{"title":"教育数据挖掘和学习分析","authors":"Akansha Mishra, Rashi Bansal, Shailendra Narayan Singh","doi":"10.1109/CONFLUENCE.2017.7943201","DOIUrl":null,"url":null,"abstract":"These days' data mining is an emerging trend, which is presently used in different areas especially in student educational and learning analytics. It is very hard and time consuming to analyze data and finding the hidden information manually. To improvise educational data mining, clustering will be used in the paper. As we need to improvise performance as well as unambiguousness of obtained models. We have used 84 under-graduate student data and grouped students according to their final marks they achieved in the course and this we have done by using clustering approach. The result which we get shows that the clarity of specific model is much better than the general model and the unambiguousness of the model is also increase.","PeriodicalId":6651,"journal":{"name":"2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence","volume":"52 1","pages":"491-494"},"PeriodicalIF":0.0000,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Educational data mining and learning analysis\",\"authors\":\"Akansha Mishra, Rashi Bansal, Shailendra Narayan Singh\",\"doi\":\"10.1109/CONFLUENCE.2017.7943201\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"These days' data mining is an emerging trend, which is presently used in different areas especially in student educational and learning analytics. It is very hard and time consuming to analyze data and finding the hidden information manually. To improvise educational data mining, clustering will be used in the paper. As we need to improvise performance as well as unambiguousness of obtained models. We have used 84 under-graduate student data and grouped students according to their final marks they achieved in the course and this we have done by using clustering approach. The result which we get shows that the clarity of specific model is much better than the general model and the unambiguousness of the model is also increase.\",\"PeriodicalId\":6651,\"journal\":{\"name\":\"2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence\",\"volume\":\"52 1\",\"pages\":\"491-494\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CONFLUENCE.2017.7943201\",\"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 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CONFLUENCE.2017.7943201","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
These days' data mining is an emerging trend, which is presently used in different areas especially in student educational and learning analytics. It is very hard and time consuming to analyze data and finding the hidden information manually. To improvise educational data mining, clustering will be used in the paper. As we need to improvise performance as well as unambiguousness of obtained models. We have used 84 under-graduate student data and grouped students according to their final marks they achieved in the course and this we have done by using clustering approach. The result which we get shows that the clarity of specific model is much better than the general model and the unambiguousness of the model is also increase.