## 5 Evaluation of Student Motivation through Questionnaires Related to the ARCS Model
### Research Hypothesis Validity  
For path analysis, we used a linear regression coefficient analysis to examine the explaination of the factors of the research model (Figure 7), in order to verify the four research hypotheses. We analyzed the causal relationships between two variables in the model, and how they directly or indirectly affected each other. The \(R^{2}\) value was calculated to show the percentage of total variance which was explained by the independent variables and regression analysis model. We used SPSS as a statistical tool to analyze the results of the linear regression coefficient analysis, in order to further validate the four research hypotheses. Overall, we hoped to prove that the AR teaching design can significantly assist English teacher and enhance concentration, confidence, satisfaction, and learning effectiveness in EFL students. Next, we tested whether the direct influence of the independent variable (learning interest using AR) on the dependent variable existed and was significant. The \(\beta\) value was obtained after making sure, \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Learning** & **Learning** & **Learning** & **Learning** & **Learning** \\  & **Attitude** & **Interest** & **Behavior** & **Satisfaction** & **Effectiveness** \\ \hline Learning attitude & \multirow{2}{*}{1} & \multirow{2}{*}{0.590(**)} & \multirow{2}{*}{0.306} & \multirow{2}{*}{0.618(**)} & \multirow{2}{*}{0.822(**)} \\ Pearson Correlation & & & & & \\ Significance & & & & & \\ (two-tailed) & & & & & \\ \hline Learning interest & \multirow{2}{*}{0.590(**)} & \multirow{2}{*}{1} & \multirow{2}{*}{0.518(*)} & \multirow{2}{*}{0.568(**)} & \multirow{2}{*}{0.485(*)} \\ Pearson Correlation & & & & & \\ Significance & & & & & \\ (two-tailed) & & & & & \\ \hline Learning behavior & \multirow{2}{*}{0.306} & \multirow{2}{*}{0.518(*)} & \multirow{2}{*}{1} & \multirow{2}{*}{0.295} & \multirow{2}{*}{0.320} \\ Pearson Correlation & & & & & \\ Significance & & & & & \\ (two-tailed) & & & & & \\ \hline Learning satisfaction & \multirow{2}{*}{0.618(**)} & \multirow{2}{*}{0.568(**)} & \multirow{2}{*}{0.295} & \multirow{2}{*}{1} & \multirow{2}{*}{0.509(*)} \\ Pearson Correlation & & & & & \\ Significance & & & & & \\ (two-tailed) & & & & & \\ \hline Learning effectiveness & \multirow{2}{*}{0.822(**)} & \multirow{2}{*}{0.485(*)} & \multirow{2}{*}{0.320} & \multirow{2}{*}{0.509(*)} & \multirow{2}{*}{1} \\ Pearson Correlation & & & & & \\ Significance & & & & & \\ (two-tailed) & & & & & \\ \hline \hline \end{tabular}  
* When the significance level is 0.05 (two-tailed), the correlation is significant. ** At a significance level of 0.001 (two-tailed), the correlation is significant. Total number of exclusions = 21.  
\end{table} 
Table 7: Correlation analysis. during the path analysis, that it was the weighted value that the independent variable significantly affected the dependent variable. Moreover, the adjusted \(R^{2}\) value was used as the explanatory indicator of each dependent variable of the research model. The path analysis of the four research hypotheses is explained in the following. * Function 1: Learning attitude = \(f\) [Learning interest]--According to the ARCS theory proposed by [PERSON], the factors influencing learning interest are teaching methods and textbook design in environmental factors (referred to as \"textbook design\" in this study). Among these, it was found that the \"Learning interest\" of AR textbook design positively affected the factor of \"Learning attitude\" in the experimental group students (\(\beta\) = 0.59, \(p\) = 0.005 \(<\) 0.05, \(R^{2}\) = 0.314). The explanatory power was 31.4%, reaching a significant level; thus, H1 is valid. * Function 2: Learning behavior = \(f\) {Learning interest}--After statistical regression, \"Learning interest\" was one of the factors affecting the factor of \"Learning behavior\" (\(\beta\) = 0.518, \(p\) = 0.016 \(<\) 0.05, \(R^{2}\) = 0.23).