Pub Date : 2021-01-01DOI: 10.1109/ICEKIM52309.2021.00167
Anping Ji, Cees Lewin, Xiure Zhang, Haibao Wang
The evaluation of the quality of professional degree postgraduate education of local universities is an important part of higher education. This article examines the four main quality factors of the quality of professional graduate education in local universities, uses a multiple regression model, and then combines the weighting method to evaluate each factor, and finally forms an evaluation system. The system index values are obtained from statistical analysis after the questionnaire. 21 indicators constitute an indicator system of 4 quality factors, and then they are weighted and weight coefficients are obtained reasonably to obtain a multiple regression model. The results indicate that the guiding role of graduate tutors and the management system play a key role, while the role of curriculum teaching and industry-university-research cooperation is small. Combining the results of the questionnaire survey and evaluation system analysis, suggestions for improvement in the training of professional degree graduate students in local universities are put forward.
{"title":"Quality Assurance of Professional Degree Graduate Education in Local Universities Based on Statistical Analysis","authors":"Anping Ji, Cees Lewin, Xiure Zhang, Haibao Wang","doi":"10.1109/ICEKIM52309.2021.00167","DOIUrl":"https://doi.org/10.1109/ICEKIM52309.2021.00167","url":null,"abstract":"The evaluation of the quality of professional degree postgraduate education of local universities is an important part of higher education. This article examines the four main quality factors of the quality of professional graduate education in local universities, uses a multiple regression model, and then combines the weighting method to evaluate each factor, and finally forms an evaluation system. The system index values are obtained from statistical analysis after the questionnaire. 21 indicators constitute an indicator system of 4 quality factors, and then they are weighted and weight coefficients are obtained reasonably to obtain a multiple regression model. The results indicate that the guiding role of graduate tutors and the management system play a key role, while the role of curriculum teaching and industry-university-research cooperation is small. Combining the results of the questionnaire survey and evaluation system analysis, suggestions for improvement in the training of professional degree graduate students in local universities are put forward.","PeriodicalId":337654,"journal":{"name":"2021 2nd International Conference on Education, Knowledge and Information Management (ICEKIM)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122012214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.1109/ICEKIM52309.2021.00048
Jiao Yanli, Gao Dayong, Liu Yong
Online education is an important part of education services. It widens the channels and means of moral education, and is conducive to building a network, digital, personalized and lifelong education system. This study analyzes the characteristics of online moral education evaluation. On the premise of fully considering the initiative, sustainability and creativity of learners in the learning process, self-evaluation is added to the evaluation results. Based on the analysis of online learners' learning process data, this paper establishes a personalized formative moral education evaluation model. In addition, this study makes an empirical analysis to provide a feasible solution to the effectiveness of moral education evaluation.
{"title":"Research on formative moral education evaluation model of online learners based on data driven","authors":"Jiao Yanli, Gao Dayong, Liu Yong","doi":"10.1109/ICEKIM52309.2021.00048","DOIUrl":"https://doi.org/10.1109/ICEKIM52309.2021.00048","url":null,"abstract":"Online education is an important part of education services. It widens the channels and means of moral education, and is conducive to building a network, digital, personalized and lifelong education system. This study analyzes the characteristics of online moral education evaluation. On the premise of fully considering the initiative, sustainability and creativity of learners in the learning process, self-evaluation is added to the evaluation results. Based on the analysis of online learners' learning process data, this paper establishes a personalized formative moral education evaluation model. In addition, this study makes an empirical analysis to provide a feasible solution to the effectiveness of moral education evaluation.","PeriodicalId":337654,"journal":{"name":"2021 2nd International Conference on Education, Knowledge and Information Management (ICEKIM)","volume":"201 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128235262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.1109/ICEKIM52309.2021.00105
He Jiangxin, Xu Zhiguo
Database technology is a core technology of information system and a method of computer-aided management of data. The key technology lies in how to organize and store data, and to help people obtain and process data efficiently. College students are not fully mature in body and mind, so as a relatively concentrated and large vulnerable group of the new crown pneumonia virus, there are all kinds of anxiety and panic. Due to the need of epidemic prevention and control, it is impossible to conduct face-to-face interviews, only with the help of Internet big data technology for online psychological evaluation. In order to help schools to improve and build psychological crisis early warning mechanism, psychological crisis response mechanism and psychological crisis recovery mechanism and other intervention mechanisms. This paper puts forward practical plans and strategies for psychological crisis intervention in colleges and universities, in order to promote the effective development of psychological crisis intervention for college students, so as to improve their physical and mental health.
{"title":"Research on Mental Health Assessment and Crisis Intervention Mechanism of University Students with Data Technology","authors":"He Jiangxin, Xu Zhiguo","doi":"10.1109/ICEKIM52309.2021.00105","DOIUrl":"https://doi.org/10.1109/ICEKIM52309.2021.00105","url":null,"abstract":"Database technology is a core technology of information system and a method of computer-aided management of data. The key technology lies in how to organize and store data, and to help people obtain and process data efficiently. College students are not fully mature in body and mind, so as a relatively concentrated and large vulnerable group of the new crown pneumonia virus, there are all kinds of anxiety and panic. Due to the need of epidemic prevention and control, it is impossible to conduct face-to-face interviews, only with the help of Internet big data technology for online psychological evaluation. In order to help schools to improve and build psychological crisis early warning mechanism, psychological crisis response mechanism and psychological crisis recovery mechanism and other intervention mechanisms. This paper puts forward practical plans and strategies for psychological crisis intervention in colleges and universities, in order to promote the effective development of psychological crisis intervention for college students, so as to improve their physical and mental health.","PeriodicalId":337654,"journal":{"name":"2021 2nd International Conference on Education, Knowledge and Information Management (ICEKIM)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128546034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.1109/ICEKIM52309.2021.00129
Wang Xiaoying, Shen Qian, Guo Jialiang
Due to the tremendous progress of technology and the increasing complexity of experiments, the era of big data has come., which makes the sample data we collect more dense and continuous, and even reflects a certain functional law. Traditional data analysis technology faces many limitations in information data mining in the era of big data. Functional data analysis is a theory and method for studying how to mine intrinsic information knowledge from infinite dimensional and irregular observation data. The classification method based on the functional perspective can not only mine traditional structured data information, but also explore the classification rules of unstructured data, which is of great significance for enriching information mining technology in the era of big data. This article discusses the classification of functional data. Firstly, it preprocesses the abnormal curve based on the centrality and externality of the functional data depth; then combines the functional data non-parametric classification method to calculate the posterior probability value of the given curve belonging to each category, and classify the unknown curve according to the principle of maximum posterior probability; finally gets better classification results on simulation data and instance data.
{"title":"Research on Nonparametric Classification Method of Functional Data","authors":"Wang Xiaoying, Shen Qian, Guo Jialiang","doi":"10.1109/ICEKIM52309.2021.00129","DOIUrl":"https://doi.org/10.1109/ICEKIM52309.2021.00129","url":null,"abstract":"Due to the tremendous progress of technology and the increasing complexity of experiments, the era of big data has come., which makes the sample data we collect more dense and continuous, and even reflects a certain functional law. Traditional data analysis technology faces many limitations in information data mining in the era of big data. Functional data analysis is a theory and method for studying how to mine intrinsic information knowledge from infinite dimensional and irregular observation data. The classification method based on the functional perspective can not only mine traditional structured data information, but also explore the classification rules of unstructured data, which is of great significance for enriching information mining technology in the era of big data. This article discusses the classification of functional data. Firstly, it preprocesses the abnormal curve based on the centrality and externality of the functional data depth; then combines the functional data non-parametric classification method to calculate the posterior probability value of the given curve belonging to each category, and classify the unknown curve according to the principle of maximum posterior probability; finally gets better classification results on simulation data and instance data.","PeriodicalId":337654,"journal":{"name":"2021 2nd International Conference on Education, Knowledge and Information Management (ICEKIM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129224283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.1109/ICEKIM52309.2021.00061
Yao Li
Massive Open Online Courses (MOOC) has become a hot topic in the field of education, which has caused widespread attention and influence in the field of higher education in recent years. Many top universities in the world have already joined MOOC. As a large-scale open online learning system, MOOC has broken the old rules of global academic exchange and cooperation. It not only established a new order, logic and mechanism for the internationalization of higher education, but also provided a new structure and opportunity for the globalization of higher education. This paper will discuss the impact of MOOC globalization on the higher education equity and the development trend of higher education MOOC in Mainland China in the context of globalization from the perspective of higher education.
大规模在线开放课程(Massive Open Online Courses, MOOC)近年来在高等教育领域引起了广泛的关注和影响，成为教育领域的热门话题。世界上许多顶尖大学已经加入了MOOC。MOOC作为一种大规模的开放式在线学习系统，打破了全球学术交流与合作的旧规则。它不仅为高等教育国际化建立了新的秩序、逻辑和机制，而且为高等教育全球化提供了新的结构和机遇。本文将从高等教育的角度探讨MOOC全球化对高等教育公平的影响，以及全球化背景下中国大陆高等教育MOOC的发展趋势。
{"title":"The Impact of Massive Open Online Courses Globalization on the Educational Equity","authors":"Yao Li","doi":"10.1109/ICEKIM52309.2021.00061","DOIUrl":"https://doi.org/10.1109/ICEKIM52309.2021.00061","url":null,"abstract":"Massive Open Online Courses (MOOC) has become a hot topic in the field of education, which has caused widespread attention and influence in the field of higher education in recent years. Many top universities in the world have already joined MOOC. As a large-scale open online learning system, MOOC has broken the old rules of global academic exchange and cooperation. It not only established a new order, logic and mechanism for the internationalization of higher education, but also provided a new structure and opportunity for the globalization of higher education. This paper will discuss the impact of MOOC globalization on the higher education equity and the development trend of higher education MOOC in Mainland China in the context of globalization from the perspective of higher education.","PeriodicalId":337654,"journal":{"name":"2021 2nd International Conference on Education, Knowledge and Information Management (ICEKIM)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123890811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.1109/ICEKIM52309.2021.00104
Xiaoning Zhu
With the development of information technology and the expansion of the floating population in China, the level of urbanization is constantly improving. Big data will set off a new wave, affecting the life and production mode of floating population, and changing their thoughts and concepts in the new era. In the wave of big data, as the main body of urbanization, the citizenization of floating population is an important embodiment of high-quality urban development. Based on the perspective of urban adaptation, this paper constructs a model of the effect of the education level of floating population on residence willingness, and analyzes how the education level of floating population affects their residence willingness by using the dynamic monitoring survey data of China's floating population in 2017 and Logit model.
{"title":"Based on big data to analyse the influence of education on the residence willingness of floating population","authors":"Xiaoning Zhu","doi":"10.1109/ICEKIM52309.2021.00104","DOIUrl":"https://doi.org/10.1109/ICEKIM52309.2021.00104","url":null,"abstract":"With the development of information technology and the expansion of the floating population in China, the level of urbanization is constantly improving. Big data will set off a new wave, affecting the life and production mode of floating population, and changing their thoughts and concepts in the new era. In the wave of big data, as the main body of urbanization, the citizenization of floating population is an important embodiment of high-quality urban development. Based on the perspective of urban adaptation, this paper constructs a model of the effect of the education level of floating population on residence willingness, and analyzes how the education level of floating population affects their residence willingness by using the dynamic monitoring survey data of China's floating population in 2017 and Logit model.","PeriodicalId":337654,"journal":{"name":"2021 2nd International Conference on Education, Knowledge and Information Management (ICEKIM)","volume":"454 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116176193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.1109/ICEKIM52309.2021.00164
Danning Li
Based on delicacy management theory and related principles, the management scheme of the whole process of postgraduate cultivating established on external PDCA cycle and key links of internal PDCA cycle are designed using PDCA model. On the premise of analyzing the objective and significance of informationization construction, system support for the refined management scheme from the aspects of system functional demand structure, process and perfecting suggestion are provided. Finally guarantee measures for delicacy management are put forward.
{"title":"Schematic Design of Postgraduate Cultivating Procedure Based on Delicacy Management","authors":"Danning Li","doi":"10.1109/ICEKIM52309.2021.00164","DOIUrl":"https://doi.org/10.1109/ICEKIM52309.2021.00164","url":null,"abstract":"Based on delicacy management theory and related principles, the management scheme of the whole process of postgraduate cultivating established on external PDCA cycle and key links of internal PDCA cycle are designed using PDCA model. On the premise of analyzing the objective and significance of informationization construction, system support for the refined management scheme from the aspects of system functional demand structure, process and perfecting suggestion are provided. Finally guarantee measures for delicacy management are put forward.","PeriodicalId":337654,"journal":{"name":"2021 2nd International Conference on Education, Knowledge and Information Management (ICEKIM)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116500592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.1109/ICEKIM52309.2021.00026
Yingjie Ren, Sirui Huang, Ya Zhou
MOOC attracts students with its unique teaching mode and high-quality curriculum resources, but it also faces the problem of high dropout rate, which affects the long development of MOOC. In order to solve the problem of high dropout rate faced by MOOC platform, this paper proposes the method of combining deep learning and integrated learning to construct the prediction model of students' withdrawal behavior. The experimental data were collected from MOOCCube2020 dataset. The convolution neural network is used to extract hidden features from the original data, and the output features are used as the input of ensemble learning model. Then, various traditional classification methods are used for training and prediction, and the prediction results of various models are fused to obtain the final result. Experiments show that the model can well fit the correlation between students' learning performance and class quitting behavior, so as to accurately predict whether students will quit the course, which is helpful to the in-depth study of MOOC learning mode.
{"title":"Deep learning and integrated learning for predicting student's withdrawal behavior in MOOC","authors":"Yingjie Ren, Sirui Huang, Ya Zhou","doi":"10.1109/ICEKIM52309.2021.00026","DOIUrl":"https://doi.org/10.1109/ICEKIM52309.2021.00026","url":null,"abstract":"MOOC attracts students with its unique teaching mode and high-quality curriculum resources, but it also faces the problem of high dropout rate, which affects the long development of MOOC. In order to solve the problem of high dropout rate faced by MOOC platform, this paper proposes the method of combining deep learning and integrated learning to construct the prediction model of students' withdrawal behavior. The experimental data were collected from MOOCCube2020 dataset. The convolution neural network is used to extract hidden features from the original data, and the output features are used as the input of ensemble learning model. Then, various traditional classification methods are used for training and prediction, and the prediction results of various models are fused to obtain the final result. Experiments show that the model can well fit the correlation between students' learning performance and class quitting behavior, so as to accurately predict whether students will quit the course, which is helpful to the in-depth study of MOOC learning mode.","PeriodicalId":337654,"journal":{"name":"2021 2nd International Conference on Education, Knowledge and Information Management (ICEKIM)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121649134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.1109/ICEKIM52309.2021.00171
Shen Sun
This paper describes a design of faculty management system based on cloud computing technology. A unique model is developed to enable performing radar chart analysis on evaluating faculty performance from the aspect of teaching, research, administration and university operation. These data are stored in a database at the cloud platform in where further analysis and tracing back can be performed to explore deeper potential of faculties. With such system, university leader board can make a proper strategic plan of faculty management in time to get acceleration on development. Meanwhile, individual faculties can be guided to be promoted following a professional pathway.
{"title":"A cloud-based system of faculty management with radar chart analysis applied","authors":"Shen Sun","doi":"10.1109/ICEKIM52309.2021.00171","DOIUrl":"https://doi.org/10.1109/ICEKIM52309.2021.00171","url":null,"abstract":"This paper describes a design of faculty management system based on cloud computing technology. A unique model is developed to enable performing radar chart analysis on evaluating faculty performance from the aspect of teaching, research, administration and university operation. These data are stored in a database at the cloud platform in where further analysis and tracing back can be performed to explore deeper potential of faculties. With such system, university leader board can make a proper strategic plan of faculty management in time to get acceleration on development. Meanwhile, individual faculties can be guided to be promoted following a professional pathway.","PeriodicalId":337654,"journal":{"name":"2021 2nd International Conference on Education, Knowledge and Information Management (ICEKIM)","volume":"64 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132371764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.1109/ICEKIM52309.2021.00106
Zhou Jie
With the development of modern information technology, online teaching is a new educational method. Teachers and students can use high-quality information resources, and break the limitations of time and space, to achieve personalized teaching.[1] During the current epidemic prevention and control period, online teaching can ensure “no suspension of classes, no suspension of teaching”, which is also a measure of not affecting students' papers, employment and other work, by making a good using of Internet big data. This paper first analyzes the current problems of online teaching in Colleges and universities, and then puts forward effective measures for the existing problems in order to maximize the effect of online teaching.
{"title":"Research into Online Teaching in Private Colleges Under the Background of Internet Big Data","authors":"Zhou Jie","doi":"10.1109/ICEKIM52309.2021.00106","DOIUrl":"https://doi.org/10.1109/ICEKIM52309.2021.00106","url":null,"abstract":"With the development of modern information technology, online teaching is a new educational method. Teachers and students can use high-quality information resources, and break the limitations of time and space, to achieve personalized teaching.[1] During the current epidemic prevention and control period, online teaching can ensure “no suspension of classes, no suspension of teaching”, which is also a measure of not affecting students' papers, employment and other work, by making a good using of Internet big data. This paper first analyzes the current problems of online teaching in Colleges and universities, and then puts forward effective measures for the existing problems in order to maximize the effect of online teaching.","PeriodicalId":337654,"journal":{"name":"2021 2nd International Conference on Education, Knowledge and Information Management (ICEKIM)","volume":"510 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130059103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：