The Impact of Application-Specific Computer Self-efficacy on Chinese College Students’ Learning Satisfaction in English MOOCs: Mediating Roles of Intrinsic Motivation and Perceived Usefulness

Hypotheses:
H1. Perceived usefulness (PU) positively influences online learning satisfaction (OLS).
H2. Intrinsic motivation (IM) positively influences perceived usefulness (PU).
H3. Intrinsic motivation (IM) positively influences online learning satisfaction (OLS).
H4. Application-specific computer self-efficacy (ACS) positively influences intrinsic motivation (IM).
H5. Application-specific computer self-efficacy (ACS) positively influences perceived usefulness (PU).
H6. Application-specific computer self-efficacy (ACS) positively influences online learning satisfaction (OLS).
H7. Intrinsic motivation (IM) mediates the relationship between application-specific computer self-efficacy (ACS) and online learning satisfaction (OLS).
H8. Perceived usefulness (PU) mediates the relationship between application-specific computer self-efficacy (ACS) and online learning satisfaction (OLS).
H9. Intrinsic motivation (IM) and perceived usefulness (PU) collectively mediate the relationship between application-specific computer self-efficacy (ACS) and online learning satisfaction (OLS).
Findings:
Several salient relationships surfaced during the exploration of the interplay between predictors of learning satisfaction in English MOOCs. First and fore-most, application-specific computer self-efficacy was notably related to intrinsic motivation (β=0.745, p<0.001), perceived usefulness (β=0.574, p<0.001), and online learning satisfaction (β=0.242, p<0.01), accounting for 55.5% of the vari-ance in intrinsic motivation (R2=0.555). Besides, intrinsic motivation demon-strated a strong connection with perceived usefulness (β=0.310, p<0.001) and online learning satisfaction (β=0.280, p<0.001). Both application-specific com-puter self-efficacy and intrinsic motivation addressed 69.1% of the variance in perceived usefulness (R2=0.691). Perceived usefulness, in turn, was also signifi-cantly linked to online learning satisfaction (β=0.419, p<0.001). The combinato-rial influence of application-specific computer self-efficacy, intrinsic motivation, and perceived usefulness contributed to 75% of the variance in online learning satisfaction (R2=0.750). This substantial proportion highlights these factors as key drivers of satisfaction in digital learning settings.