Effect of facial expressions on student’s comprehension recognition in virtual educational environments

Virtual classroom

A virtual classroom (Marco Van Der 2005) is the use of video, audio and other technology to simulate the traditional class and learning environment as closely as possible. Virtual environments may be used for a plethora of pedagogical purposes (Jelfs & Colbourn 2002) such as distance education. There is an increase in virtual schools worldwide as education mediated by computer is considered very important for the future (Russell & Holkner 2000). Virtual Education (Kurbel 2001) refers to instruction in a learning environment where teacher and student are separated by time or space, or both, and the teacher provides course content through course management applications, multimedia resources, the Internet, videoconferencing, etc. Students receive the content and communicate with the teacher via the same technologies.

The physical classroom is a physical room that must be visited at an appropriate time in order to participate in, while a virtual classroom is not physically accessed. This difference makes a virtual classroom, available to many, adaptable and flexible because of its non- physical location (Oakes 2002). Virtual classrooms tend to encourage collaborative learning (Taxen & Naeve 2002), because more information and knowledge can be gained through the interaction and involvement with virtual class members than solely through the reception of information from an instructor.

Virtual class room communication

A real classroom enables live face-to-face communication (Mohamed Sathik & Sofia 2011); many virtual classrooms aim to implement this by having regularly scheduled chat room with video conferencing interactions where students can interact with each other and the lecturer as they would in a real classroom. Hence, the classroom communication in virtual classroom is analogous to the communication in real classroom. In virtual classrooms, synchronous communication is used for learning and teaching, it has been referred as a channel of communication, which learners use to communicate with fellow class members and their lecturer (Burbles 2004; Huloria). In the classroom, lecturers and students--both consciously and unconsciously--send and receive nonverbal cues several hundred times a day (Mohamed Sathik & Sofia 2011). Lecturers should be conscious of nonverbal communication in the classroom for two basic reasons: to become better receivers of student’s messages and to gain the ability to send positive signals that support student’s learning while simultaneously becoming more skilled at avoiding negative signals that suppress their learning. It is just as important for lecturers to be good nonverbal communication senders as it is for them to be good receivers.

Facial expressions

Teacher student Interaction plays a vital role in any classroom environment (Mohamed Sathik & Sofia 2011). The impact due to communication of the face is so powerful in interaction. Faces are rich in information about individual identity, and also about mood and mental state, being accessible windows into the mechanisms governing our emotions. Studies reveal that the most expressive way humans display emotions is through facial expressions. Facial expressions are the primary source of information, next to words, in determining an individual’s internal feelings.

All people thus certainly Lecturers and students use facial expressions to form impressions of another. A study had revealed that the facial expressions of the lecturers kept the students motivated and interested during the lectures (Toby et al. 2008). A Lecturer can also use student’s facial expressions as valuable sources of feedback. While delivering a lecture, a Lecturer should use student’s expressions to determine whether or not to slow down, speed up, or in some other way modify his presentation. The basic strategy of optimizing the classroom behavior is that the teachers must have the capability to feel student’s minds changing; they must be good at observing student’s facial expression, every action and movement. This helps the Lecturers to understand their own weakness and to change it.

Lecturers should be highly skilled in understanding the emotions in order to identify the comprehension of the students from their facial expressions itself. If the Lecturers are not able to identify the significance in the facial expressions it will undermine the understanding of the students, thereby, create negative impact on student’s learning.

Momentary expressions that signal emotions include muscle movements such as raising the eyebrows, wrinkling the forehead, rolling the eyes or curling the lip (Resmana Lim & Reinders 2000). When students are feeling uncomfortable, they may have lowered brow, drawn together brow, horizontal or vertical forehead wrinkles, and have a hard time in maintaining eye contact. To be a good receiver of student messages, a lecturer must be familiar to many of the subtle nonverbal cues that their students send.

Studies have evaluated that student’s emotional states are expressed with specific behaviours that can be automatically detected (Toby et al. 2008). Detecting facial landmarks (such as position of Forehead, eyes, nose, mouth, etc.) play an important role in face recognition systems (Russell & Holkner 2000) as they act as the action units of the face, which determine the denotation behind the expressions (Jain 1999) indicated by them. Recognition of emotions from facial expressions involves the task of categorizing active and spontaneous facial expressions to extract information about the underlying emotional states.

In this study, the main hypothesis of the first step proposed that facial expression is the widely used nonverbal communication mode by the students in the classroom which in turn helps the lecturers to identify the comprehension of the students. The second step proposed that the facial expressions through the action units (Eyes, Mouth, Eyebrows and Forehead) help the lecturers to identify the involvement and comprehension of the students in the classroom during the lecture. The third step proposed that the student’s expressions are significantly correlated to their emotions that in turn identify their level of comprehension. The significance of the study was statistically interpreted.

The remainder of this paper is organized as follows. The experimental results are discussed in Section 'Experimental Results'. Conclusion and directions for future work are briefly covered in Section 'Conclusion'. The methods adopted in this paper are presented in Section 'Methods'.

Analysis: non-verbal communication

The first step of the experiment proposed that the facial expression is the widely used nonverbal communication mode by the students in the classroom which in turn helps the lecturers to identify the comprehension of the students. To prove the effectiveness, student’s expressions that are used for non-verbal communication in virtual pedagogical environments was investigated first. It was measured using five communication variables. Figure 1 represents the frequency percent of communication variables.

Figure 1, depicts that frequency percent of ‘yes’ is very high when compared to the frequency percent of ‘No’ which infers that facial expression is the widely used nonverbal communication mode by the students in the classroom which in turn helps the lecturers to identify the comprehension of the students.

Where,

R_ij – Rank given for ith item by jith individual.

N_j – Number of items ranked by jth individual.

Table 1 clearly indicates that Facial expression is ranked high by the lectures for the frequent and effective mode of Nonverbal communication in the classroom during the lecture which helps them to interpret the level of comprehension of the students. Scores are pictorially represented in Figure 2.

Analysis: action units

The second step of the experiment proposed that the facial expressions of the action units (Eyes, Mouth, Eyebrows and Forehead) the lecturers to identify the involvement and comprehension of the students in the classroom during the lecture. The analysis made to check the effectiveness of the interpretation of student’s comprehension through facial expressions signaled by action units.

Figure 3 shows that the facial expressions indicated by the action units for expressing their comprehension of the lecture is above the average level ( >3).

Thus, the presence of positive or negative emotions of the students can help to recognize their comprehension towards the lecture with the help of their corresponding facial expressions. Other expressions are below the average which confirms the lecturer is in unpredictable state.

Table 3, shows that the measured facial expressions indicated by the action units are above the average level (25.2600 > 15) where 15 is the Testvalue. T value shows there is correlation between the students comprehension and the facial expressions. Thus the facial expressions (Eye shrink, Eye Enlarge, Mouth Widen, Lip curl, Eyebrow Raise, Eyebrow Lowered, Forehead Wrinkles) of the action units (Eyes, Mouth, Eyebrows and Forehead) helps the lecturers to identify the involvement and comprehension of the students in the classroom during the lecture.

Analysis: facial expressions

The third step proposed that the student’s expressions are significantly correlated with their emotions which in turn identify their level of comprehension. Hence, we evaluated Pearson’s correlation between the facial expressions, and the student’s emotional feelings. Correlation and Standard deviation were computed between positive emotions (comprehension) and positive expressions. Then we calculated the correlation between negative emotions (incomprehension) and negative expressions.

The significance of the association between emotions and expressions are tested using T-test and the observation is given in Table 5. Standard Error Bar in Figure 4 clearly depicts that the error value is very negligible.

Pairs	Mean	Standard deviation	Standard error mean
Positive emotion – Positive expression	2.2500	3.03640	.30364
Negative emotion – Negative expression	9.1800	2.80469	.28047

The above statistical analysis strongly suggests that facial expression is the most frequently used nonverbal communication mode used by the student in the classroom and student’s expressions are significantly correlated to their emotions, where which can help to recognize their comprehension in the lecture. In particular, the more expressive the student was more the lecturer recognizes the comprehension of the students.