Investigating student engagement in blended learning settings using experience sampling and structural equation modeling

We investigated activity-level student engagement in blended learning classes at the university level. We used intensive longitudinal methodology to collect activity level engagement data throughout a semester for 68 students enrolled in six blended courses across two universities. We used structural equation modeling to gain a holistic understanding of learning environments, including the influence of personal characteristics, course design, and student perceptions of the learning experience on in-the-moment cognitive and emotional engagement. To investigate longitudinal relationships between emotional and cognitive engagement, we employed cross-lagged modeling techniques. Findings showed that course design and student perception variables had a greater influence on engagement than individual student characteristics and that student multitasking had a strong negative influence on engagement. Students' perceptions of the importance of the activity had a strong positive influence on both cognitive and emotional engagement. An important outcome of engagement was the students' perceptions that they were learning and improving.