{"title":"建立适应学习的参考语境模型","authors":"Ouissem Benmesbah, Mahnane Lamia, Mohamed Hafidi, Ishaq Zouaghi","doi":"10.23919/WMNC.2019.8881825","DOIUrl":null,"url":null,"abstract":"Adaptive and context-aware learning provides learning content according to a learner’s context. In order to achieve this goal, the dimensions that constitute the context in the current learner’s state have to be determined. There are several existing works within this field and each of these are taking care of a subset of context parameters - like learning styles, learner location, etc. But, a standardized model that helps to capture a learner’s context in its entirety is not available. The requirement to define context more precisely and in a uniform way has been identified by several researchers because a general and precise definition of context can facilitate the identification of what does and does not constitute context and can enable reuse and share of contextual data over applications. To this end, this work proposes a reference context model that helps to define a learner’s context. The proposed model is developed by consolidating the various context parameters used in the existing adaptive systems and organizing them into an appropriate structure.","PeriodicalId":197152,"journal":{"name":"2019 12th IFIP Wireless and Mobile Networking Conference (WMNC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Towards a reference context model for adaptive learning\",\"authors\":\"Ouissem Benmesbah, Mahnane Lamia, Mohamed Hafidi, Ishaq Zouaghi\",\"doi\":\"10.23919/WMNC.2019.8881825\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Adaptive and context-aware learning provides learning content according to a learner’s context. In order to achieve this goal, the dimensions that constitute the context in the current learner’s state have to be determined. There are several existing works within this field and each of these are taking care of a subset of context parameters - like learning styles, learner location, etc. But, a standardized model that helps to capture a learner’s context in its entirety is not available. The requirement to define context more precisely and in a uniform way has been identified by several researchers because a general and precise definition of context can facilitate the identification of what does and does not constitute context and can enable reuse and share of contextual data over applications. To this end, this work proposes a reference context model that helps to define a learner’s context. The proposed model is developed by consolidating the various context parameters used in the existing adaptive systems and organizing them into an appropriate structure.\",\"PeriodicalId\":197152,\"journal\":{\"name\":\"2019 12th IFIP Wireless and Mobile Networking Conference (WMNC)\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 12th IFIP Wireless and Mobile Networking Conference (WMNC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/WMNC.2019.8881825\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 12th IFIP Wireless and Mobile Networking Conference (WMNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/WMNC.2019.8881825","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards a reference context model for adaptive learning
Adaptive and context-aware learning provides learning content according to a learner’s context. In order to achieve this goal, the dimensions that constitute the context in the current learner’s state have to be determined. There are several existing works within this field and each of these are taking care of a subset of context parameters - like learning styles, learner location, etc. But, a standardized model that helps to capture a learner’s context in its entirety is not available. The requirement to define context more precisely and in a uniform way has been identified by several researchers because a general and precise definition of context can facilitate the identification of what does and does not constitute context and can enable reuse and share of contextual data over applications. To this end, this work proposes a reference context model that helps to define a learner’s context. The proposed model is developed by consolidating the various context parameters used in the existing adaptive systems and organizing them into an appropriate structure.