{"title":"从用户流量分析电子学习平台特征","authors":"M. M. Cristian, B. D. Dan","doi":"10.1109/SOFTCOM.2006.329780","DOIUrl":null,"url":null,"abstract":"An e-Learning platform has been designed and implemented. The platform has built in capabilities of monitoring and recording user's actions. For a user, all executed actions on the platform represent his activity. The activity of all users makes up platform's activity. Based on platform's activity data, we introduce an attribute for our e-Learning platform called Quality of Service (QoS). Two parameters define the QoS: learning proficiency of students and classification capability of the platform. Machine learning and modeling techniques evaluate the parameters for our platform or any other e-Learning system.","PeriodicalId":292242,"journal":{"name":"2006 International Conference on Software in Telecommunications and Computer Networks","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"E-Learning Platform Characterization from User Trafic\",\"authors\":\"M. M. Cristian, B. D. Dan\",\"doi\":\"10.1109/SOFTCOM.2006.329780\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An e-Learning platform has been designed and implemented. The platform has built in capabilities of monitoring and recording user's actions. For a user, all executed actions on the platform represent his activity. The activity of all users makes up platform's activity. Based on platform's activity data, we introduce an attribute for our e-Learning platform called Quality of Service (QoS). Two parameters define the QoS: learning proficiency of students and classification capability of the platform. Machine learning and modeling techniques evaluate the parameters for our platform or any other e-Learning system.\",\"PeriodicalId\":292242,\"journal\":{\"name\":\"2006 International Conference on Software in Telecommunications and Computer Networks\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-09-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 International Conference on Software in Telecommunications and Computer Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SOFTCOM.2006.329780\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 International Conference on Software in Telecommunications and Computer Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SOFTCOM.2006.329780","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
E-Learning Platform Characterization from User Trafic
An e-Learning platform has been designed and implemented. The platform has built in capabilities of monitoring and recording user's actions. For a user, all executed actions on the platform represent his activity. The activity of all users makes up platform's activity. Based on platform's activity data, we introduce an attribute for our e-Learning platform called Quality of Service (QoS). Two parameters define the QoS: learning proficiency of students and classification capability of the platform. Machine learning and modeling techniques evaluate the parameters for our platform or any other e-Learning system.