Abstract
The present study investigates whether adults and children exhibit different eye-fixation patterns when they look at human faces, machinelike robotic faces, and humanlike robotic faces. The results from two between-subject experiments showed that children and adults did have different facial recognition patterns; children tended to fixate more on the mouth of both machinelike and humanlike robotic faces than they do on human faces, while adults focused more on the eyes. The implications of notable findings and the limitations of the experiment are discussed.
Highlights
Do children and adults share the same or similar patterns when they interact with robots? Are the ways in which children and adults view and form impressions of robots different? These and related questions have become relevant in recent years because R‐Learning for children has gained much attention and popularly lately
The results from the multivariate analysis of variance (MANOVA) indicated that participants who looked at the machinelike robotic faces (M=24.00%, SD=17.10) reported a longer fixation time on the mouth than those looking at the human faces (M=15.45%, SD=9.74), F(1,76)=16.81, p
The age of the participants did not have a significant effect on the percentage of the fixation time on the sum of core features, the results from the MANOVA found that adults (M=48.58%, SD=15.52) had a longer fixation time on the eyes than children (M=24.27%, SD=14.19), F(1,76)=52.57, p
Summary
Do children and adults share the same or similar patterns when they interact with robots? Are the ways in which children and adults view and form impressions of robots different? These and related questions have become relevant in recent years because R‐Learning for children has gained much attention and popularly lately. Are the ways in which children and adults view and form impressions of robots different? The present study argues that we may answer these questions by examining whether children and adults look at robotic faces differently when forming first impressions. When we communicate with others, we exchange our emotions, feelings and thoughts by using various communication modalities. Gross and Ballif suggested that facial expressions are one of the most efficient ways for understanding others’ emotions and feelings. Children do not have sufficient social communication skills to understand others’ minds or feelings when compared to adults [8], suggesting that the ways in which children recognize and see robotic faces may be different from that of adults
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