The Association Between Mental Health, Peer-to-Peer Confirmation and Learning Motivating Factors in E-Learning

Abstract

COVID‐19 lead to rapid implementation of e‐learning, but also increased the rates of anxiety, depression (Lawrence et al., 2021; Jojoa et al., 2021), and fatigue (Escudero‐Castillo, Mato‐Díaz, Rodriguez‐Alvarez, 2021), which relate to dramatically diminished e‐learning motivation. Thus, it was deemed important to identify e‐learning motivating factors related to mental health. Furthermore, since computer programming skills are among the core competencies that professionals are expected to possess in the era of rapid technology development, it was also critical to identify the factors related to computer programming learning.  Thus, this study aims to identify associations between depression, anxiety, fatigue, and learning motivating factors in e‐learning‐based education. Furthermore, this study aims to compare the patterns in participants and non‐participants of e‐learning‐based computer programming courses, and to identify the specific factors relating to computer programming e‐learners. The sample consisted of 596 e‐learners (198 men, 398 women; age range = 18-56, SD - 8,443), including 281 computer programming e‐learners, other respondents studied social sciences at various Lithuanian Universities; however, these students were studying remotely due to the COVID‐19 pandemic. Study instruments: the Learning Motivating Factors Questionnaire (Law et al., 2010), the Patient Health Questionnaire‐9 (Kroenke et al., 2001), the Generalized Anxiety Disorder Scale‐7 (Spitzer et al., 2006), and the Multidimensional Fatigue Inventory‐20 (Smets et al., 1995), the Student‐to‐Student Confirmation Scale (LaBelle & Johnson, 2018). The results revealed that computer programming e‐learners differed from other e‐learners in mental health, peer‐to‐peer confirmation and learning motivating factors. T‐test analysis revealed some statistically significant differences between the groups in peer-to-peer confirmation: university students in social sciences demonstrated higher scores of individual attention and acknowledgement than participants of e‐learning based computer programming education. A multiple linear regression showed that mental health was significantly related with learning motivating factors in the group of respondents participating in computer programming courses: depression was significantly related with challenging goals, reward and recognition, social pressure and competition; anxiety, fatigue was significantly related with challenging goals, reward and recognition. The challenging goals factor (intrinsic motivation) was a significant predictor of diminished depression, anxiety and fatigue in e-learning.