# Virtual Reality or Videoconferencing for Online Learning? Evidence from Comparative Meta-Analyses
## 4 Results and Discussion
### Moderator Analysis for VR-Supported Online Learning  
#### 4.2.1 Research Context in VR Studies  
One contextual consideration is class size. Regular-sized (51.4%) and small classes (48.6%) had a well-balanced distribution in the sample, as shown in Table 4. Although we \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multirow{2}{*}{\(k\)} & \multirow{2}{*}{\(g\)} & \multirow{2}{*}{\(SE\)} & \multirow{2}{*}{\(95\%\) CI} & \multicolumn{4}{c}{**Heterogeneity**} \\ \cline{5-8}  & & & & & \(Q\) & \(df\) & \(p\) & \(I^{2}\) \\ \hline Fixed & 37 & 0.819 & 0.041 & [0.738, 0.900] & \multirow{2}{*}{430.196} & \multirow{2}{*}{36} & \multirow{2}{*}{0.000} & \multirow{2}{*}{91.632\%} \\ Random & 37 & 0.913 & 0.148 & [0.624, 1.203] & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Results for the overall analysis of VR. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multirow{2}{*}{\(k\)} & \multirow{2}{*}{\(g\)} & \multirow{2}{*}{\(SE\)} & \multirow{2}{*}{\(95\%\) CI} & \multicolumn{4}{c}{**Heterogeneity**} \\ \cline{5-8}  & & & & & \(Q\) & \(df\) & \(p\) & \(I^{2}\) \\ \hline Fixed & 35 & 0.212 & 0.024 & [0.164, 0.260] & \multirow{2}{*}{245.828} & \multirow{2}{*}{34} & \multirow{2}{*}{0.000} & \multirow{2}{*}{86.169\%} \\ Random & 35 & 0.284 & 0.071 & [0.146, 0.423] & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Results for the overall analysis of VC platforms. found that the effect size for small classes (\(g\) = 0.657) was lower than that for regular-sized classes (\(g\) = 1.181), the variance between the different sample sizes was not significant (\(Q_{B}\) = 3.399, \(p\) = 0.065). This suggests that VR can effectively support online learning in both large and small classes. However, under certain conditions, a regular-sized class may be more conducive to improving learning outcomes. It would be valuable for future studies to explore the circumstances under which small classes can be advantageous. With respect to disciplinary domain, engineering and technology sciences were the most commonly studied disciplines (59.5%), followed by humanities and social sciences (24.3%), medical science (8.1%), and natural science (8.1%). Previous studies have shown that VR has a large effect in engineering, social sciences, and basic sciences (37), and the results of this study further confirm this tendency. The \(Q\) statistics indicated a significant difference in effect size (\(Q_{B}\) = 17.934, \(p\) < 0.001). While all four disciplines had a positive moderating impact on VR-supported online learning, natural science showed the greatest effect size (\(g\) = 4.565), followed by medical science (\(g\) = 0.818), humanities and social sciences (\(g\) = 0.689), and engineering and technology sciences (\(g\) = 0.619). The reason for this may be that research in natural science mainly deals with abstract physical phenomena and natural laws. VR can simulate and construct these phenomena and laws, thus providing learners with a more intuitive and in-depth learning experience. Notably, the effect size for VR in natural science (\(g\) = 4.565) was derived from a small number of studies (\(k\) = 3), and should therefore be interpreted with caution due to possible overestimation.