{"title":"提出了一项评估任务,以识别在线课程中的困难学生","authors":"A. Staikopoulos, Owen Conlan","doi":"10.1145/3099023.3099049","DOIUrl":null,"url":null,"abstract":"This paper describes and proposes a community evaluation task that is designed for evaluating learning systems that can automatically identify different types of problems, that students may encounter with their online courses. As a basis, the learning systems would use logs from an artificial learning environment to analyse the student interactions and behaviour with the online course. The learning systems will also use specific domain models to ensure that the course requirements such as task deadlines and learning content conditions (e.g., pre-requisites) are addressed. As a result, the outputs (identified student problems) can be used by a) the learning systems to provide personalised feedback and direction to students to overcome a problem b) notify an instructor for a more professional support and response c) inform a learning designer for potential problems on the design of the course.","PeriodicalId":219391,"journal":{"name":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Proposing an Evaluation Task for Identifying Struggling Students in Online Courses\",\"authors\":\"A. Staikopoulos, Owen Conlan\",\"doi\":\"10.1145/3099023.3099049\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes and proposes a community evaluation task that is designed for evaluating learning systems that can automatically identify different types of problems, that students may encounter with their online courses. As a basis, the learning systems would use logs from an artificial learning environment to analyse the student interactions and behaviour with the online course. The learning systems will also use specific domain models to ensure that the course requirements such as task deadlines and learning content conditions (e.g., pre-requisites) are addressed. As a result, the outputs (identified student problems) can be used by a) the learning systems to provide personalised feedback and direction to students to overcome a problem b) notify an instructor for a more professional support and response c) inform a learning designer for potential problems on the design of the course.\",\"PeriodicalId\":219391,\"journal\":{\"name\":\"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3099023.3099049\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3099023.3099049","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Proposing an Evaluation Task for Identifying Struggling Students in Online Courses
This paper describes and proposes a community evaluation task that is designed for evaluating learning systems that can automatically identify different types of problems, that students may encounter with their online courses. As a basis, the learning systems would use logs from an artificial learning environment to analyse the student interactions and behaviour with the online course. The learning systems will also use specific domain models to ensure that the course requirements such as task deadlines and learning content conditions (e.g., pre-requisites) are addressed. As a result, the outputs (identified student problems) can be used by a) the learning systems to provide personalised feedback and direction to students to overcome a problem b) notify an instructor for a more professional support and response c) inform a learning designer for potential problems on the design of the course.