From perceptive and eye-tracking perspectives to explore Senior Vocational High School students’ misconceptions on emotion

碩士 === 國立嘉義大學 === 輔導與諮商學系研究所 === 100 === The purpose of this study are to understand the emotion perception of different misconceptions types of Vocational Senior High School students. The study implemented the "EQ-i:YV " as a research tool, and with the usage of eye-tracking systems and a...

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Bibliographic Details
Main Authors: Chang, Tien-Yu, 張恬瑜
Other Authors: Huang, Tsai-Wei
Format: Others
Language:zh-TW
Online Access:http://ndltd.ncl.edu.tw/handle/76274071124373352267
Description
Summary:碩士 === 國立嘉義大學 === 輔導與諮商學系研究所 === 100 === The purpose of this study are to understand the emotion perception of different misconceptions types of Vocational Senior High School students. The study implemented the "EQ-i:YV " as a research tool, and with the usage of eye-tracking systems and a emotion recognition test designed by the researcher, and recorded students' eye-tracking data through the GazeTracker software. Finally, we adopted the BW index designed by Huang(2011)to understand students' emotion misconceptions. The results of this study are summarized as follows: 1. Different misconceptions types of students' emotional types and intensities are of significantly different in the emotion of “scared”, but their emotional quotients are not. 2. Different misconceptions types of students' total time in slides are of significantly different in the emotion of “angry”, “hate”, and “neuter”. The total time in lookzones and the percentage of lookzones in total time are of significantly different in many subjects. The total number of entrances in lookzones are of significantly different in the emotion of “happy”, “angry”, “scared”, “hate”, “surprised” and “neuter”. 3. Different misconceptions types of students' C indexes were of significantly different, but their total score are not. And there are no differences in W, B, M indexes for sex. 4. Some of the misconceptions types, emotion perception and eye-tracking data are efficiently estimated the expressions and misconceptions of emotion.