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Do Students with Different Personality Traits Demonstrate Different Physiological Signals in Video-based Learning?

Human-Computer Interaction 2025-01-03 v1 Artificial Intelligence

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.

Keywords

Cite

@article{arxiv.2501.00449,
  title  = {Do Students with Different Personality Traits Demonstrate Different Physiological Signals in Video-based Learning?},
  author = {Chun-Hsiung Tseng and Hao-Chiang Koong Lin and Yung-Hui Chen and Jia-Rou Lin and Andrew Chih-Wei Huang},
  journal= {arXiv preprint arXiv:2501.00449},
  year   = {2025}
}
R2 v1 2026-06-28T20:53:22.212Z