Based on logistic regression model to explore the impact of different time pressure on network learning engagement

Objective: To investigate whether students’ network learning engagement varies under different time pressures in the Traditional Chinese medicine nursing course. Methods: Based on network teaching mode, in the once-weekly Traditional Chinese medicine nursing course of our school, three classes which were selected by a simple random sampling method are given different opening hours each week respectively: 3-day group, 5-day group, 7-day group. After the course, all students were given questionnaires which was collected online together with all the learning videos had been completed or not and other learning engagement related data. The whole process of the course was based on the web platform: i.chaoxing.com. The relevant influential factors were analyzed by logistic regression model - $p(y = 1\mid x) = \frac{{\exp (\beta 0 + \beta x)}}{{1 + \exp (\beta 0 + \beta x)}}$ – multiple linear regression model -Y=β
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- for online learning engagement. Result: The 5-day group showed the highest completion rate of the learning videos (P for trend = 0. 038). The active procrastinators in 3-day group have better the total number of learning times. Conclusion: In weekly sessions of Traditional Chinese Medicine Nursing, students given moderate time pressure to complete the course may obtain better learning engagement. Active procrastination is more involved in learning under high time pressure.