Monitoring audience engagement using electrodermal activity during an inaugural lecture.

Area of Science:

• Psychology
• Neuroscience
• Human-Computer Interaction

Background:

• Quantifying audience attentional engagement in real-world settings is challenging using self-reports.
• Physiological synchrony, particularly electrodermal activity (EDA), shows potential for measuring engagement in controlled environments.
• Understanding group-specific attentional responses is crucial for optimizing communication and learning.

Purpose of the Study:

• To investigate the utility of physiological synchrony in electrodermal activity (EDA) for assessing audience engagement in a live lecture setting.
• To determine if EDA-based physiological synchrony can differentiate between audience groups with varying relationships to the speaker (personal vs. professional).
• To evaluate the correlation between physiological synchrony, individual EDA, and self-reported engagement levels.

Main Methods:

• Monitoring electrodermal activity (EDA) of 30 participants during an inaugural lecture.
• Calculating physiological synchrony between participants' EDA signals.
• Comparing synchrony and individual EDA measures between personal and professional groups.
• Correlating physiological measures with self-reported engagement levels and predefined lecture events.

Main Results:

• Physiological synchrony in EDA effectively distinguished between the personal and professional audience groups.
• Both physiological synchrony and individual EDA measures accurately identified predefined engaging lecture events.
• Neither physiological synchrony nor individual EDA showed a reliable correlation with post-lecture self-reported engagement levels.

Conclusions:

• Electrodermal activity (EDA) and physiological synchrony are sensitive measures of audience attention in real-world scenarios, independent of simple sensory or movement artifacts.
• Physiological synchrony offers a valuable, objective metric for understanding group-specific attentional dynamics in naturalistic settings.
• Future applications include optimizing educational content and entertainment experiences by analyzing expert-novice or target group engagement patterns.