Distinguishing Anxiety Subtypes of English Language Learners Towards Augmented Emotional Clarity
Distinguishing Anxiety Subtypes of English Language Learners Towards Augmented Emotional Clarity
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DOI：
10.1007/978-3-030-52240-7_29
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发表时间：
2020-06-10
期刊：
影响因子：
--
通讯作者：
Gong J
中科院分区：
文献类型：
--
作者：
Lee H;Mandalapu V;Kleinsmith A;Gong J
演讲焦虑（PSA）和外语焦虑（弗拉）困扰着大多数英语学习者（ELLs）。然而，很少有工具可以帮助多元文化学习者清楚地识别他们所感受到的焦虑类型。在本文中，我们提出了一个实地研究进行了真实的语言课堂。我们开发了基于皮肤电活动（EDA）特征的机器学习模型，以预测表现为PSA和弗拉的非语言行为。这些学生被贴上了PSA和弗拉焦虑类别的标签，PSA更多，弗拉更多，或者没有焦虑。为了将ELL分类到各自的焦虑类别中，突出的EDA特征被用来支持焦虑源的预测。这些结果可能会鼓励ELLs和教师都意识到焦虑亚型的起源，并制定一个定制的做法，在一门外语的公开演讲。
Public Speaking Anxiety (PSA) and Foreign Language Anxiety (FLA) afflict most English Language Learners (ELLs) during a presentation. However, few tools are available to help multicultural learners clearly identify which type of anxiety they are feeling. In this paper, we present a field study conducted in real language classrooms. We developed machine learning models based on features of electrodermal activity (EDA) to predict non-verbal behaviors manifested as PSA and FLA. The students were labeled with the anxiety categories both PSA and FLA, PSA more, FLA more, or no anxiety. To classify the ELLs into their respective anxiety categories, prominent EDA features were employed that supported the predictions of anxiety sources. These results may encourage both ELLs and instructors to be aware of the origins of anxiety subtypes and develop a customized practice for public speaking in a foreign language.
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影响因子：
10.3
作者：
Butler RM;Boden MT;Olino TM;Morrison AS;Goldin PR;Gross JJ;Heimberg RG
通讯作者：
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影响因子：
4.9
作者：
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通讯作者：
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影响因子：
2.7
作者：
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通讯作者：
YOUNG, DJ
DOI：
10.1016/j.jbtep.2004.04.012
发表时间：
2004-09-01
影响因子：
1.8
作者：
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通讯作者：
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DOI：
10.2307/1166137
发表时间：
1994-01-01
影响因子：
9.5
作者：
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通讯作者：
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