## 3 Research Results
### Questionnaire Survey Results
#### 3.2.5 An Example of Regression Analyses with Y1 as the Dependent Variable

Table 12: The integrated Step 2 hierarchical regression analysis results with C1 through C3 as the control variables, one pair of (X1 and X2), (X3 and X4), and (X5 and X6) as the independent variables, and one of Y1 through Y6 as the dependent variable. (1)  
Case 1 -- with control variables C1-C3 and independent variables X1 and X2 as input:  
According to the Step 1 analysis result shown in Table 11, where the value of the change of the coefficient of determination is 0.26 **, it is indicated that C1, C2, and C3 together can explain 20% of the variation of Y1 with the with f-static F(3, 66) = 5.49 and \(p\) < 0.01 (indicated by the two asterisks in 0.20 **). Furthermore, as indicated by the Step 2 analysis result shown in Table 12, with C1, C2, and C3 as the control variables, the inclusion of X1 and X2 increases the variance of Y1 by 18%, and this effect is very significant with f-static F(2, 64) = 9.83, \(p\) < 0.001. Specifically, X1 (with the standardized regression coefficient \(g\) = 0.07 and \(p\) = 0.50) has no significance in explaining the variance of Y1, while X2 (with \(g\) = 0.46 and \(p\) < 0.001) is _very significant_ in this aspect, and the higher the value \(g\) of X2, the higher its significance to explain the variance of Y1. In short, the user's feeling \"X2: it is easy to understand the role classification by using the system\", together with the thoughts expressed in C1 through C3 shown in Table 11 and repeated below,  
C1: I am very fond of watching the performances of traditional puppet shows;  
C2: after using the system, I understand the puppet role classification better; \begin{table}
\begin{tabular}{c c c c} \hline  & **Easy** & **Effective** & **Enjoyable** \\  & **(X1 and X2)** & **(X3 and X4)** & **(X5 and X6)** \\ \hline
**N = 70** & \(\Delta\mathbf{R}^{2}\) & \(\Delta\mathbf{R}^{2}\) & \(\Delta\mathbf{R}^{2}\) \\ \hline \multicolumn{4}{c}{**Y1 By experiencing the role play, I can learn a lot of the puppeteer’s skills.**} \\ \hline _Step 1_ & 0.20 * & 0.20 ** & 0.20 ** \\ \hline _Step 2_ & 0.18 *** & 0.10 * & 0.11 ** \\ \hline
**Total \(R^{2}\)** & 0.38 *** & 0.30 ** & 0.31 ** \\ \hline \multicolumn{4}{c}{**Y2 By experiencing the role play, I can learn many puppet characters’ narration skills.**} \\ \hline _Step 1_ & 0.20 ** & 0.20 ** & 0.20 ** \\ \hline _Step 2_ & 0.14 ** & 0.10 * & 0.15 ** \\ \hline
**Total \(R^{2}\)** & 0.34 ** & 0.30 * & 0.35 ** \\ \hline
**Y3 After experiencing the system, I can write puppetry and perform by myself.** \\ \hline _Step 1_ & 0.33 *** & 0.33 *** \\ \hline _Step 2_ & 0.03 & 0.04 & 0.14 ** \\ \hline
**Total \(R^{2}\)** & 0.36 & 0.37 & 0.47 ** \\ \hline \multicolumn{4}{c}{**Y4 The role play conducted on the system is a good set of cultural learning materials**} \\ \hline _Step 1_ & 0.25 ** & 0.25 ** & 0.25 ** \\ \hline _Step 2_ & 0.08 * & 0.12 ** & 0.05 \\ \hline
**Total \(R^{2}\)** & 0.33 * & 0.37 ** & 0.30 \\ \hline \multicolumn{4}{c}{**Y5 After using the system, I can remember the puppet characteristics and operation skills**} \\ \hline _Step 1_ & 0.25 *** & 0.25 *** & 0.25 *** \\ \hline _Step 2_ & 0.09 * & 0.10 ** & 0.15 ** \\ \hline
**Total \(R^{2}\)** & 0.34 * & 0.35 ** & 0.40 ** \\ \hline \multicolumn{4}{c}{**Y6 I will recommend my friends and family to use the system to learn puppetry**} \\ \hline _Step 1_ & 0.26 *** & 0.26 *** & 0.26 *** \\ \hline _Step 2_ & 0.07 & 0.04 & 0.06 \\ \hline
**Total \(R^{2}\)** & 0.33 & 0.30 & 0.32 \\ \hline \end{tabular} Note: * \(p\) < 0.05, ** \(p\) < 0.01, *** \(p\) < 0.001.  
\end{table} 
Table 13: The integrated data of changes of coefficient of determination \(\Delta\mathbf{R}^{2}\) of the two steps of regressions for all cases. * after using the system, I admire the puppeteer's manipulation skills, implies _very significantly_ the resulting user's experience expressed in \"Y1: by experiencing the role play, I can learn a lot of the puppeteer's skills\".