. A Link-22 data chain time synchronization algorithm with KF-RTPT is proposed to address the actual existence and unavoidable time deviation based on accuracy and timestamp acquisition errors. Meanwhile, a time slot allocation and optimization algorithm designed to maximize message transmission benefits is being developed to optimize the allocation of node time slot requirements. Finally, the constructed teaching resource management model is empirically analyzed from three perspectives: error optimization, dynamic time slot allocation, and model application effect. According to the findings, the KF-RTPT algorithm increases motion error efficiency by 3.83 in low-speed motion states and 8.16 in high-speed motion states when compared to the conventional RTT method. This effectively eliminates motion error and boosts the effectiveness of teaching and managing resources in colleges and universities.

The Development Trend of Innovative Teaching of Dance in Colleges and Universities Based on Clustering Algorithm in the Context of Big Data

Abstract This paper establishes a model for teaching dance innovation in colleges and universities based on big data. Using a clustering algorithm to obtain the characteristics of dance teaching using affiliation assignment calculation to maximize the fuzzy indicators, the dance innovation teaching indicators are divided to improve the assessment accuracy. The optimization of dance teaching assessment indicators is normalized to complete the data processing and clustering in the teaching system and combined with the user preference to divide the student group based on similar characteristics. The results show that 45.00% of the student’s performance ability of physical balance is excellent, and the dance teaching classroom question score is 93. Big data technology can effectively integrate and categorize the existing dance teaching resources in colleges and universities, thus improving the quality of dance teaching.

Cluster analysis and its application in teaching resources of university curriculum: A personalized method

AbstractThe current personalized recommendation methods for teaching resources of university courses suffer from poor recommendation effectiveness due to the absence of user tags. To address this issue, a new personalized recommendation method based on cluster analysis is proposed. The proposed method leverages web crawler technology to obtain user tags, followed by processing the tags to remove meaningless terms, normalize word forms, and perform data processing. The processed tags are used to calculate user interest preferences for each tag cluster generated by clustering. Based on this, a user interest model is built, and user similarity is calculated to determine the recommendation score of each resource. The recommended resources are then ranked according to their recommendation score and presented to the target user. Experimental results demonstrate that the proposed method achieves high accuracy, recall rate, and F1 value for personalized recommendation of teaching resources in colleges and universities. In comparison, the method proposed in this paper has a significantly shorter recommendation time of 10.65 s. Further, the proposed model not only takes less time but also has higher recommendation efficiency when compared with existing personalized recommendation methods.

Experiential Learning Practices and Career Courses: Predictors of First Destination Outcomes

This study examined connections between experiential learning practices, mandatory career courses, and positive first destination outcomes of graduates from a large public institution prior to and during the COVID-19 pandemic. The rising cost of education and competition among universities has led to consumer demands for information pertaining to their return on investment. Universities have been encouraged to provide first-destination outcomes for graduates as a way to show the value of their degree programs. To strengthen these outcomes, many programs encourage or mandate experiential learning known as high-impact practices (HIPs) and career courses to prepare emerging adult learners for the transition to employment or further education. However, little is known as to the impact these practices have on the first-destination outcomes of these graduating students. This study identified specific experiential practices which proved beneficial to securing employment or acceptance to continued education, with an important caveat that career courses added only limited benefit for some respondents. These findings will better inform the allocation of university teaching resources and are a basis for further study of career practices in higher education.

Research on the integration of online teaching resources in higher education institutions under the perspective of industry-education integration

Abstract The purpose of exploring the development mode of online teaching resources in colleges and universities is to enhance the utilization rate of online teaching resources to promote the diversification of teaching methods. In this paper, based on big data technology, a cloud education platform integrating online teaching resources in colleges and universities is constructed under the perspective of integrating industry and education, and the architecture and functions of the cloud education platform are explained. Then the collaborative filtering algorithm is used to filter and collect the information on online teaching resources, and the Pearson correlation formula is used to pre-process the data and help users to recommend teaching resources. Finally, the pre-processed data are filtered and analyzed using the multilayer perceptron technology under the deep learning model. To verify the practicality of the cloud education platform proposed in this paper, the platform’s performance is evaluated by combining MAE metrics with RMSE metrics. In terms of load capacity, the platform has the best load capacity when the number of users is 200. From the performance test, the average transmission rate of the cloud education platform is 8.1% and 0.93% higher than that of NetEase Cloud Classroom and Tencent Classroom, and the average transmission time is 7.09 s. From the practicality analysis, the average value of the MAE index is 0.317%, and the average value of the RMSE index is 0.232%. This shows that the cloud education platform can effectively integrate university online teaching resources and help universities achieve diversified development of teaching methods.

Retracted: Method of Ideological and Political Teaching Resources in Universities Based on School-Enterprise Cooperation Mode

Retracted: Method of Ideological and Political Teaching Resources in Universities Based on School-Enterprise Cooperation Mode

Multimodal Corpus Construction and Research of Intercultural Communication Based on Multiple Regression Equation

Abstract To promote the transformation of education and teaching concepts, guide the reform of teaching content and teaching methods, and promote the joint construction and sharing of high-quality curriculum teaching resources in colleges and universities through modern information technology, improve the quality of talent training and serve the construction of a learning society. Using video analysis and website research methods, the author takes the cross-cultural communication courses offered by 22 universities in the national excellent resource sharing courses published by the multimodal online corpus of “Love Course Network” as the research sample, taking the playability of teaching videos, noise level, picture definition, multimedia courseware playing, utilization of curriculum resources and network interaction as research contents, the construction and application of teaching videos are analyzed in depth. The results show that, in the construction of intercultural communication sharing courses, there are still problems such as poor playability of teaching videos, noise and poor picture clarity.

Managing the integration of teaching resources for college physical education using intelligent edge-cloud computing

These days, colleges and universities have accumulated many resources in teaching and scientific research due to the acceleration of education information in China. However, many teaching resources are in short supply due to a lack of standardized resource construction and the closeness of management methods. Physical education significant teaching resources in Chinese colleges and universities must be utilized. If not integrated, it would seriously restrict the development of physical education in China. However, the traditional management of physical education teaching resources tends to worsen the data management, which is easy to cause the loss of physical education teaching resources data. With the development of the Internet of Things (IoT), cloud computing, and other technologies, intelligent edge cloud computing can ensure the integrity of physical education teaching resources and improve utilization. In this paper, cloud computing is used to manage physical education teaching resources in colleges and universities, and virtualization technology is used to research physical education teaching resources. Moreover, a resource scheduling method is proposed to ensure equal load distribution across various edge resources. The proposed strategy also provides increased utilization levels for computing resources. The comparison between the sports teaching resources under cloud computing and traditional sports teaching resources found that cloud resource management's sharing degree of teaching equipment has increased by 20.6% compared with conventional resource management. The sharing degree of courses has increased by 16.5%, and the utilization rate of sports venues has increased by 27.1% compared with traditional resource management. The utilization rate of sports film and television materials increased by 30.7%. Teachers and students benefit significantly from college and university teaching resources in the context of cloud computing. It demonstrates how cloud computing may assist colleges and universities in managing and integrating their teaching resources more effectively. The management and integration of college sports resources through cloud computing can promote the mutual exchange of college resources and have practical significance for the development of college education.

Status and improvements of transforming scientific research achievements into teaching resources in universities

There are many practical difficulties in the concrete implementation of transforming scientific research results into teaching resources. Through analyzing the existing transformation forms and problems, a comprehensive transformation model is discussed, and a comprehensive evaluation system covering teachers and students is established. Establish a guarantee mechanism from multiple channels such as capital investment, system guarantee, and performance reward, escort the transformation of scientific research results into teaching resources, and promote universities to strengthen the talents training.

Text Mining and Teaching Methods of College Teaching Resources Based on College Students' Mental Health

Text Mining and Teaching Methods of College Teaching Resources Based on College Students' Mental Health

On the Teaching Reform of Badminton Courses in Colleges and Universities Under the Background of "Internet+"

In the new era of the rapid development of Internet information. College physical education needs to be reformed in order to meet the development of The Times, in order to promote the combination of college badminton and science and technology, and drag the development of discipline. This paper explores the teaching reform of badminton course in colleges and universities under the background of "Internet +" by means of literature, expert interview, and inductive and deductive methods, and concludes that due to the influence of traditional teaching ideas, badminton teaching in colleges and universities presents problems such as passive acceptance by students, emphasis on technology and neglect of theory, and unreasonable assessment methods. With the continuous progress of science and technology, many new technologies are constantly appearing in people's vision, which has a great impact on people's life, work and study. The application of "Internet +" in the field of college physical education has produced a huge effect. Especially during the pandemic, it plays an irreplaceable role. Conclusion: Under the background of "Internet +", we should explore the reform of badminton teaching in colleges and universities, fully explore the essence of online badminton course, improve the teaching efficiency of badminton course, and provide new ideas and methods for the reform of badminton course and the formation of high-quality teaching resources in colleges and universities.

Analyzing the Design and Promotion of Ideological and Political Content in Online Finance and Economics Courses

In the context of the new media age, the emergence and development of finance and economics courses along with online course resources have greatly enriched the presentation of teaching resources in colleges and universities. However, subjected to the flawed design and poor promotion of ideological and political contents, which are less popular, online finance and economics courses often do not reflect the meaning well or maximize the application of the courses’ ideological and political reform. This paper explores the dilemma and reasons for the promotion of the courses’ ideological and political content, in hope to provide suggestions for the design and promotion of ideological and political content in online finance and economics courses in colleges and universities.

Recommendation Method of Online Teaching Resources in Colleges and Universities Considering Different User Preference Factors

In order to improve the recommendation performance of online teaching resources in colleges and universities and the learning efficiency of users, this paper considers user preference factors and studies the recommendation method of online teaching resources in colleges and universities. This paper selects different user preference factors and extracts preference keywords and builds a keyword projection model for different user preference resources based on this. In this paper, Markov is used to construct a keyword probability model, and the TF-IDF algorithm is introduced to refine online teaching resources. According to the calculated closeness of the resources required by the user, this paper realizes the accurate recommendation of resources. The experimental results show that each recommendation performance index of this method has reached a high value. The recommendation accuracy rate of this algorithm is the highest at 82.2%, the recall rate is the highest at 78.7%, the F value is the highest at 83.5%, and the average absolute error is lower than 0.56. And the successful recommendation rate of this method is as high as 97.6%.

Study on the Application of Digitized Resources in English Language Teaching under a Blended Teaching Model

In the post-pandemic era, with the constant updating and development of information technology, both at home and abroad, the close connection between the modern education system and information technology has been demonstrated. Along with the continuous innovation of modern educational technology tools, the practical application about blended teaching has been developed significantly, and the value of this model, which integrates the advantages of lecture-based teaching and independent learning, for effective teaching of English education has received wide attention. Therefore, in the current educational environment, exploring the application of digital teaching resources in colleges and universities, based on the blended teaching mode, under the conditions of information technology has become a comprehensive need to adapt to the new educational environment, as well as improve the teaching effectiveness. The research background and content of this paper has been summarized by sorting out the current teaching situation in the context of the current pandemic and the background of the development of the blended teaching model, while combining the definition of the core concept, to discusses the strategies for developing and applying digitized teaching resources to teaching practice under this model, thereby to outline the teaching effects produced by the application of this model. Meanwhile, it is further argued that the teaching and practice process of foreign language education needs to continuously absorb advanced educational concepts, timely update and improve teaching methods and develop and utilize multimodal teaching resources, in order to provide a guarantee for the overall improvement of teaching quality, enhance students’ fully comprehensive cognition and understanding of English language learning, and exert sustainable teaching effectiveness.

Research on the Application of Artificial Intelligence Wireless Network Technology in the Optimization of University Resources

With the increase of teaching resources in universities, allocation for teaching resources has gradually attracted people’s attention. How to optimize and reorganize the numerous teaching resources so as to maximize the teaching efficiency and achieve the best teaching effect is a question that the majority of college management workers must think deeply. Due to the development of computer science, artificial neural networks and wireless networks have made considerable progress. This article optimizes the resources of colleges and universities from these two aspects. First, this work proposes an improved artificial neural network to optimize school resources. The algorithm pointed out that the adaptive genetic algorithm itself has problems such as slow evolution speed and poor individual diversity of the population. After that an improved adaptive genetic algorithm is proposed to optimize BP network training process. By introducing individual evolutionary trend adjustment parameters, a new calculation formula for crossover probability as well as mutation probability is constructed. Improved BP algorithm can effectively avoid the shortcomings of local minima. Second, additional momentum and adaptive learning rate strategies are used to optimize BP network to promote the efficiency for network training. Third, the artificial intelligence network is deployed in the wireless network, and the wireless network will complete the work of data collection, processing, and transmission, so as to optimize the resources of colleges and universities.

Method of Ideological and Political Teaching Resources in Universities Based on School-Enterprise Cooperation Mode

The personalized recommendation system influences the recommendation of ideological and political teaching resources in universities, resulting in a high MAE score. As a result, under the school-enterprise collaboration paradigm, this study proposes a customised recommendation approach for ideological and political teaching resources in colleges and universities. The ideological and political teaching resource bank is developed against the backdrop of the teaching paradigm that combines universities and businesses. Learners’ browsing data history is gathered to create a learning interest model for them. A hybrid collaborative filtering recommendation method was devised, and a recommendation engine was established by Taste component, taking into account individualised resource recommendation needs and information entropy weight distribution mode. When compared to previous techniques, the developed customised recommendation method considerably enhances the recommendation quality of instructional resources and reduces MAE by 29% and 34%, respectively.