College Student Management Research Articles

Research on the Education Management of College Students under the Background of Big Data

With the continuous development of big data technology, the education management of college students has become more and more important. Therefore, colleges and universities should use big data technology to conduct a comprehensive research and analysis of the education management of college students, so as to improve the education quality of college students and realize the comprehensive growth of college students. This article discusses how to reform the education management method of college students and combines the latest educational big data technology. It can not only provide practical information for the education work of colleges and universities, but also provide students with personalized teaching programs for students to promote their overall growth.

Discussion on the Optimization Path of College Student Education Management under the Perspective of Internet

With the continuous development of Internet technology, "Internet +" mode has become an important driving force in all fields of society. It not only provides convenience for people's study, life, work and communication, but also promotes the optimization and innovation of traditional education management mode, making the dissemination of information more convenient and efficient. This paper aims to explore the impact of the Internet on the education management of college students, and put forward a series of reform and development suggestions based on the current challenges, in order to better meet the needs of students.

Research on the innovative value and path of the management of college students under the new media environment

Taking the wechat platform of the Communist Youth League of 10 vocational colleges in Zhejiang Province as the data collection object, the number of published articles and the number of reading were classified and statistically analyzed. The study found that the wechat official accounts of the Communist Youth League of universities had large differences in the number of publication times, unbalanced content of publication, and low participation of young students. Therefore, it puts forward the innovative value and path exploration of college league work under the new media environment.

Retracted: Innovation of Ideological and Political Education Management of College Students Based on IOT Big Data Technology in a Wireless Network Environment.

[This retracts the article DOI: 10.1155/2022/9585760.].

Collaborative Governance of College Student Management and Home School Communication Strategies

Collaborative Governance of College Student Management and Home School Communication Strategies

Refined education mechanism based on edge computing for college student management

Refined education mechanism based on edge computing for college student management

Construction and Adjustment Methods for Teacher-Student Relationship in College Student Management Based on Big Data Analysis

Building a harmonious Teacher-Student Relationship (TSR) is a necessary work for college student management, because different TSRs can result in different effects in student management and cultivation. However, in existing studies, the definitions of harmonious TSR given by different scholars are dimensionless, the understandings of the nature of TSR is not thorough enough, and the analysis of the influencing factors of TSR often lacks the support of theoretical evidences. To overcome these shortcomings, this paper aims to study the construction and adjustment methods for the TSR in college student management based on big data analysis. At first, the paper investigated the daily behavioral features of college students on online management platforms; then, with the help big data analysis and data processing techniques, this paper calculated the fitness degree of harmonious TSR between college students and the counselors and other administrators who engaged in student management works and have interacted with them. After that, based on the calculation results of the said fitness degree, this paper built a basic interactive network for college student management works, and gave the method for dividing student management groups. At last, experimental results verified the effectiveness of the proposed algorithm.

An In-Depth Discussion on the Education Management of College Students from the Perspective of New Media

In-depth discussion on the education management of college students from the perspective of new media is the main idea of the designed study. At present, the research and practice of school knowledge management mainly involves two aspects: teacher's personal knowledge management and also school-level knowledge management, and there are few researches on college students' self-knowledge management. Multi-channel information carriers such as the Internet, coal, books and magazines make their ideological concerns show a clear wide-area feature, covering various issues of history and reality, domestic and international, but it is precisely this kind of informatization. The extreme richness, rapid change and dispersion of various information in society also breed the superficial development of the ideological and cultural needs of contemporary college students. This paper gives then ovel suggestions.

Motivation of Student Management Subjects in Universities Based on Network Intelligence

With the intelligent development of the society and the development of the big data era, the network intelligence applications in various fields have deeply penetrated them, and colleges and universities, as the place where information technology is most widely used, have been profoundly affected by the network intelligence. In this context, besides the traditional use of digitalization, informatization, and networking to assist in managing students’ studies and life, the work of the main body of student management in colleges and universities is also gradually developing towards intelligence. In the research of this study, through the application and development of network intelligence, the intelligent research of college student management is carried out by using the technical advantages of massive data access, so as to improve the motivation of college student management subjects through intelligence, make students feel the orderly and reliable humanized management while improving the efficiency of student management, and provide sufficient technological guarantee for college management.

Challenges and Strategies of Student Management in Universities in the Context of Big Data

As the most active and knowledge-intensive university, the forefront of the use of network information technology, the education, management, and service mode of the school, and the ideology, learning methods, and behavioural habits of teachers and students will be profoundly affected by the era of big data. The current form of student management in universities is too old and needs to be replaced by a new management system. With the promotion of the construction of smart campus, the rapid development of big data technology has realised the innovation of student management in colleges and universities. This paper takes students of Wuhan University as the research object. By collecting various application data in the campus information system, the K-means algorithm in cluster analysis is used to classify students’ campus behavioural characteristics, and then the Apriori algorithm is used to correlate students’ behavioural characteristics with their academic performance. The experimental results show that there is a close relationship between the consumption behaviour, work and rest behaviour, study behaviour characteristics of different student groups, and their academic performance. Using the results of these analyses, universities can adopt differentiated management measures for different categories of students, which can help improve students’ academic performance as well as further enhance the efficiency of student management.

A Mental Health Management and Cognitive Behavior Analysis Model of College Students Using Multi-View Clustering Analysis Algorithm.

In this new era that is full of social changes, ongoing economic transformation, an abundance of information resources, and a fast pace of life, the pressure that people feel to compete with one another is also increasing day by day. Because of the vast differences in people's states of consciousness and worldviews, interpersonal relationships have become increasingly difficult to navigate. Students in higher education institutions will eventually emerge as the dominant demographic in society. Their mental health has a significant bearing on all aspects of life, including learning and future growth. An objective condition that must be met in order to guarantee that the next generation of talent will have a high level of overall quality is the improvement of the mental health of college students (CSMH) in the new era. One component of public health is the emotional well-being of students in higher education. The state of the public's health is consistently ranked among the most urgent problems facing modern society. However, there is not much hope for the Chinese CSMH. In order to effectively manage their mental health, a variety of educational institutions, including colleges and universities, have proposed a large number of management strategies for CSMH. The vast majority of these strategies are not targeted, and they do not offer a variety of management strategies that are based on the many different psychological states. It is necessary to first be able to accurately predict the mental health status of each individual college student in order to achieve the goal of improving the mental health management of students attending colleges and universities. This study proposes using a multi-view K-means algorithm, abbreviated as MvK-means, to analyze the CSMH's data on mental health. This is possible because the data can be obtained from multiple perspectives. This paper presents a multi-view strategy as well as a weight strategy in light of the fact that each point of view contributes in its own unique way. Different weight values should be assigned to each view's data, which will ultimately result in an improved evaluation effect of the model. The findings of the experiments indicate that the model that was proposed has a beneficial impact on the analysis of the data pertaining to the mental health of college students.

Design and Management of Comprehensive Art Student Information Database from the Perspective of Internet plus Education

With the rapid development of information technology and network technology, all kinds of data increase exponentially, and the traditional relational databases cannot handle these data well, which is also reflected in the sharp increase in the number of college students. The amount of students' information is increasing exponentially and the simple management method in the past can no longer meet the needs of the new situation. This paper adopts B/S mode and three-tier architecture and relies on network technology and ASP.NET technology to design and implement the student information management system. The system is divided into eight functional modules: comprehensive information inquiry for students, scholarship evaluation, evaluation and award, economic recognition, student loan management, student violation, communication and feedback, and system management. Different operation interfaces are designed according to four users with different permissions: students, class tutors, college administrators, and student affairs offices. This paper describes the system analysis, design, and implementation in detail. The practice results show that the initial use of the student information database management reflects well and achieves the expected goal. The system is easy to maintain and extensible and has good application value. The operation of the system has greatly improved the management efficiency of student affairs and enabled the student affairs administrators to complete various student affairs more efficiently. Campus information construction is becoming an important part of the overall construction of colleges and universities, and it is also a basic and continuous work. Accelerating the establishment of a set of comprehensive, perfect, and efficient student comprehensive management information systems is an urgent need to promote the modernization of college student management. The modernization, informatization, and standardization of college student management are a complex systematic project. Only by relying on modern information technology can we cope with the base pressure brought by the continuous enrollment expansion of college students, promote the flat and intensive utilization of college management information, and improve the efficiency and quality of service.

Student Management Method of Private Colleges and Universities Based on Geographic Information System and WIFI

In order to improve the student management effect of private colleges and universities, this paper combines geographic information system and WIFI to construct a private college student management system. In the structural design, this paper divides the platform into several modules according to the idea of modularization and narrates the function of each part. In the database design, this paper completes the construction of each function of the platform. In the process design, this paper determines the design process of the platform. Finally, this paper studies the key technologies involved in the system and evaluates students’ trajectory positioning and management effects in colleges and universities. The research shows that the student management system of private colleges and universities based on geographic information system and WIFI proposed in this paper can effectively improve the student management effect of private colleges and universities.

Design of the Student Attendance Management System Based on the Internet of Things Technology

The IoT refers to the linking of items to a network through message-generating devices; in the connection process, communication and information circulation are carried out through the information dissemination medium to realize intelligent identification, tracking, supervision, and other functions. Attendance management is a system for assessing employee attendance, including being late, leaving early, and asking for leave. Student attendance refers to the attendance rate of students in class. This article aimed to study the design and research of the student attendance management system based on the Internet of things technology, and use this system to accurately record students’ attendance and develop good habits for students. An effective attendance management company has been developed to enhance the collection of information for student management in universities, to keep track of teachers’ and students’ teaching attendance in real time, and to connect teachers and students in real time using computer technology. Access to the Android version of the software speeds up the collection and processing of information and can play an important role in improving the efficiency of personnel management. On the basis of analysing the operation logic of the attendance system, matching programs and the attendance system software are designed. The experimental results of this article show that the attendance rate of students with utilitarian personality is the highest, as high as 70%; the attendance rate of students with helpless personality is 13%; the attendance rate of students who follow the current personality accounted for 10%; and the attendance rate of nonmotivated students accounted for 7%. It can be seen from this that personality is an important factor affecting students’ attendance rate. The attendance rate of positive psychology with goals is the highest, and the attendance rate of students without clear goals is the lowest. The student attendance management system of the Internet of things technology has been applied in practical work, but with the continuous construction and development of the school, the continuous improvement of new software and hardware, and the emergence of new needs in practical work, the student attendance management system is easy to crash when processing a large amount of data at the same time.

A Scalable Blockchain Framework for ELA Assessment

As a popular technology in the information age, blockchain is having a profound impact on various industries, including the field of education. Blockchain technology can accelerate the modernization of education in China, adapt to the new situation of epidemic prevention and control needs, and promote the renewal of the management and training modes of college students. Blockchain technology is decentralized, tamper-proof, traceable, trackable, open and transparent, which is conducive to the realization of individual student-centered teaching and learning, as well as an open, and transparent teaching process, which can motivate the learning motivation of English majors and improve the effectiveness of the student management and training models. To address the problem of low accuracy of the traditional English proficiency classification methods, this article aims to explore the application of blockchain technology in the management and training model of English majors and its feasibility. We propose a proficiency evaluation model based on a Discrete Hopfield Neural Network (DHNN). Firstly, the hierarchical analysis method is used to construct the evaluation index system of students’ English ability, and then the ability classification indexes are divided into 5 levels.The network achieves the classification of students’ English proficiency through the associative memory of the classification criteria, and the classification results are compared with those of the BPNN model. The simulation results show that the classification accuracy of the BPNN model is 80.0% and that of the DHNN model is 100.0%. The DHNN model has improved the classification accuracy and generalization ability, and the model establishment process is simple and the results are intuitive, which verifies the effectiveness of the proposed model

College Students' Behavior Initiative, Psychological Availability, and Innovation and Entrepreneurship: The Mediating Effect of Interest Orientation

The features of college students’ initiative character and psychological availability can generate great influence on their Innovative and Entrepreneurship (I&E). Relevant existing studies paid insufficient attention on the interest orientation management of college students’ I&E from the perspective of I&E education, and few of them viewed the problems of the behavior initiative and psychological availability of college students’ I&E from the perspective of individual student. To fill in these research blanks, this paper aims to analyze the relationship among behavior initiative, psychological availability, and I&E interest orientation of college students. At first, based on the evaluation data of the behavior initiative and psychological availability features of college students’ I&E, tags of their I&E behavior were created, and the behavior preferences of their I&E were predicted based on the machine learning algorithm. Then, the prediction results of I&E interest were tested using the mediating effect method, and it’s found that when behavior initiative and psychological availability features affect college students’ I&E performance, interest orientation plays a mediating role in the process. The experiment verified the effectiveness of the proposed prediction model and gave the analysis results of the mediating effect.

Humanized Management of College Students Based on Machine Perspective and Intelligent Monitoring System

In order to improve the effect of humanized management of college students, this article builds a humanized management system for college students based on the machine perspective and intelligent monitoring system, studies its hardware and software systems, and introduces the basic principle of evanescent mode resonators. Moreover, the formulas of the resonant frequency and the unloaded Q value of the resonator are deduced by the equivalent circuit of the evanescent mode resonator, and the variation curve of the unloaded Q value and the resonant frequency of the actual resonator is obtained by HFSS simulation. In addition, this article constructs a humanized management model for college students based on the machine perspective and intelligent monitoring system. The experimental research results show that the intelligent monitoring system based on the machine perspective proposed in this article has good effects and can effectively improve the quality of humanized management of college students.

Research on Innovative Mechanism of Student Management in Private Colleges and Universities

Research on Innovative Mechanism of Student Management in Private Colleges and Universities

Research on the Problems and Countermeasures of Student Management in Private Colleges and Universities

Research on the Problems and Countermeasures of Student Management in Private Colleges and Universities

Artificial Intelligence of Internet of Things Based on Machine Learning and College Student Management

Under the background of the development of higher education, according to the characteristics of college student management, after analyzing its background and practical significance, this study constructs an intelligent college student management system of Internet of things based on machine learning. The data volume of the Internet of things is huge, so ensuring the normal and efficient operation of the system is the primary goal. In this study, the data management model of the system is constructed with the help of cyclic neural network in machine learning algorithm to predict the data and optimize the computer program. At the same time, the system data are filled and classified by the k-nearest neighbor model, and the data are trained and simulated by constructing a safe bilstm neural network system. Because the information related to students in the university database involves personal privacy, in order to ensure the security of the system and avoid relevant data leakage, in the judgment standard of configuration error data flow, this study calculates the monitoring abnormal data and loss function through the dark network flow and ip2vec algorithm, so as to establish the system abnormal monitoring model and identify the system error data flow. Finally, it constructs the college student management system and expounds on the basic requirements of the system use cases. After a series of tests of system performance, capacity, and stability, the results meet the basic requirements of system operation, which provides a certain reference for the application of college student management in the future.