在MOOC论坛中识别与内容相关的线索

Yi Cui, A. Wise
{"title":"在MOOC论坛中识别与内容相关的线索","authors":"Yi Cui, A. Wise","doi":"10.1145/2724660.2728679","DOIUrl":null,"url":null,"abstract":"This study investigated the extent to which students asked and instructors answered content-related questions in MOOC discussion forums; subsequently a classification model was built to identify such questions based on extracted linguistic features. Results showed content-related threads were a minority and under-addressed by instructors. However, linguistic modeling was promising in identifying them with high reliability.","PeriodicalId":20664,"journal":{"name":"Proceedings of the Second (2015) ACM Conference on Learning @ Scale","volume":"270 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2015-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"44","resultStr":"{\"title\":\"Identifying Content-Related Threads in MOOC Discussion Forums\",\"authors\":\"Yi Cui, A. Wise\",\"doi\":\"10.1145/2724660.2728679\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study investigated the extent to which students asked and instructors answered content-related questions in MOOC discussion forums; subsequently a classification model was built to identify such questions based on extracted linguistic features. Results showed content-related threads were a minority and under-addressed by instructors. However, linguistic modeling was promising in identifying them with high reliability.\",\"PeriodicalId\":20664,\"journal\":{\"name\":\"Proceedings of the Second (2015) ACM Conference on Learning @ Scale\",\"volume\":\"270 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-03-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"44\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Second (2015) ACM Conference on Learning @ Scale\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2724660.2728679\",\"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 Second (2015) ACM Conference on Learning @ Scale","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2724660.2728679","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 44

摘要

本研究调查了MOOC论坛中学生提问和教师回答内容相关问题的程度;随后,基于提取的语言特征,建立分类模型来识别这些问题。结果显示,与内容相关的线程是少数,并且没有得到教师的重视。然而,语言建模在识别它们方面有很高的可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Identifying Content-Related Threads in MOOC Discussion Forums
This study investigated the extent to which students asked and instructors answered content-related questions in MOOC discussion forums; subsequently a classification model was built to identify such questions based on extracted linguistic features. Results showed content-related threads were a minority and under-addressed by instructors. However, linguistic modeling was promising in identifying them with high reliability.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Learning is Not a Spectator Sport: Doing is Better than Watching for Learning from a MOOC Learnersourcing of Complex Assessments All It Takes Is One: Evidence for a Strategy for Seeding Large Scale Peer Learning Interactions Designing MOOCs as Interactive Places for Collaborative Learning Who You Are or What You Do: Comparing the Predictive Power of Demographics vs. Activity Patterns in Massive Open Online Courses (MOOCs)
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1