## 4 Results and Discussions
### Gender-Wise Analysis  
In this section, gender is taken as the independent variable to analyze against SE using both PR and NBR models to check whether there is an impact of gender on SE or not. Multiple experiments were performed regarding timestamps to analyze the impact between gender and engagement/non-engagement. The results of the experiments are listed in Table 8.  
The details of experiments that have a significant impact on engagement or non-engagement are explained below. Case 1: All male students are compared with all the female students with respect to engagement. **Null Hypothesis:**_Gender does not impact engagement_. For this analysis, gender is taken as an independent variable, and engagement is the dependent variable. It may be observed that the Z-value of both the PR and NBR lies under the acceptance region and rejected the null hypothesis as shown in Table 9. Therefore, it is \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Experiments** & **Independent Variable** & **Dependent Variable** & **Results** \\ \hline \multirow{3}{*}{1} & All MorningMale (1) vs. all & & & & \\  & MorningFemale (0) students with & & Gender & Engagement & No significant impact \\  & engagement & & & & \\ \hline \multirow{3}{*}{2} & All Morning(1) vs. all Evening(0) students & & & & \\  & with non-engagement & & & & \\ \hline \multirow{3}{*}{3} & All EveningMale (1) vs. all & & & & \\  & EveningFemale (0) students with & & & & \\  & engagement & & & & \\ \hline \multirow{3}{*}{4} & All EveningMale (1) vs. all & & & & \\  & EveningFemale (0) students with & & & & \\ \multicolumn{3}{c}{non-engagement} & & & & \\ \hline \multirow{3}{*}{5} & All Males (1) vs. All Females (0) with & & & & \\  & engagement & & & & \\ \hline \multirow{3}{*}{6} & All Males (1) vs. All Females (0) with & & & & \\  & non-engagement & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 7: All morning (1) vs. all evening (0) students with non-engagement. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Independent Variable** & **Dependent Variable** & **Const.** & **Coefficient** & **Std. Err** & **Z Value** & **Prob** & **Test** \\ \hline \multirow{3}{*}{Session} & \multirow{2}{*}{Engaged} & 3.447717 & 0.1011712 & 0.0417288 & 2.42 & 0.015 & PR \\  & & 3.447717 & 0.1011712 & 0.0473721 & 2.14 & 0.033 & NBR \\ \hline \hline \end{tabular}
\end{table} 
Table 8: List of experiments with respect to gender. concluded that there is an impact of gender on engagement but the negative relationship means that male students decrease their engagement as compared to female students. \[\text{Eng}=3.568-0.0985\text{ Gender} \tag{8}\]  
Case 2: All male students are also compared with all the female students with respect to non-engagement. **Null Hypothesis:**_Gender does not impact non-engagement_. In this case, gender is taken as an independent variable, and non-engagement is the dependent variable. The results reveal that there is an insignificant impact of gender on non-engagement because the z-value does lie in the acceptance region as shown in Table 10. Therefore, the null hypothesis is accepted. The generalizability of the proposed model is validated using an independent experiment. For this purpose, some clips of male and female students in the offline classroom environment were recorded and tested using the proposed model. These students were not incorporated for training or even for the testing phase of model building. Figure 9 presents one frame from the testing video through which we may observe that all students are detected, and the proposed model labeled them according to their engagement and non-engagement states. The attained average accuracy for this independent experiment on unseen data is found to be 83%, which is close to the 90% of model accuracy, so the absolute error is 7% which can be ignored. Hence, the generalizability of the proposed model is validated.