{"title":"细粒度跨机构学习数据的挑战与潜力","authors":"A. Dix","doi":"10.1145/2876034.2893429","DOIUrl":null,"url":null,"abstract":"While MOOCs and other forms of large-scale learning are of growing importance, the vast majority of tertiary students still study in traditional face-to-face settings. This paper examines some of the challenges in attempting to apply the benefits of large-scale learning to these settings, building on a growing repository of cross-institutional data.","PeriodicalId":20739,"journal":{"name":"Proceedings of the Third (2016) ACM Conference on Learning @ Scale","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Challenge and Potential of Fine Grain, Cross-Institutional Learning Data\",\"authors\":\"A. Dix\",\"doi\":\"10.1145/2876034.2893429\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"While MOOCs and other forms of large-scale learning are of growing importance, the vast majority of tertiary students still study in traditional face-to-face settings. This paper examines some of the challenges in attempting to apply the benefits of large-scale learning to these settings, building on a growing repository of cross-institutional data.\",\"PeriodicalId\":20739,\"journal\":{\"name\":\"Proceedings of the Third (2016) ACM Conference on Learning @ Scale\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-04-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Third (2016) ACM Conference on Learning @ Scale\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2876034.2893429\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Third (2016) ACM Conference on Learning @ Scale","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2876034.2893429","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Challenge and Potential of Fine Grain, Cross-Institutional Learning Data
While MOOCs and other forms of large-scale learning are of growing importance, the vast majority of tertiary students still study in traditional face-to-face settings. This paper examines some of the challenges in attempting to apply the benefits of large-scale learning to these settings, building on a growing repository of cross-institutional data.
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