I. Perikos, P. Angelopoulos, M. Paraskevas, T. Zarouchas, Giannis Tzimas
{"title":"持续学习过程的评价与知识提取方法","authors":"I. Perikos, P. Angelopoulos, M. Paraskevas, T. Zarouchas, Giannis Tzimas","doi":"10.1109/CSE.2014.106","DOIUrl":null,"url":null,"abstract":"This study presents the utilization of a Hybrid Education Platform for the realization of a versatile blended learning model oriented to computer engineering and science educators. Furthermore, a data mining approach is introduced to analyze the questionnaires that learners submit concerning the learning activities they have participated in. Specifically, a clustering and classification methodology framework is followed in order to efficiently examine and extract behavioral trends of the participants. Preliminary results indicate the robustness of the proposed methodology scheme which can potential be applied to various evaluation tasks.","PeriodicalId":258990,"journal":{"name":"2014 IEEE 17th International Conference on Computational Science and Engineering","volume":"33 5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Methodology for Evaluation and Knowledge Extraction from On-going Learning Process\",\"authors\":\"I. Perikos, P. Angelopoulos, M. Paraskevas, T. Zarouchas, Giannis Tzimas\",\"doi\":\"10.1109/CSE.2014.106\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study presents the utilization of a Hybrid Education Platform for the realization of a versatile blended learning model oriented to computer engineering and science educators. Furthermore, a data mining approach is introduced to analyze the questionnaires that learners submit concerning the learning activities they have participated in. Specifically, a clustering and classification methodology framework is followed in order to efficiently examine and extract behavioral trends of the participants. Preliminary results indicate the robustness of the proposed methodology scheme which can potential be applied to various evaluation tasks.\",\"PeriodicalId\":258990,\"journal\":{\"name\":\"2014 IEEE 17th International Conference on Computational Science and Engineering\",\"volume\":\"33 5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE 17th International Conference on Computational Science and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSE.2014.106\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 17th International Conference on Computational Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSE.2014.106","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Methodology for Evaluation and Knowledge Extraction from On-going Learning Process
This study presents the utilization of a Hybrid Education Platform for the realization of a versatile blended learning model oriented to computer engineering and science educators. Furthermore, a data mining approach is introduced to analyze the questionnaires that learners submit concerning the learning activities they have participated in. Specifically, a clustering and classification methodology framework is followed in order to efficiently examine and extract behavioral trends of the participants. Preliminary results indicate the robustness of the proposed methodology scheme which can potential be applied to various evaluation tasks.