摘要
采用3(自闭症儿童、智障儿童和普通儿童)×3(面孔偏转0度、45度、90度)×3(高兴表情、中性表情、愤怒表情)三因素混合实验设计,考察自闭症儿童在不同面部偏转角度的条件下,对于高兴、中性和愤怒表情的觉察能力。结果发现,自闭症儿童表情觉察的正确率与智障儿童和普通儿童存在显著差异,而在正确反应时方面差异不显著;三类儿童均表现出对于高兴表情的觉察效能优于愤怒表情;在0度面孔偏转角度的条件下儿童表情觉察的正确率显著高于45度和90度,且正确反应时短于45度和90度。研究者认为,自闭症儿童对不同面孔偏转的表情觉察总体认知加工能力偏低,受面孔偏转角度影响显著,较多依赖于面孔构形信息,同时在表情觉察过程中表现出正性情绪突显效应。
This study, based on the 3 (participants: children with ASD, ID, and TD)×3 (face viewpoints: O, 45, and90 degrees) x 3 (facial expressions: happy, neutral, and angry) mixed design, aims to explore autistic children's ability to detect happy, neutral, and angry facial expressions under different face viewpoints. The results show the following: There was a significant difference between the three types of children in the rate of correctness of facial expression detection, but an insignificant difference between them in the time for correct reaction; the three types of children showed a greater ability in their detection of happy expressions than in their detection of angry expressions; and they showed a significantly higher rate of correctness of facial expression detection and a shorter time for correct reaction under the 0-degree face viewpoints than under the 45- or 90- degree face viewpoints. The study concludes the following: Autistic children show a low ability to detect facial expressions under different face viewpoints; they are significantly affected by face viewpoints; they depend much on facial configurations; and they show significantly positive emotions in their detection of facial expressions.
作者
林云强
童叶莹
LIN Yunqiang TONG Yeying(Hangzhou College for Kindergarten Teachers, Zhejiang Normal University, Hangzhou, 310012 Fenghua Special Education School, Fenghua, 315500)
出处
《中国特殊教育》
CSSCI
北大核心
2016年第12期33-40,共8页
Chinese Journal of Special Education
基金
2014年度教育部人文社会科学研究青年基金项目"自闭症谱系障碍儿童的威胁知觉及其教育应用研究"(项目批准号:14YJC880033)
2015年度浙江省高校人文社会科学重点研究基地浙江师范大学教育学一级学科基地项目"3-8岁儿童挑战性行为的表现特征
功能特点及教育应对策略"(项目批准号:ZJJYX201509)
浙江省哲学社会科学研究培育基地--浙江师范大学儿童研究院研究专项的研究成果之一
关键词
自闭症儿童
面孔偏转角度
面部表情
表情觉察
children with autism face viewpoint facial expressions facial expression detection