Facial animacy in anthropomorphised designs: Insights from leveraging self-report and facial expression analysis for multimedia learning

IF 8.9 1区 教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers & Education Pub Date : 2024-09-05 DOI:10.1016/j.compedu.2024.105150
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Abstract

Anthropomorphism is the act of attributing human-like characteristics to non-human objects and has played a key role in the field of emotional design in multimedia learning. Despite its significance, the relationship between animacy and anthropomorphism, particularly facial animacy, remains underexplored albeit its potential impact on learning engagement and emotional responses. Hence, this study aims to address this gap by examining the effects of facial animacy in anthropomorphised designs using a 3 × 2 design (none vs. static vs. animated) based on self-reported measure (SRM) and facial emotion recognition (FER) and how both measures are associated. The findings revealed discrepancies between both measures, with mostly moderate to weak correlations between hypothesised associations. SRM results indicated that face animacy decreased perceived boredom, while static and dynamic anthropomorphised designs increased curiosity. The FER results revealed notable similarities between designs without anthropomorphism and the static versions, highlighting that facial animacy led participants to express more joy and less neutral expressions. Additionally, neutral expressions were associated with lower enjoyment perception, while negative emotions, especially boredom, were linked to reduced attention.

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拟人化设计中的面部动画:利用自我报告和面部表情分析进行多媒体学习的启示
拟人化是将类似人类的特征赋予非人类物体的行为,在多媒体学习的情感设计领域发挥着关键作用。尽管拟人化具有重要意义,但动画与拟人化之间的关系,尤其是面部动画,尽管对学习参与和情感反应有潜在影响,却仍未得到充分探索。因此,本研究采用 3 × 2 设计(无 vs. 静态 vs. 有动画),基于自我报告测量法(SRM)和面部情绪识别法(FER),研究拟人化设计中面部动画的影响以及这两种测量法之间的关联,旨在填补这一空白。研究结果表明,这两种测量之间存在差异,假设的关联之间大多存在中度到弱度的相关性。SRM 结果表明,面部动画降低了感知到的无聊感,而静态和动态拟人化设计则增加了好奇心。FER结果显示,没有拟人化的设计与静态版本的设计有明显的相似之处,突出表明面部动画使参与者表达更多的喜悦,而较少表达中性表情。此外,中性表情与较低的快乐感知有关,而负面情绪,尤其是无聊,则与注意力下降有关。
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来源期刊
Computers & Education
Computers & Education 工程技术-计算机:跨学科应用
CiteScore
27.10
自引率
5.80%
发文量
204
审稿时长
42 days
期刊介绍: Computers & Education seeks to advance understanding of how digital technology can improve education by publishing high-quality research that expands both theory and practice. The journal welcomes research papers exploring the pedagogical applications of digital technology, with a focus broad enough to appeal to the wider education community.
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