Identification of heart rate change during the teaching process

Area of Science:

• Educational Technology
• Physiological Computing
• Human-Computer Interaction

Background:

• The Internet of Things (IoT) offers novel methods for non-invasive physiological monitoring.
• Understanding student engagement and arousal is crucial for effective teaching, especially in remote learning environments.

Purpose of the Study:

• To investigate the use of common IoT devices for non-invasive physiological data acquisition.
• To identify changes in student arousal levels during the teaching process using physiological data.
• To explore the correlation between heart rate, arousal, and learning outcomes.

Main Methods:

• Collected physiological data, specifically heart rate (HR), from students during distance learning activities.
• Recorded time-stamped data correlating HR with specific teaching activities.
• Utilized IoT devices for accessible and non-invasive data collection.

Main Results:

• Demonstrated the feasibility of using IoT devices to monitor physiological responses.
• Identified patterns in heart rate changes related to student arousal levels during online lessons.
• Established a potential link between physiological arousal and learning engagement.

Conclusions:

• The proposed system can identify shifts in student arousal, offering a pathway to enhance teaching efficiency.
• Real-time monitoring of arousal can enable teachers to adjust pedagogical strategies for improved student understanding.
• This methodology supports data-driven improvements in educational delivery and learning success.