{"title":"尝试对中小学互动白板课堂记录进行客观评价","authors":"Shen Li, Fang Dan","doi":"10.1109/ICCSE.2014.6926589","DOIUrl":null,"url":null,"abstract":"This paper tried to find a method to evaluate the interactive whiteboard classroom records in primary and secondary schools objectively. An evaluation model was constructed based on coding, clustering and comparison. A table of important teaching and learning behaviors was created for coding. The coding results showed that the features of the good classroom teaching are not the same. The fuzzy clustering algorithm was used to divide the good classroom teaching into several clusters, and the cluster-center was used to represent the cluster's feature. The correlation analysis was used to compare the unknown-level encode data with the cluster-center data. If they were similar, it can be inferred that the unknown-level classroom records were very likely good too. Otherwise, the unknowns very likely were not good. The simulation results showed that this method was effective. The model had an advantage on objective comparison to decide which one was worse.","PeriodicalId":275003,"journal":{"name":"2014 9th International Conference on Computer Science & Education","volume":"138 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Try to make an objective evaluation on interactive whiteboard classroom record in primary and secondary schools\",\"authors\":\"Shen Li, Fang Dan\",\"doi\":\"10.1109/ICCSE.2014.6926589\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper tried to find a method to evaluate the interactive whiteboard classroom records in primary and secondary schools objectively. An evaluation model was constructed based on coding, clustering and comparison. A table of important teaching and learning behaviors was created for coding. The coding results showed that the features of the good classroom teaching are not the same. The fuzzy clustering algorithm was used to divide the good classroom teaching into several clusters, and the cluster-center was used to represent the cluster's feature. The correlation analysis was used to compare the unknown-level encode data with the cluster-center data. If they were similar, it can be inferred that the unknown-level classroom records were very likely good too. Otherwise, the unknowns very likely were not good. The simulation results showed that this method was effective. The model had an advantage on objective comparison to decide which one was worse.\",\"PeriodicalId\":275003,\"journal\":{\"name\":\"2014 9th International Conference on Computer Science & Education\",\"volume\":\"138 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 9th International Conference on Computer Science & Education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSE.2014.6926589\",\"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 9th International Conference on Computer Science & Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSE.2014.6926589","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Try to make an objective evaluation on interactive whiteboard classroom record in primary and secondary schools
This paper tried to find a method to evaluate the interactive whiteboard classroom records in primary and secondary schools objectively. An evaluation model was constructed based on coding, clustering and comparison. A table of important teaching and learning behaviors was created for coding. The coding results showed that the features of the good classroom teaching are not the same. The fuzzy clustering algorithm was used to divide the good classroom teaching into several clusters, and the cluster-center was used to represent the cluster's feature. The correlation analysis was used to compare the unknown-level encode data with the cluster-center data. If they were similar, it can be inferred that the unknown-level classroom records were very likely good too. Otherwise, the unknowns very likely were not good. The simulation results showed that this method was effective. The model had an advantage on objective comparison to decide which one was worse.