## 3 Results and Discussion
### Effectiveness Analysis
#### 3.2.2 Total Test Time  
A normality test was performed, where the total time to complete the tutorial is the variable of interest. Table 2 shows the results of the skewness and kurtosis values calculated using SPSS. Both variables (R Total Time and VR Total time) are within range.  
The KS and Shapiro-Wilk tests were used to test the normality of both variables. A p-value of less than 0.05 implies that the data are significantly different from a normal distribution. Hence, the null hypothesis for both tests--stating that data are not significantly different from a normal distribution--were rejected. Table 3 shows the normality test results for total time.  
Results from both tests (Kolmogorov-Smirnov and Shapiro-Wilk) show that there are no statistically significant differences, indicating that the data follow a normal curve. Since the total time values are normally distributed, the remaining parametric assumptions need to be met to proceed with a parametric test. These are:  
1. Research design: As discussed earlier, since the entire sample is exposed to both conditions, R and VR, the research is considered to have a within-subject design and a paired _t_-test/ANOVA is used to infer information about total time;
2. Measurement level/Nature of variable: Time is a ratio variable;
3. Assumption violation and normal distribution;
4. Normality: R Total Time and VR Total Time are normally distributed;
5. Extreme outliers: a z-squared method was performed using SPSS and no extreme outliers were detected;
6. Homogeneity of variance: a Levene test (R Total Time: \(p\) = 0.605 \(>\) 0.05; VR Total Time = 0.60 \(>\) 0.05) was conducted to test for the homogeneity of variance, showing that there is a homogeneity of variances for both variables and that a parametric test can be conducted.  
Consequently, a paired _t_-test was performed to test the following hypothesis at the 0.05 significance level:  
\[\mathrm{H_{0}}:\mu_{\mathrm{VR}}\ -\ \mu_{\mathrm{R}}\ =0\ \mathrm{versus}\ \mathrm{H_{a}}\ :\mu_{\mathrm{VR}}\ -\ \mu_{\mathrm{R}}\ \ \
eq\ 0\]  
As Table 4 shows, the paired _t_-test is associated with a statistically significant effect (_t_ = 6.944, _df_ = 29, \(p\) < 0.001). Comparing the means from both conditions ensures that the proposed VR module outperforms R in terms of the time it takes for participants to complete the tutorial. The participants took in average 7 min less to complete the entire tutorial in the VR module in comparison to the R module.  
\begin{table}
\begin{tabular}{c c c} \hline
**Dependent Variable** & **Skewness Value** & **Kurtosis Value** \\ \hline R Total Time & 0.13 & \(-\)1.30 \\ \hline VR Total Time & 0.749 & 0.639 \\ \hline \end{tabular}
\end{table}
Table 2: Skewness and Kurtosis of total time.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline  & \multicolumn{3}{c}{**Kolmogorov-Smirnov**} & \multicolumn{3}{c}{**Shapiro-Wilk**} \\ \cline{2-6}  & **Statistic** & _df_ & **Sig.** & **Statistic** & _df_ & **Sig.** \\ \hline R Total Time & 0.108 & 30 & 0.200 & 0.959 & 30 & 0.292 \\ \hline VR Total Time & 0.078 & 30 & 0.200 & 0.974 & 30 & 0.665 \\ \hline \end{tabular}
\end{table}
Table 3: Normality assumption test: Total time.