Seasonal Patterns Of Learning Management System Logins Interact With Chronotype, Social Jet Lag, And Gender To Impact Academic Performance
Location
SU 214
Start Date
19-4-2019 10:20 AM
Department
Biology
Abstract
Human circadian rythms are 24-hour oscillations in individual’s behavior and physiology that are synchronized with environmental cues. These individuals develop stable phase relationships between the environment and their internal rhythms giving rise to different chronotypes (e.g. morning larks, afternoon finches, and night owls). Misalignment between these rhythms has been shown to have severe consequences to health and academic performance. One such misalignment, caused by the imposition of one’s social schedule, is termed social jetlag (SJL). Previous studies have shown that increased levels of social jetlag correlate with decreased academic performance, but data on the impact of season and gender on this phenomenon are limited. Online records of daily logins from the university learning management system Desire to Learn (D2L) have been used to study the interaction between chronotype, social jetlag, gender, and academic performance. In the current study, we mined data from over 3 million Desire to Learn login events by Northeastern Illinois University students and analyzed these data in the R 3.5.0 statistical package to identify seasonal patterns across chronotypes in login activity and social jetlag. Specifically, semesters were broken down into week bins characterized by class and non-class day activity in Desire to Learn, and chronotypes were assessed by median non-class day activity per semester. Social jetlag was calculated by subtracting the median login time of non-class days from the median login time on class days. Students were then sorted and patterns in social jetlag and grade point average were identified. Preliminary results suggest that social jetlag was lower and grade point average was higher in the spring compared to fall. In addition, women were found to have higher grade point averages and take fewer courses than men, however, they both have the same social jetlag levels. Data mining across multiple semesters worth of academic profiles in Desire to Learn will provide knowledge for students, educators, and universities to create customized schedules that fit individual chronotypes in an effort to minimize social jetlag and increase overall academic performance.
Seasonal Patterns Of Learning Management System Logins Interact With Chronotype, Social Jet Lag, And Gender To Impact Academic Performance
SU 214
Human circadian rythms are 24-hour oscillations in individual’s behavior and physiology that are synchronized with environmental cues. These individuals develop stable phase relationships between the environment and their internal rhythms giving rise to different chronotypes (e.g. morning larks, afternoon finches, and night owls). Misalignment between these rhythms has been shown to have severe consequences to health and academic performance. One such misalignment, caused by the imposition of one’s social schedule, is termed social jetlag (SJL). Previous studies have shown that increased levels of social jetlag correlate with decreased academic performance, but data on the impact of season and gender on this phenomenon are limited. Online records of daily logins from the university learning management system Desire to Learn (D2L) have been used to study the interaction between chronotype, social jetlag, gender, and academic performance. In the current study, we mined data from over 3 million Desire to Learn login events by Northeastern Illinois University students and analyzed these data in the R 3.5.0 statistical package to identify seasonal patterns across chronotypes in login activity and social jetlag. Specifically, semesters were broken down into week bins characterized by class and non-class day activity in Desire to Learn, and chronotypes were assessed by median non-class day activity per semester. Social jetlag was calculated by subtracting the median login time of non-class days from the median login time on class days. Students were then sorted and patterns in social jetlag and grade point average were identified. Preliminary results suggest that social jetlag was lower and grade point average was higher in the spring compared to fall. In addition, women were found to have higher grade point averages and take fewer courses than men, however, they both have the same social jetlag levels. Data mining across multiple semesters worth of academic profiles in Desire to Learn will provide knowledge for students, educators, and universities to create customized schedules that fit individual chronotypes in an effort to minimize social jetlag and increase overall academic performance.
Comments
Aaron Schirmer and Benjamin Smarr are the faculty sponsors of this project.