  Student engagement plays a vital role in academic success with high
engagement often linked to positive educational outcomes. Traditionally,
student engagement is measured through self-reports, which are both
labour-intensive and not real-time. An emerging alternative is monitoring
physiological signals such as Electrodermal Activity (EDA) and Inter-Beat
Interval (IBI), which reflect students' emotional and cognitive states. In this
research, we analyzed these signals from 23 students wearing Empatica E4
devices in real-world scenarios. Diverging from previous studies focused on lab
settings or specific subjects, we examined physiological synchrony at the
intra-student level across various courses. We also assessed how different
courses influence physiological responses and identified consistent temporal
patterns. Our findings show unique physiological response patterns among
students, enhancing our understanding of student engagement dynamics. This
opens up possibilities for tailoring educational strategies based on
unobtrusive sensing data to optimize learning outcomes.
