Do Students with Different Personality Traits Demonstrate Different Physiological Signals in Video-based Learning?
December 31, 2024 Β· Declared Dead Β· π Cogent Education
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Authors
Chun-Hsiung Tseng, Hao-Chiang Koong Lin, Yung-Hui Chen, Jia-Rou Lin, Andrew Chih-Wei Huang
arXiv ID
2501.00449
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.AI
Citations
2
Venue
Cogent Education
Last Checked
4 months ago
Abstract
Past researches show that personality trait is a strong predictor for ones academic performance. Today, mature and verified marker systems for assessing personality traits already exist. However, marker systems-based assessing methods have their own limitations. For example, dishonest responses cannot be avoided. In this research, the goal is to develop a method that can overcome the limitations. The proposed method will rely on physiological signals for the assessment. Thirty participants have participated in this experiment. Based on the statistical results, we found that there are correlations between students personality traits and their physiological signal change when learning via videos. Specifically, we found that participants degree of extraversion, agreeableness, conscientiousness, and openness to experiences are correlated with the variance of heart rates, the variance of GSR values, and the skewness of voice frequencies, etc.
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