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.研究假设： H1. 感知有用性（Perceived Usefulness，PU）对在线学习满意度（Online Learning Satisfaction，OLS）具有正向影响。 H2. 内在动机（Intrinsic Motivation，IM）正向影响感知有用性（PU）。 H3. 内在动机（IM）正向影响在线学习满意度（OLS）。 H4. 特定应用计算机自我效能感（Application-specific Computer Self-efficacy，ACS）正向影响内在动机（IM）。 H5. 特定应用计算机自我效能感（ACS）正向影响感知有用性（PU）。 H6. 特定应用计算机自我效能感（ACS）正向影响在线学习满意度（OLS）。 H7. 内在动机（IM）在特定应用计算机自我效能感（ACS）与在线学习满意度（OLS）的关系中起中介作用。 H8. 感知有用性（PU）在特定应用计算机自我效能感（ACS）与在线学习满意度（OLS）的关系中起中介作用。 H9. 内在动机（IM）与感知有用性（PU）共同在特定应用计算机自我效能感（ACS）与在线学习满意度（OLS）的关系中起中介作用。 研究结果： 在针对英语慕课（Massive Open Online Courses，MOOC）学习满意度预测变量间的相互作用展开探究的过程中，多项显著关联得以显现。首先，特定应用计算机自我效能感（ACS）与内在动机（IM，β=0.745，p<0.001）、感知有用性（PU，β=0.574，p<0.001）及在线学习满意度（OLS，β=0.242，p<0.01）均存在显著关联，可解释内在动机55.5%的方差（R²=0.555）。此外，内在动机（IM）与感知有用性（PU，β=0.310，p<0.001）及在线学习满意度（OLS，β=0.280，p<0.001）存在较强关联。特定应用计算机自我效能感（ACS）与内在动机（IM）共同可解释感知有用性（PU）69.1%的方差（R²=0.691）。而感知有用性（PU）同样与在线学习满意度（OLS）存在显著关联（β=0.419，p<0.001）。特定应用计算机自我效能感（ACS）、内在动机（IM）与感知有用性（PU）的联合影响可解释在线学习满意度（OLS）75%的方差（R²=0.750）。这一较高的解释比例表明，上述因素是数字学习场景中学习满意度的关键驱动因素。