## 4 Analysis Results
### Structural Model Analysis
#### 4.2.1 Path Analysis  
The Table 7 shows the results of path coefficients. Hedonic motivation (HM) (b = 0.301, \(p\) < 0.001), cultural intelligence (CQ) (b = 0.277, \(p\) = 0.012) and English self-efficacy (ESE) (b = 0.189, \(p\) = 0.002) significantly impact to quality of experience (QoE). Quality of experience (QoE) (b = 0.829, \(p\) < 0.001) significantly impact to English continues learning intention (ECL).  
The results support the research question regarding the validity of the research model. A total of 48.8% of the quality of experience (QoE) can be explained by hedonic motivation (HM), cultural intelligence (CQ) and English self-efficacy (ESE) constructs. Further,  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Model Fit** & **Criteria** & **Model Fit of the Research Model** \\ \hline ML\(\chi^{2}\) & The small the better & 2177.135 \\ DF & The large the better & 887.000 \\ Normed Chi-sqr (\(\chi^{2}\)/DF) & 1 \(<\)\(\chi^{2}\)/DF \(<\) 3 & 2.454 \\ RMSEA & \textless{}0.08 & 0.061 \\ SRMR & \textless{}0.08 & 0.064 \\ TLI (NNFI) & \textgreater{}0.9 & 0.889 \\ CFI & \textgreater{}0.9 & 0.896 \\ GFI & \textgreater{}0.9 & 0.837 \\ AGFI & \textgreater{}0.9 & 0.827 \\ \hline \hline \end{tabular} Note: DF: degree of freedom; RMSEA: root mean square error of approximation; SRMR: standardized root mean square residual; TLI: Tucker–Lewis index; NNFI: non-normed fit index; CFI: comparative fit index; GFI: goodness of fit index; AGFI: adjusted-goodness-of-fit index.  
\end{table}
Table 6: Model fit.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**DV** & **IV** & **Unstd.** & **S.E.** & **Unstd./S.E.** & \(p\)**-Value** & **Std.** & \(\mathbf{R^{2}}\) \\ \hline QoE & HM & 0.301 & 0.048 & 6.319 & 0.000 & 0.405 & 0.488 \\  & CQ & 0.277 & 0.111 & 2.500 & 0.012 & 0.190 & \\  & ESE & 0.189 & 0.060 & 3.158 & 0.002 & 0.213 & \\ ECL & QE & 0.829 & 0.068 & 12.172 & 0.000 & 0.721 & 0.519 \\ \hline \hline \end{tabular} Note: DV: dependent variable; IV: independent variable; Unstd.: unstandardized; S.E.: standard error; Std.: standard.  
\end{table}
Table 7: Regression coefficient.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & **AVE** & **HM** & **QE** & **ECL** & **CQ** & **ESE** \\ \hline HM & 0.860 & **0.927** & & & & \\ QE & 0.557 & 0.642 & **0.746** & & & \\ ECL & 0.764 & 0.463 & 0.721 & **0.874** & & \\ CQ & 0.593 & 0.628 & 0.579 & 0.417 & **0.770** & \\ ESE & 0.706 & 0.554 & 0.557 & 0.401 & 0.633 & **0.84** \\ \hline \hline \end{tabular} Note: The items on the diagonal in bold represent the square roots of the AVE; off-diagonal elements are the correlation estimates. AVE: average variance extracted; HM: hedonic motivation; QoE: quality of experience; ECL: English continuous learning intention; CQ: cultural intelligence; ESE: English self-efficacy.  
\end{table}
Table 5: Discriminant validity for the measurement model.  
51.9% of English continues learning intention (ECL) can be explained by the quality of experience (QoE) constructs, as Figure 2 shows. In the figure, * means the regression coefficient's p-value less than 0.05, ** means the p-value less than 0.01, and *** means the \(p\)-value less than 0.001, as the figures in Table 7.