AUTHOR=Rimasiute-Knabikiene Romualda , Dirzyte Aiste 

TITLE=Profiles of e-learners based on learning motivation: differences in peer-to-peer confirmation and mental health

JOURNAL=Frontiers in Education

VOLUME=Volume 10 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/education/articles/10.3389/feduc.2025.1622805

DOI=10.3389/feduc.2025.1622805

ISSN=2504-284X

ABSTRACT=IntroductionPrevious research employing latent profile analysis has considerably advanced our understanding of student motivation in online learning environments. However, a gap remains in exploring how mental health and social dimensions—specifically anxiety, depression, and peer-to-peer confirmation—influence these motivational profiles. Although prior studies indicate associations between student learning motivation, mental health, and peer-to-peer confirmation, their role in motivation profile is less understood. The current study aims to explore motivational profiles of e-learners, their differences in mental health, and their links to peer-to-peer confirmation.MethodsA cross-sectional survey of 595 university e-learners (33.3% male, 66.7% female; mean age 26.34 years, SD 8.4; age range 18–56) was conducted. Four instruments were used in this study: the Learning Motivating Factors Questionnaire, the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder Scale (GAD-7), and Student-to-Student Confirmation Scale. Latent profile analysis (LPA) identified motivation profiles. Binomial logistic regression tested whether peer-to-peer confirmation dimensions predicted profile membership, and independent-samples t-tests compared anxiety and depression between profiles.ResultsThe latent profile analysis (LPA) identified high motivation profile and low motivation profile. The results of the binomial logistic regression revealed that peer-to-peer confirmation, namely, individual attention, was a significant predictor of student motivation: higher individual attention predicted high motivation profile membership, suggesting that personalized interactions between peers serve as a protective factor against low motivation. Additionally, e-learners in the low motivation profile had significantly higher levels of anxiety and depression.ConclusionThis study contributes to the growing research on student motivation, peer-to-peer confirmation, and mental health in e-learning. The latent profile analysis underscored the importance of individual attention as a unique and powerful factor in motivating students in e-learning environments. As higher education continues to embrace e-learning models, it will be essential to integrate effective mechanisms for peer interactions and communication processes to enhance student motivation. Additionally, the findings revealed that e-learners in the low motivation profile had significantly higher levels of anxiety and depression, which suggests that students' mental health should be among the priorities of education policies targeting correlates of academic achievements. Future studies should examine factors that are both protective for e-learners mental health and beneficial for learning outcomes.