Student Clickstream Data: Does Time of Day Matter?
Gina Ricker, Mathew Koziarski, Pearson Online & Blended Learning, United States ; Alyssa Walters, Pearson Online and Blended Learning, United States
Journal of Online Learning Research Volume 6, Number 2, ISSN 2374-1473 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC USA
Student activity data has a demonstrated relationship with performance in the online classroom. The implications and context of activity levels in K-12 online schools are not yet well understood. This study examined the role of student chronotype, defined here as the time of day a student is most active in an online course, and overall activity level on course performance. Clickstream data captured by a Learning Management System from 411 students enrolled in an 11th grade English course in the fall of 2018 at two Midwestern full-time K-12 virtual schools were used to determine chronotype and activity level. Students were classified as one of four possible chronotypes given the mode of their click activity. Because students who enroll late typically under-perform compared to students who enroll on time, time of enrollment was controlled for. Results of an ANCOVA showed that students who are most active in the morning significantly outperformed students who are most active in the afternoon and evening. Morning students also tend to be the most active overall. The results of a hierarchical regression imply that total student activity in the course is contextualized by chronotype and has a more substantial impact on performance.
Ricker, G., Koziarski, M. & Walters, A. (2020). Student Clickstream Data: Does Time of Day Matter?. Journal of Online Learning Research, 6(2), 155-170. Waynesville, NC USA: Association for the Advancement of Computing in Education (AACE).
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