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

December 31, 2024 Β· Declared Dead Β· πŸ› Cogent Education

πŸ‘» CAUSE OF DEATH: Ghosted
No code link whatsoever

"No code URL or promise found in abstract"

Evidence collected by the PWNC Scanner

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.
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

πŸ“œ Similar Papers

In the same crypt β€” Human-Computer Interaction

Died the same way β€” πŸ‘» Ghosted