基于云模型的5E在线学习情感体验分析方法

Yumin Zheng, Chaowang Shang, Cheng Feng, Han Yue
{"title":"基于云模型的5E在线学习情感体验分析方法","authors":"Yumin Zheng, Chaowang Shang, Cheng Feng, Han Yue","doi":"10.1109/IEIR56323.2022.10050071","DOIUrl":null,"url":null,"abstract":"5E Online learning is the main form of integrated teaching, and the emotional experience of 5E online learning is an important embodiment of learners’ learning input. Based on the Ekman theoretical model, this paper designs and develops a cloud model of 5E online learning emotional experience with the six dimensions of “happy, relaxed, anxious, surprised, sad, and boredom which takes the area of the cloud as the main parameter. It determines the characteristic vectors and observation functions that characterize the learner’s emotional experience and evaluates the learner’s 5E online learning emotional experience. Otherwise, it promotes the learner’s 5E online learning ability and optimizes the evaluation of the online teaching process. Taking MOOCS as an example, this paper applies the cloud model to evaluate students’ emotions and verifies its effectiveness through specific data. This method enriches the methods of emotion calculation and characterization for online learners and provides a reference for the current multi-modal sentiment analysis research.","PeriodicalId":183709,"journal":{"name":"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Analysis Method of 5E Online Learning Emotional Experience based on Cloud Model\",\"authors\":\"Yumin Zheng, Chaowang Shang, Cheng Feng, Han Yue\",\"doi\":\"10.1109/IEIR56323.2022.10050071\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"5E Online learning is the main form of integrated teaching, and the emotional experience of 5E online learning is an important embodiment of learners’ learning input. Based on the Ekman theoretical model, this paper designs and develops a cloud model of 5E online learning emotional experience with the six dimensions of “happy, relaxed, anxious, surprised, sad, and boredom which takes the area of the cloud as the main parameter. It determines the characteristic vectors and observation functions that characterize the learner’s emotional experience and evaluates the learner’s 5E online learning emotional experience. Otherwise, it promotes the learner’s 5E online learning ability and optimizes the evaluation of the online teaching process. Taking MOOCS as an example, this paper applies the cloud model to evaluate students’ emotions and verifies its effectiveness through specific data. This method enriches the methods of emotion calculation and characterization for online learners and provides a reference for the current multi-modal sentiment analysis research.\",\"PeriodicalId\":183709,\"journal\":{\"name\":\"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEIR56323.2022.10050071\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEIR56323.2022.10050071","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

5E在线学习是整合教学的主要形式,5E在线学习的情感体验是学习者学习投入的重要体现。本文以Ekman理论模型为基础,以云的面积为主要参数,设计并开发了以“快乐、放松、焦虑、惊讶、悲伤、无聊”六个维度的5E在线学习情感体验云模型。确定表征学习者情感体验的特征向量和观察函数,对学习者的5E在线学习情感体验进行评价。提高学习者的5E在线学习能力,优化在线教学过程的评价。本文以mooc为例,运用云模型对学生情绪进行评价,并通过具体数据验证其有效性。该方法丰富了在线学习者的情感计算和表征方法,为当前的多模态情感分析研究提供了参考。
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
An Analysis Method of 5E Online Learning Emotional Experience based on Cloud Model
5E Online learning is the main form of integrated teaching, and the emotional experience of 5E online learning is an important embodiment of learners’ learning input. Based on the Ekman theoretical model, this paper designs and develops a cloud model of 5E online learning emotional experience with the six dimensions of “happy, relaxed, anxious, surprised, sad, and boredom which takes the area of the cloud as the main parameter. It determines the characteristic vectors and observation functions that characterize the learner’s emotional experience and evaluates the learner’s 5E online learning emotional experience. Otherwise, it promotes the learner’s 5E online learning ability and optimizes the evaluation of the online teaching process. Taking MOOCS as an example, this paper applies the cloud model to evaluate students’ emotions and verifies its effectiveness through specific data. This method enriches the methods of emotion calculation and characterization for online learners and provides a reference for the current multi-modal sentiment analysis research.
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
Is the Research on AI Empowered Pedagogy in China Decaying? Explore the interrelationship of cognition, emotion and interaction when learners engage in online discussion Solving Word Function Problems in Line with Educational Cognition Way Comparative Analysis of Problem Representation Learning in Math Word Problem Solving Prompt-Based Missing Entity Recovery for Solving Arithmetic Word Problems
×
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