{"title":"使用学习方式进行内容交付个性化","authors":"Manish Joshi","doi":"10.1109/ICSCAN49426.2020.9262434","DOIUrl":null,"url":null,"abstract":"Personalization in e-services is desirable and large numbers of professional players are ensuring that personalization must be included as a web service for users. Moreover, recommender systems can perform effectively only with the support of personalization. Personalization has gained momentum in the service sector including education. With the advancement of the concept of ‘Teaching with Technology’, industry is inching forward to provide personalized learning contents on e-learning platforms. Personalization can be offered to a learner by ana-lyzing learning behavior, cognitive skills, learning style etc. of a learner. Most of the researchers have attained personalization especially in distance mode of e-learning using Adaptive Educational Hypermedia Systems (AEHS). Different aspects of personalization that demonstrate a paradigm shift from synchronous to adaptive approach of e-learning are being explored and experimented by many researchers. In this paper, we present our experiments of delivering learning objects (LOs) to learners that suits to the learners learning style. A personalized instruction delivery mechanism is developed that matches Learning style of a LO and the learning style of a learner. We demonstrate how such matching is ensured. We present the design of the Intelligent Tutoring System that we have developed and further discussed the learning style driven content delivery personalization.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"208 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Use of Learning Style for Content Delivery Personalization\",\"authors\":\"Manish Joshi\",\"doi\":\"10.1109/ICSCAN49426.2020.9262434\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Personalization in e-services is desirable and large numbers of professional players are ensuring that personalization must be included as a web service for users. Moreover, recommender systems can perform effectively only with the support of personalization. Personalization has gained momentum in the service sector including education. With the advancement of the concept of ‘Teaching with Technology’, industry is inching forward to provide personalized learning contents on e-learning platforms. Personalization can be offered to a learner by ana-lyzing learning behavior, cognitive skills, learning style etc. of a learner. Most of the researchers have attained personalization especially in distance mode of e-learning using Adaptive Educational Hypermedia Systems (AEHS). Different aspects of personalization that demonstrate a paradigm shift from synchronous to adaptive approach of e-learning are being explored and experimented by many researchers. In this paper, we present our experiments of delivering learning objects (LOs) to learners that suits to the learners learning style. A personalized instruction delivery mechanism is developed that matches Learning style of a LO and the learning style of a learner. We demonstrate how such matching is ensured. We present the design of the Intelligent Tutoring System that we have developed and further discussed the learning style driven content delivery personalization.\",\"PeriodicalId\":6744,\"journal\":{\"name\":\"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)\",\"volume\":\"208 1\",\"pages\":\"1-5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSCAN49426.2020.9262434\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSCAN49426.2020.9262434","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Use of Learning Style for Content Delivery Personalization
Personalization in e-services is desirable and large numbers of professional players are ensuring that personalization must be included as a web service for users. Moreover, recommender systems can perform effectively only with the support of personalization. Personalization has gained momentum in the service sector including education. With the advancement of the concept of ‘Teaching with Technology’, industry is inching forward to provide personalized learning contents on e-learning platforms. Personalization can be offered to a learner by ana-lyzing learning behavior, cognitive skills, learning style etc. of a learner. Most of the researchers have attained personalization especially in distance mode of e-learning using Adaptive Educational Hypermedia Systems (AEHS). Different aspects of personalization that demonstrate a paradigm shift from synchronous to adaptive approach of e-learning are being explored and experimented by many researchers. In this paper, we present our experiments of delivering learning objects (LOs) to learners that suits to the learners learning style. A personalized instruction delivery mechanism is developed that matches Learning style of a LO and the learning style of a learner. We demonstrate how such matching is ensured. We present the design of the Intelligent Tutoring System that we have developed and further discussed the learning style driven content delivery personalization.