Cunling Bian, Shijun Dong, Chunrong Li, Zheng Shi, Weigang Lu
{"title":"基于概念图和免疫算法的自适应学习路径生成","authors":"Cunling Bian, Shijun Dong, Chunrong Li, Zheng Shi, Weigang Lu","doi":"10.1109/ICCSE.2017.8085526","DOIUrl":null,"url":null,"abstract":"In recent years, the research of adaptive learning path has drawn a lot of attentions, which organizes the learning resources in accordance with the learner's attributes. As a result, it is quite necessary to find an efficient implementation approach for generating the adaptive learning path. In this paper, we first create a learner-centered concept map by graph theory. Then learning object (LO) is applied as an organization model for learning resource and we apply the immune algorithm (IA) into its selection to generate the optimal learning path. The simulation results show that the proposed approach is effective for adaptive learning path generation.","PeriodicalId":256055,"journal":{"name":"2017 12th International Conference on Computer Science and Education (ICCSE)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Generation of adaptive learning path based on concept map and immune algorithm\",\"authors\":\"Cunling Bian, Shijun Dong, Chunrong Li, Zheng Shi, Weigang Lu\",\"doi\":\"10.1109/ICCSE.2017.8085526\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, the research of adaptive learning path has drawn a lot of attentions, which organizes the learning resources in accordance with the learner's attributes. As a result, it is quite necessary to find an efficient implementation approach for generating the adaptive learning path. In this paper, we first create a learner-centered concept map by graph theory. Then learning object (LO) is applied as an organization model for learning resource and we apply the immune algorithm (IA) into its selection to generate the optimal learning path. The simulation results show that the proposed approach is effective for adaptive learning path generation.\",\"PeriodicalId\":256055,\"journal\":{\"name\":\"2017 12th International Conference on Computer Science and Education (ICCSE)\",\"volume\":\"93 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 12th International Conference on Computer Science and Education (ICCSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSE.2017.8085526\",\"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 12th International Conference on Computer Science and Education (ICCSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSE.2017.8085526","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Generation of adaptive learning path based on concept map and immune algorithm
In recent years, the research of adaptive learning path has drawn a lot of attentions, which organizes the learning resources in accordance with the learner's attributes. As a result, it is quite necessary to find an efficient implementation approach for generating the adaptive learning path. In this paper, we first create a learner-centered concept map by graph theory. Then learning object (LO) is applied as an organization model for learning resource and we apply the immune algorithm (IA) into its selection to generate the optimal learning path. The simulation results show that the proposed approach is effective for adaptive learning path generation.