Detecting emotion model in e-learning system
Affective computing is computing that relates to human affects things. In this research, it proposed a teaching model with affective computing. It uses a novel method to detect learner's emotion and adjust emotion when learner's emotion without in positive emotion status. The detecting emo...
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creator | Guey-Shya Chen Min-Feng Lee |
description | Affective computing is computing that relates to human affects things. In this research, it proposed a teaching model with affective computing. It uses a novel method to detect learner's emotion and adjust emotion when learner's emotion without in positive emotion status. The detecting emotion teaching model uses emotion management module that include the detecting emotion and emotion map functions to detect learner's emotion and record emotion status for learning. This research uses emotion map to record the emotion locus for learning activity. In this detecting emotion teaching model integrates learning activities and emotion locus to create a complete learning portfolio. And it can be applied in analyzing learning status for adjusting learner's situation. By this research detecting emotion teaching model it makes a method that was based on learner's emotion to build a more effective learning environment. The detect emotion teaching model, which is a kind of innovative learning model can be applied in game based learning for continuously developing in the future and it can be used in a variety of teaching environment for increasing study effect. |
doi_str_mv | 10.1109/ICMLC.2012.6359628 |
format | Conference Proceeding |
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In this research, it proposed a teaching model with affective computing. It uses a novel method to detect learner's emotion and adjust emotion when learner's emotion without in positive emotion status. The detecting emotion teaching model uses emotion management module that include the detecting emotion and emotion map functions to detect learner's emotion and record emotion status for learning. This research uses emotion map to record the emotion locus for learning activity. In this detecting emotion teaching model integrates learning activities and emotion locus to create a complete learning portfolio. And it can be applied in analyzing learning status for adjusting learner's situation. By this research detecting emotion teaching model it makes a method that was based on learner's emotion to build a more effective learning environment. 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In this research, it proposed a teaching model with affective computing. It uses a novel method to detect learner's emotion and adjust emotion when learner's emotion without in positive emotion status. The detecting emotion teaching model uses emotion management module that include the detecting emotion and emotion map functions to detect learner's emotion and record emotion status for learning. This research uses emotion map to record the emotion locus for learning activity. In this detecting emotion teaching model integrates learning activities and emotion locus to create a complete learning portfolio. And it can be applied in analyzing learning status for adjusting learner's situation. By this research detecting emotion teaching model it makes a method that was based on learner's emotion to build a more effective learning environment. The detect emotion teaching model, which is a kind of innovative learning model can be applied in game based learning for continuously developing in the future and it can be used in a variety of teaching environment for increasing study effect.</description><subject>Abstracts</subject><subject>Affective computing</subject><subject>Detecting Emotion</subject><subject>E-learning</subject><subject>Electronic learning</subject><subject>Emotion map</subject><subject>Radio frequency</subject><subject>Videos</subject><issn>2160-133X</issn><isbn>1467314846</isbn><isbn>9781467314848</isbn><isbn>9781467314879</isbn><isbn>1467314870</isbn><isbn>9781467314862</isbn><isbn>1467314862</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1j81KxDAUhSMqOI59Ad30AUzNTW7zs5Q66kDFzSzcDW1zK5H-SJPNvL0jjmfzcfjgwGHsFkQBINzDtnqrq0IKkIVWpdPSnrHMGQuojQK0xp2z6_-C-oKtJGjBQamPK5bF-CWOMYjWwYrdP1GiLoXpM6dxTmGe8nH2NORhyokP1CzTr4uHmGi8YZd9M0TKTlyz3fNmV73y-v1lWz3WPDiRuO9QtV1ppLKGOtK97b23Rmj02JQ9gi6Ncxrd0aIQLZm2lQp8azQCkFJrdvc3G4ho_72EsVkO-9NX9QNF3UTY</recordid><startdate>201207</startdate><enddate>201207</enddate><creator>Guey-Shya Chen</creator><creator>Min-Feng Lee</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201207</creationdate><title>Detecting emotion model in e-learning system</title><author>Guey-Shya Chen ; Min-Feng Lee</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-dc43bc572387ece6f8fdd87064d4a5f41657996497ec400be7bb231db76411e33</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Abstracts</topic><topic>Affective computing</topic><topic>Detecting Emotion</topic><topic>E-learning</topic><topic>Electronic learning</topic><topic>Emotion map</topic><topic>Radio frequency</topic><topic>Videos</topic><toplevel>online_resources</toplevel><creatorcontrib>Guey-Shya Chen</creatorcontrib><creatorcontrib>Min-Feng Lee</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Guey-Shya Chen</au><au>Min-Feng Lee</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Detecting emotion model in e-learning system</atitle><btitle>2012 International Conference on Machine Learning and Cybernetics</btitle><stitle>ICMLC</stitle><date>2012-07</date><risdate>2012</risdate><volume>5</volume><spage>1686</spage><epage>1691</epage><pages>1686-1691</pages><issn>2160-133X</issn><isbn>1467314846</isbn><isbn>9781467314848</isbn><eisbn>9781467314879</eisbn><eisbn>1467314870</eisbn><eisbn>9781467314862</eisbn><eisbn>1467314862</eisbn><abstract>Affective computing is computing that relates to human affects things. In this research, it proposed a teaching model with affective computing. It uses a novel method to detect learner's emotion and adjust emotion when learner's emotion without in positive emotion status. The detecting emotion teaching model uses emotion management module that include the detecting emotion and emotion map functions to detect learner's emotion and record emotion status for learning. This research uses emotion map to record the emotion locus for learning activity. In this detecting emotion teaching model integrates learning activities and emotion locus to create a complete learning portfolio. And it can be applied in analyzing learning status for adjusting learner's situation. By this research detecting emotion teaching model it makes a method that was based on learner's emotion to build a more effective learning environment. 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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Abstracts Affective computing Detecting Emotion E-learning Electronic learning Emotion map Radio frequency Videos |
title | Detecting emotion model in e-learning system |
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