A Review of Methods To Measure Affective Domain in Learning

Lusiana Syaiful, Marina Ismail, Z. A. Aziz
{"title":"A Review of Methods To Measure Affective Domain in Learning","authors":"Lusiana Syaiful, Marina Ismail, Z. A. Aziz","doi":"10.1109/ISCAIE.2019.8743903","DOIUrl":null,"url":null,"abstract":"Learning is part of education. The involvement of affective domain in education is very important for holistic learning. Affective domain is part of Bloom’s Taxonomy that consists of five major stages which are attending, receiving, valuing, organization and characterization. Every stage has its own action verb and its own meaning. The study of affective domain has been tackled for over a decade but not much focus on assessing it by level. Affective is very vague and uncertainties as it is more towards attitude, emotion and behavior. Affective is very hard to be predict, challenging and can change rapidly. This study compares several techniques that are possible for assessing affective domain. From the studies, the most used technique to measure affective is fuzzy logic. Fuzzy logic is the technique that able to measure uncertainties and vague values.","PeriodicalId":369098,"journal":{"name":"2019 IEEE 9th Symposium on Computer Applications & Industrial Electronics (ISCAIE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 9th Symposium on Computer Applications & Industrial Electronics (ISCAIE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCAIE.2019.8743903","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Learning is part of education. The involvement of affective domain in education is very important for holistic learning. Affective domain is part of Bloom’s Taxonomy that consists of five major stages which are attending, receiving, valuing, organization and characterization. Every stage has its own action verb and its own meaning. The study of affective domain has been tackled for over a decade but not much focus on assessing it by level. Affective is very vague and uncertainties as it is more towards attitude, emotion and behavior. Affective is very hard to be predict, challenging and can change rapidly. This study compares several techniques that are possible for assessing affective domain. From the studies, the most used technique to measure affective is fuzzy logic. Fuzzy logic is the technique that able to measure uncertainties and vague values.
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
学习情感域测量方法综述
学习是教育的一部分。情感域在教育中的介入对于整体学习是非常重要的。情感领域是Bloom分类法的一部分,该分类法由五个主要阶段组成,即参与、接受、重视、组织和表征。每个阶段都有自己的动作动词和含义。情感领域的研究已经进行了十多年,但对其层次评价的关注并不多。情感是非常模糊和不确定的,因为它更倾向于态度、情感和行为。情感是很难预测的,具有挑战性,可以迅速改变。本研究比较了几种可能用于评估情感领域的技术。从研究来看,最常用的情感度量方法是模糊逻辑。模糊逻辑是一种能够测量不确定性和模糊值的技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Developing the Maturity Model for Gig Economy Business Processes Dark Data Management as frontier of Information Governance Information Governance derivatives of Social Solidarity Economy Initiatives Exponentially Adaptive Sine-Cosine Algorithm for Global Optimization Wireless Hand Gesture Controlled Robotic Arm Via NRF24L01 Transceiver
×
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