# Smart Classroom Monitoring Using Novel Real-Time Facial Expression Recognition System
## 3 Results  
The study focused on analyzing the relationship between facial expressions and learning. It has been observed from the data that the facial expressions of students change frequently (in seconds) during lecture which shows that the learning and facial expressions are directly related to each other. The six selected facial expressions (dissatisfied, sadness, happiness, fear, satisfied and concentration) of 100 students were analyzed against five selected variables (duration of lecture, difficulty of subject, gender, seating position in classroom and department). The facial expressions were first analyzed against the variable \"gender\". The homogeneity of covariance matrix the ([PERSON]'s M = 135 and the \(p\) value is \(p>0.05\)) and the [PERSON]'s test for homogeneity or equality of variance for selected facial expressions where \(p<0.05\) shows the homogeneity of data. The MANOVA test was carried out for the variance of student's facial expressions for the variable \"gender\". There was a significant difference between male and female student's facial expressions when collectively considered for six selected facial expressions of students during the classroom learning. The value of Wilks' Lambda (\(\Lambda\))= 0.926, F (6,506) = 6.694, \(p<0.001\), partial \(\eta 2=0.74\). The separate ANOVA was conducted for each dependent variable, with each ANOVA evaluated at an alpha level of 0.0083 with the Bonferroni adjustments. The variables showed the following effects:  
* Happy had no significant effect, F(1,511) = 0.003, partial \(\eta 2<0.001\)
* Sad had no significant effect, F(1,511) = 4.483, partial \(\eta 2=0.009\)
* Satisfied had a significant effect, F(1,511) = 15.370, partial \(\eta 2=0.029\)
* Dissatisfied had a significant effect, F(1,511) = 23.026, partial \(\eta 2=0.43\)
* Concentration did not have a significant effect, F(1,511) = 4.176, partial \(\eta 2=0.008\)
* Fear did not have a significant effect, F(1,511) = 3.446, partial \(\eta 2=0.007\)  
Similarly, using the MANOVA to test the effect of the variable \"department\", we analyzed the five selected facial expressions mentioned above. The homogeneity of the covariance matrix (Box's M = 141 and the \(p\) value is \(p<0.05\)) and the [PERSON]'s test for homogeneity or equality of variance for selected facial expressions (multiple variables) of the students where the \(p\) value is \(p<0.05\) shows the homogeneity of the data. The value of Wilks' Lambda (\(\Lambda\)) = 0.972, F (18,1426) = 0.792, \(p=0.712\), partial \(\eta 2=0.009\) shows that there was not a significant impact of the variable \"department\" on the facial expressions of the students. The statistical analysis is shown in Table 2.  
\"Seating position\" was another selected variable. It was analyzed against selected facial expressions to determine its effect. The covariance matrix homogeneity (Box's M = 240, \(p\) < 0.05) and variance homogeneity against selected facial expressions shows \(p\) < 0.05 and Wilks' Lambda (\(\Lambda\)) = 0.877, F (6,506) = 11.741; \(p\) < 0.05), indicating the seating position effect on the student's facial expressions. Furthermore, the seating position was divided into three rows--first row, middle row and last row--and the facial expressions were analyzed according to row in order to clearly understand the effect by applying the MANOVA test. The students in the first row had a Wilks' Lambda (\(\Lambda\)) = 0.969, F (6,506) = 2.681; \(p\) < 0.05, partial \(\eta\)2 = 0.031 and after applying ANOVA for each variable the \(p\) < 0.05, indicating a strong impact. Furthermore, in order to identify the most frequent facial expressions among the students sitting in the front row, the mean and standard deviation were focused there and showed that those students displayed satisfaction, concentration and happiness. The results are given in the Table 3.  
The ANOVA conducted for students sitting in the middle row shows that students sitting there were satisfied, as shown in Table 4.