Engagement To Online Learning, Mental Well-Being, Self-Regulated Learning, And Academic Performance: A Path Analysis
REY ALMER L. GINDAP, LPT, MAED1, NEIL RYAN B. ADO, LPT, PhD2,
PERLA C. PADRO, LPT, PhD3
https://orcid.org/0000-0002-1477-62781, https://orcid.org/0000-0002-0764-02412,
https://orcid.org/0000-0001-9074-61023
sirgindapreyalmer@gmail.com1, neilrarye1985@gmail.com2, p.padro@smctagum.edu.ph3
St. Mary’s College of Tagum, Inc.
Tagum City, Davao del Norte, Philippines1-3
DOI: https://doi.org/10.54476/ioer-imrj/44714
ABSTRACT
The recent data disclosed that more than 50 percent of the countries worldwide and most of the ASEAN countries scored below average in the Science subjects. Furthermore, due to the pandemic, online or e-learning is the most effective way to continue the teaching and learning process. This is a quantitative study that used a descriptive-correlational design with route analysis to handle data. This study investigated the association between four interrelated variables: engagement to online learning (ETOL), self-regulated learning (SRL), mental well-being (MWB), and academic performance (AP) in science subjects. Stratified random sampling was used to choose grade 12 STEM students from schools in Davao del Norte, Philippines. Data gathered were treated using Pearson-r, mean, structural equation modelling, and multiple regression analysis. Findings revealed that only SRL turned out to be a statistically significant predictor of AP in Science. More so, as to the best fit model, both SRL and MWB have a direct influence on AP, but ETOL has a large indirect effect on AP through SRL and MWB. Thus, students should exercise greater self-regulation. Educators must highlight students’ self-regulated learning skills in online learning.
Keywords: Path analysis, Sequential Equation Modeling, engagement to online learning, self-regulated learning, mental well-being, academic performance