### Structural Equation Model
- Both measurement models present acceptable and positive factor loadings, signifying the direct relationship between the dimensions of each construct and the construct itself. From Table 22, it can be observed that the correlations between the error terms are low but significant, meaning that the corresponding dimensions share something in common not measured, which is indirectly picked up by the errors. In Table 23, the structural equation model presents an ideal fit in most of the key indicators, such as CMIN/DF (1.271), RMR (0.010), GFI (0.996), AGFI (0.989), NFI (0.979), RFI (0.952), IFI (0.995), TLI (0.989), and CFI (0.995), indicating that the model fits the data very well. However, parsimony indicators, such as PGFI (0.354), PRATIO (0.444), PNFI \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multicolumn{2}{c}{**Relation**} & \multicolumn{4}{c}{**Coefficient**} & **S.E.** & **C.R.** & \(p\)**-Value** \\ \cline{3-8}  & & **Estimated** & **Standardized** & & & \\ \hline F5 pd & \(\leftarrow\) & F2 & \(-\)0.184 & \(-\)0.163 & 0.029 & \(-\)6.429 & **\(\ast\ast\)** \\ \hline F5 pd & \(\leftarrow\) & F1 & 0.918 & 0.584 & 0.048 & 19.025 & **\(\ast\ast\)** \\ \hline F2 ea & \(\leftarrow\) & F2 & 0.926 & 0.726 & 0.039 & 23.892 & **\(\ast\ast\)** \\ \hline F4 ea & \(\leftarrow\) & F2 & 0.767 & 0.495 & 0.044 & 17.513 & **\(\ast\ast\)** \\ \hline F3 ea & \(\leftarrow\) & F5 pd & 0.147 & 0.133 & 0.025 & 5.767 & **\(\ast\ast\)** \\ \hline F3 ea & \(\leftarrow\) & F2 & 0.733 & 0.587 & 0.036 & 20.126 & **\(\ast\ast\)** \\ \hline F2 ea & \(\leftarrow\) & F5 pd & 0.132 & 0.117 & 0.025 & 5.361 & **\(\ast\ast\)** \\ \hline Flea & \(\leftarrow\) & F1 & 0.097 & 0.059 & 0.038 & 2.572 & 0.01 \\ \hline Flea & \(\leftarrow\) & F2 & 1.000 & 0.839 & & & \\ \hline F2 pd & \(\leftarrow\) & F1 & 1.025 & 0.595 & 0.047 & 21.699 & **\(\ast\ast\)** \\ \hline F4 pd & \(\leftarrow\) & F1 & 1.012 & 0.838 & 0.038 & 26.304 & **\(\ast\ast\)** \\ \hline F3 pd & \(\leftarrow\) & F2 ea & \(-\)0.063 & \(-\)0.073 & 0.019 & \(-\)3.387 & **\(\ast\ast\)** \\ \hline F3 pd & \(\leftarrow\) & F1 & 0.861 & 0.566 & 0.043 & 20.238 & **\(\ast\ast\)** \\ \hline F2 pd & \(\leftarrow\) & F4 ea & \(-\)0.071 & \(-\)0.089 & 0.016 & \(-\)4.403 & **\(\ast\ast\)** \\ \hline F4 pd & \(\leftarrow\) & F3 ea & \(-\)0.045 & \(-\)0.064 & 0.013 & \(-\)3.417 & **\(\ast\ast\)** \\ \hline F1 pd & \(\leftarrow\) & F1 ea & \(-\)0.065 & \(-\)0.073 & 0.020 & \(-\)3.341 & **\(\ast\ast\)** \\ \hline F1 pd & \(\leftarrow\) & F4 ea & \(-\)0.038 & \(-\)0.056 & 0.014 & \(-\)2.748 & 0.006 \\ \hline F1 pd & \(\leftarrow\) & F1 & 1.000 & 0.678 & & & \\ \hline \hline \end{tabular} Note: F1 = teaching practice in virtual environments, F1 pd = teaching interaction, F2 pd = means of co-communication, F3 pd = student collaboration, F4 pd = teaching process, F5 pd = Do-Cent support, F2 = student academic stress in virtual environments, Flea = time overload and constraints, F2 ea = interaction and participation, F3 ea = technological resources, F4 ea = distractions in the study environment.  
\end{table} 
Table 22: Covariance weights of the structural equation model of university teaching practice and academic stress of university students in virtual education. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multicolumn{2}{c}{**Covariability**} & \multicolumn{2}{c}{**Covariance**} & **Correlation** & **S.E.** & **C.R.** & \(p\)**-Value** \\ \hline e8 & \(\leftrightarrow\) & e9 & 0.061 & 0.097 & 0.019 & 3.208 & 0.001 \\ \hline e3 & \(\leftrightarrow\) & e5 & 0.028 & 0.075 & 0.011 & 2.541 & 0.011 \\ \hline \hline \end{tabular} Note: S.E. = standard error, C.R. = critical ratio.  
\end{table} 
Table 21: Structural equation modeling of university teaching practice and academic stress of university students in virtual education. (0.435), and PCFI (0.442), do not reach acceptable thresholds, suggesting that the model is somewhat complex. The Hoelter (0.05:2472) and Hoelter (0.01:3008) values indicate that the sample size is adequate for the model fit to be reliable.