{"title":"基于规则的自适应电子学习系统","authors":"O. Takács","doi":"10.1109/ICETA.2014.7107629","DOIUrl":null,"url":null,"abstract":"This article describes rule based system of adaptive e-learning. Elemental part of this system are rules that are thoroughly described together with different types of their categorization. There is also briefly described the engine that uses this rules, how are they applied, how can they interoperate and collaborate and how are avoided all conflicts in rules. This rule based engine was used in adaptive system Barborka 4 that was used in two successful pedagogical experiments in two Ph. D. thesis.","PeriodicalId":340996,"journal":{"name":"2014 IEEE 12th IEEE International Conference on Emerging eLearning Technologies and Applications (ICETA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Rule based system of adaptive e-learning\",\"authors\":\"O. Takács\",\"doi\":\"10.1109/ICETA.2014.7107629\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article describes rule based system of adaptive e-learning. Elemental part of this system are rules that are thoroughly described together with different types of their categorization. There is also briefly described the engine that uses this rules, how are they applied, how can they interoperate and collaborate and how are avoided all conflicts in rules. This rule based engine was used in adaptive system Barborka 4 that was used in two successful pedagogical experiments in two Ph. D. thesis.\",\"PeriodicalId\":340996,\"journal\":{\"name\":\"2014 IEEE 12th IEEE International Conference on Emerging eLearning Technologies and Applications (ICETA)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE 12th IEEE International Conference on Emerging eLearning Technologies and Applications (ICETA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICETA.2014.7107629\",\"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 12th IEEE International Conference on Emerging eLearning Technologies and Applications (ICETA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICETA.2014.7107629","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This article describes rule based system of adaptive e-learning. Elemental part of this system are rules that are thoroughly described together with different types of their categorization. There is also briefly described the engine that uses this rules, how are they applied, how can they interoperate and collaborate and how are avoided all conflicts in rules. This rule based engine was used in adaptive system Barborka 4 that was used in two successful pedagogical experiments in two Ph. D. thesis.
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