Who excels in online learning in Japan? - Eisuke Tokiwa (Frontiers in Psychology)
IntroductionThis study aims to elucidate the impact of Big Five personality traits on learning behaviors and outcomes in online education. Given the increasing reliance on digital learning platforms, understanding individual differences in learning performance is crucial, particularly in the Japanese context.MethodsData were collected from 103 third-year high school students in Tokyo, utilizing the online learning platform “Study Sapuri” and a personality traits questionnaire (BFI-2-J). Learning behaviors were assessed through system logs, while personality traits were measured using a validated psychological scale. Spearman correlation analysis was employed to examine the relationships between these variables. The correlation calculations were based on Equations 1-3, which provide the framework for assessing relationships between variables.ResultsThe analysis revealed that conscientiousness had the strongest positive influence on learning outcomes, with students scoring high in conscientiousness achieving superior results, particularly in STEM subjects. Additionally, agreeableness was positively associated with learning behaviors, such as the number of video content views on the platform. In contrast, extraversion showed varying effects depending on its facets: assertiveness positively influenced learning outcomes, while sociability was associated with a more passive approach. Moreover, students with high levels of neuroticism tended to adopt a cautious attitude toward learning, which was linked to longer study durations and potentially higher learning quality.DiscussionThese findings highlight the role of personality traits in shaping online learning engagement and effectiveness. The study also suggests that Japan’s cultural context may influence the relationship between personality traits and academic performance, leading to outcomes for extraversion and neuroticism that differ from those observed in other countries. The implications of these results for personalized learning strategies and digital education design are discussed.