The Impact of Gender on Online Learning Behavioral Patterns: A Comparative Study Based on Lag Sequential Analysis

Abstract

Despite several studies highlighted the importance of considering gender in online learning, the current literature about how male and female students would behave is still fragmented. Additionally, little attention has been paid to investigating the impact of gender on online learning behavioral patterns. This study applies lag sequential analysis (LSA) to investigate gender-related difference in the behavioral patterns of 116 students in an online course for six weeks. The obtained results indicated that overall there is no significant difference in the frequency of online learning behaviors between female and male students. However, the LSA showed that males and females demonstrated different transitional patterns in their online learning behaviors. Female behaviors were more coherently linked to each other. In contrast, some of the male behaviors were relatively isolated without significant antecedents and consequences, calling for learning supports. Also, females tended to view their achievement reports before starting the main course activities, showing that female students were more achievement-oriented. The findings provide explanations about how gender affects online learning and implications on how to design personalized online learning interventions based on considering gender-related differences.