An Examination of Cyber University Students’ LMS Log Data : Focusing on Login Times Based on Learner Characteristics

This study aims to analyze the login times and learning patterns of cyber university students on the LMS, focusing on factors such as login device, learner gender, and age group with the aim of contributing to the design and operation of online course offerings. The analysis draws from LMS log data of 401 students enrolled in an English program at a cyber university, revealing several significant patterns. First, students showed a strong preference for logging in via PCs rather than mobile phones. Second, there were notable differences in device preferences related to age and gender. Men in their 40s logged in more frequently using mobile devices compared to younger users in their 20s and 30s. Third, login patterns varied by day of the week, with the highest activity occurring on Sundays and a decline as the weekend approached. For female students, login activity peaked between 9 and 11 AM and between 8 and 10 PM. Among women over 30, login rates dropped around typical work hours, suggesting a potential connection to work schedules. Finally, time-based analysis showed that men’s peak login times were between 9 and 10 AM and 8 and 10 PM, while men over 50 exhibited a different pattern, with login activity steadily increasing from 9 AM and peaking at 2 PM. These findings underscore the importance of considering demographic factors in the design of online learning platforms.