{"title":"夏尔巴:通过推荐引擎提高学生的成功率","authors":"Robert Bramucci, J. Gaston","doi":"10.1145/2330601.2330625","DOIUrl":null,"url":null,"abstract":"Students flock to online services like Amazon, Pandora and Netflix that offer personalized recommendations, in stark contrast to the \"one size fits all\" services in higher education. In this session we demonstrate Sherpa, a recommendation engine for courses, information and services that utilizes both human and machine intelligence.","PeriodicalId":311750,"journal":{"name":"Proceedings of the 2nd International Conference on Learning Analytics and Knowledge","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":"{\"title\":\"Sherpa: increasing student success with a recommendation engine\",\"authors\":\"Robert Bramucci, J. Gaston\",\"doi\":\"10.1145/2330601.2330625\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Students flock to online services like Amazon, Pandora and Netflix that offer personalized recommendations, in stark contrast to the \\\"one size fits all\\\" services in higher education. In this session we demonstrate Sherpa, a recommendation engine for courses, information and services that utilizes both human and machine intelligence.\",\"PeriodicalId\":311750,\"journal\":{\"name\":\"Proceedings of the 2nd International Conference on Learning Analytics and Knowledge\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-04-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"22\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2nd International Conference on Learning Analytics and Knowledge\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2330601.2330625\",\"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 2nd International Conference on Learning Analytics and Knowledge","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2330601.2330625","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sherpa: increasing student success with a recommendation engine
Students flock to online services like Amazon, Pandora and Netflix that offer personalized recommendations, in stark contrast to the "one size fits all" services in higher education. In this session we demonstrate Sherpa, a recommendation engine for courses, information and services that utilizes both human and machine intelligence.