## 4 Analysis Results
### Measurement Model
#### 4.1.2 Second-Order Confirmatory Factor Analysis  
The definition of a second-order structure is that several first-order potential factors are affected by a higher level of common factors. There are no observed variables of second-order factors which are directly related to the first-order factors. Each first-order factor, otherwise, is related to its observed variable. A second-order model needs to evaluate by confirmatory factor analysis as the first-order factor does.  
The reliability and validity of the first-order factors should be confirmed before the evaluation of the second-order factor model. The factor loading between the second-order factor and first-order factors should be 0.7 or above, 0.6 above was acceptable. As shown in Table 3, the reliability and validity of all constructs meet the level recommended by [PERSON] and [PERSON].  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Construct**} & \multirow{2}{*}{**Item**} & \multicolumn{3}{c}{**Significance of Estimated Parameters**} & \multicolumn{2}{c}{**Item Reliability**} & \multicolumn{2}{c}{**Construct Reliability**} & \multicolumn{2}{c}{**Convergence Validity**} \\ \cline{3-9}  & & **Unstd.** & **S.E.** & **Unstd./S.E.** & \(p\)**-Value** & **Std.** & **SMC** & **CR** & **AVE** \\ \hline \multirow{4}{*}{HM} & HM1 & 1.000 & & & & 0.875 & 0.766 & 0.968 & 0.860 \\  & HM2 & 1.137 & 0.040 & 28.528 & 0.000 & 0.931 & 0.867 & & \\  & HM3 & 1.177 & 0.039 & 29.997 & 0.000 & 0.951 & 0.904 & & \\  & HM4 & 1.172 & 0.040 & 29.395 & 0.000 & 0.947 & 0.897 & & \\  & HM5 & 1.178 & 0.042 & 28.191 & 0.000 & 0.931 & 0.867 & & \\ \hline \multirow{4}{*}{QoE} & QE1 & 1.000 & & & & 0.728 & 0.530 & 0.882 & 0.557 \\  & QE2 & 1.168 & 0.076 & 15.319 & 0.000 & 0.793 & 0.629 & & \\  & QE3 & 1.262 & 0.085 & 14.857 & 0.000 & 0.786 & 0.618 & & \\  & QE4 & 1.041 & 0.084 & 12.324 & 0.000 & 0.667 & 0.445 & & \\  & QE5 & 1.214 & 0.094 & 12.907 & 0.000 & 0.737 & 0.543 & & \\  & QE6 & 1.181 & 0.088 & 13.393 & 0.000 & 0.758 & 0.575 & & \\ \hline \multirow{4}{*}{ECL} & ECL & 1.000 & & & & 0.837 & 0.701 & 0.928 & 0.764 \\  & ECL2 & 1.011 & 0.051 & 19.950 & 0.000 & 0.824 & 0.679 & & \\  & ECL3 & 1.037 & 0.045 & 22.802 & 0.000 & 0.894 & 0.799 & & \\  & ECL4 & 1.117 & 0.046 & 24.259 & 0.000 & 0.937 & 0.878 & & \\ \hline \hline \end{tabular} Note: Unstd.: unstandardized factor loadings; Std.: standardized factor loadings; SMC: square multiple correlations; CR: composite reliability; AVE: average variance extracted; HM: hedonic motivation; QoE: quality of experience; ECL: English continuous learning intention.  
\end{table}
Table 2: Results for the measurement model assessment.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Construct**} & \multirow{2}{*}{**Item**} & \multicolumn{3}{c}{**Significance of Estimated Parameters**} & \multicolumn{2}{c}{**Item Reliability**} & \multicolumn{2}{c}{**Construct Reliability**} & \multicolumn{2}{c}{**Convergence Validity**} \\ \cline{3-9}  & & **Unstd.** & **S.E.** & **Unstd./S.E.** & \(p\)**-Value** & **Std.** & **SMC** & **CR** & **AVE** \\ \hline MCQ & MCQ1 & 1.000 & & & & 0.764 & 0.584 & 0.759 & 0.515 \\  & MCQ2 & 0.757 & 0.072 & 10.522 & 0.000 & 0.620 & 0.384 & & \\  & MCQ3 & 1.008 & 0.083 & 12.193 & 0.000 & 0.759 & 0.576 & & \\ CCQ & CCQ6 & 1.000 & & & & 0.642 & 0.412 & 0.870 & 0.575 \\  & CCQ7 & 1.113 & 0.091 & 12.203 & 0.000 & 0.730 & 0.533 & & \\  & CCQ8 & 1.323 & 0.105 & 12.547 & 0.000 & 0.774 & 0.599 & & \\  & CCQ9 & 1.395 & 0.111 & 12.600 & 0.000 & 0.801 & 0.642 & & \\  & CCQ10 & 1.430 & 0.111 & 12.899 & 0.000 & 0.830 & 0.689 & & \\ OCGQ11 & 1.000 & & & & 0.647 & 0.419 & 0.845 & 0.522 \\  & OCQ12 & 1.350 & 0.110 & 12.310 & 0.000 & 0.771 & 0.594 & & \\  & OCQ13 & 1.073 & 0