本研究旨在利用眼球追蹤技術探討自閉症學生和一般正常發展學生的情緒表情辨
識任務，以進一步瞭解自閉症患者在面對不同圖片格式的數位表情符號時，其辨識率與
視覺注意力分布和一般正常發展學生是否有所差異。為達上述目的，本研究採用實驗研
究法，以新北市某中學之 7-9 年級的學生為研究對象，共招募一般發展學生 29 位、自閉
症學生 6 位，進行數位表情符號情緒辨識測驗（簡稱「 REFE 測驗」），並透過眼球追蹤
技術針對其辨識表情符號的歷程進行眼動資料的資料收集與分析。研究結果發現：（一）
自閉症學生與一般正常發展學生在判讀三種圖片格式（卡通圖片、圖像表情符號、 顏文
字）的表情辨識率無顯著差異；（二）自閉症學生與一般正常發展學生在數位表情符號情
緒辨識測驗中，視覺注意力之分布呈現組間顯著差異，兩組學生在觀看卡通圖片時，自
閉症學生傾向凝視於臉孔的下半部，與一般正常發展學生傾向凝視臉孔的上半部不同，
此外，在辨識圖像表情符號時，自閉症學生較不會把視覺注意力放在眉毛的位置；然而，
兩組學生在辨識顏文字的眼動歷程卻無顯著的差異；（三）自閉症學生與一般正常發展
學生在辨識表情符號時，眼動指標與表情辨識率之間有顯著相關性，當學生在觀看卡通
圖片時，在眼睛及鼻子的凝視時間與辨識率呈現顯著的相關性，以及當學生在判讀較複
雜的表情符號時，會需要更多的時間以及非眼睛的線索來做為判斷的依據。

The purpose of this study was to investigate how high school students recognize different formats of digital emoticons by using eye-tracking techniques. In particular, this study adopted an experimental design to examine the difference in the recognition of digital emoticons between autism spectrum disorder (ASD) and typically-developing (TD) students in terms of the rate of accurate recognition of the digital emoticons and eight eye-movement indices. The participants in this study were 29 TD students and 6 ASD students. The two groups of students were asked to recognize 18 digital emoticons represented by three different formats (cartoon pictures, emoji images, and emoticon images) and six different sorts of emotional expressions (happiness, anger, sadness, surprise, disgust, and fear). An eye-tracker was used to record the participants’ eye movements while they were recognizing the digital emoticons. The results of this study indicate that the two groups had no significant difference in the rates of accurate recognition of the digital emoticons with respect to the three formats and six sorts. Nonetheless, the two groups showed different patterns of visual attention while recognizing the digital emoticons. The ADS students tended to pay more attention to the lower part of the faces of the cartoon pictures, while the TD students were more likely to focus on the upper part of the face. In addition, the ASD students paid less attention to eyebrows than TD students while watching the emoji images. However, the two groups had no difference in all eight eye-movement indices while recognizing the emoticon images. Moreover, there are some significant correlations between the rates of accurate recognition of the digital emoticons and the eye-movement indices. The rates of accurate recognition appear to positively correlate with the fixation durations on the eyes of the cartoon pictures but negatively correlated with the fixation durations on the eye in the emoji images and emoticon images.

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