Early morning university classes correlate with poor sleep and academicperformance dukenus NatureHumBehav
. More studies are needed to assess whether starting classes later can result in sustained improvements in sleep behaviour and class attendance. Some students may gradually shift their bedtime later, hence reducing the benefit of starting classes later. Concurrent interventions to improve students’ self-regulation skills may be important for ensuring that students allocate enough time for sleep and attend classes.
The method of using Wi-Fi connection data to estimate class attendance was validated by collecting attendance data from course instructors. Attendance data were obtained for 53 class sessions across 13 different courses. Instructors who provided attendance data were recruited from a convenience sample of faculty involved in educational research. In each of the class sessions, we determined the number of enroled students with at least one Wi-Fi connection during class.
Wi-Fi-confirmed attendance was investigated over three semesters using all available data on the ALSET Data Lake before the COVID-19 pandemic. We decided to focus on large lecture courses because we expected that students would be more likely to skip these classes compared with other types of courses that are smaller and more interactive. Absenteeism is less likely to be noticed or tracked in larger lecture courses, and in-class participation is not a key element of most lecture courses.
. The average class size in the dataset was 193 ± 73 students and class size did not differ between lecture start times = 0.91,= 0.476). The Wi-Fi-confirmed attendance rate for each student was determined in each of the 337 courses. In a given course, this was calculated as the number of lectures in which a student was detected by Wi-Fi, divided by the total number of lectures held during the semester .
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