Elena Baralis, Luca Cagliero, L. Farinetti, M. Mezzalama, Enrico Venuto
{"title":"混合学习环境下大规模教育服务的实验验证","authors":"Elena Baralis, Luca Cagliero, L. Farinetti, M. Mezzalama, Enrico Venuto","doi":"10.1109/COMPSAC.2017.123","DOIUrl":null,"url":null,"abstract":"New information and communication technologies offer today many opportunities to improve the quality of educational services in universities and in particular they allow to design and implement innovative learning models. This paper describes and validates our university blended learning model, and specifically the massive educational video service that we offer to our students since 2010. In these years, we have gathered a huge amount of detailed data about the students' access to the service, and the paper describes a number of analyses that we carried out with these data. The common goal was to find out experimentally whether the main objectives of the educational video service we had in our mind when we designed it, namely appreciation, effectiveness and flexibility, were reflected by the users' behavior. We analyzed how many students used the service, for how many courses, and how many videos they accessed within a course (appreciation of the service). We analyzed the correlation between the use of the service and the performance of the students in terms of successful examination rate and average mark (effectiveness of the service). Finally, by using data mining techniques we profiled users according to their behavior while accessing the educational video service. We found out six different patterns that reflect different uses of the services matching different learning goals (flexibility of the service). The results of these analyses show the quality of the proposed blended learning model and the coherency of its implementation with respect to the design goals.","PeriodicalId":6556,"journal":{"name":"2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC)","volume":"16 1","pages":"381-390"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Experimental Validation of a Massive Educational Service in a Blended Learning Environment\",\"authors\":\"Elena Baralis, Luca Cagliero, L. Farinetti, M. Mezzalama, Enrico Venuto\",\"doi\":\"10.1109/COMPSAC.2017.123\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"New information and communication technologies offer today many opportunities to improve the quality of educational services in universities and in particular they allow to design and implement innovative learning models. This paper describes and validates our university blended learning model, and specifically the massive educational video service that we offer to our students since 2010. In these years, we have gathered a huge amount of detailed data about the students' access to the service, and the paper describes a number of analyses that we carried out with these data. The common goal was to find out experimentally whether the main objectives of the educational video service we had in our mind when we designed it, namely appreciation, effectiveness and flexibility, were reflected by the users' behavior. We analyzed how many students used the service, for how many courses, and how many videos they accessed within a course (appreciation of the service). We analyzed the correlation between the use of the service and the performance of the students in terms of successful examination rate and average mark (effectiveness of the service). Finally, by using data mining techniques we profiled users according to their behavior while accessing the educational video service. We found out six different patterns that reflect different uses of the services matching different learning goals (flexibility of the service). The results of these analyses show the quality of the proposed blended learning model and the coherency of its implementation with respect to the design goals.\",\"PeriodicalId\":6556,\"journal\":{\"name\":\"2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC)\",\"volume\":\"16 1\",\"pages\":\"381-390\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COMPSAC.2017.123\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMPSAC.2017.123","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Experimental Validation of a Massive Educational Service in a Blended Learning Environment
New information and communication technologies offer today many opportunities to improve the quality of educational services in universities and in particular they allow to design and implement innovative learning models. This paper describes and validates our university blended learning model, and specifically the massive educational video service that we offer to our students since 2010. In these years, we have gathered a huge amount of detailed data about the students' access to the service, and the paper describes a number of analyses that we carried out with these data. The common goal was to find out experimentally whether the main objectives of the educational video service we had in our mind when we designed it, namely appreciation, effectiveness and flexibility, were reflected by the users' behavior. We analyzed how many students used the service, for how many courses, and how many videos they accessed within a course (appreciation of the service). We analyzed the correlation between the use of the service and the performance of the students in terms of successful examination rate and average mark (effectiveness of the service). Finally, by using data mining techniques we profiled users according to their behavior while accessing the educational video service. We found out six different patterns that reflect different uses of the services matching different learning goals (flexibility of the service). The results of these analyses show the quality of the proposed blended learning model and the coherency of its implementation with respect to the design goals.