The impact of video lecturers’ nonverbal communication on learning – An experiment on gestures and facial expressions of pedagogical agents

2022 ◽  
Vol 176 ◽  
pp. 104350
Author(s):  
Sascha Schneider ◽  
Felix Krieglstein ◽  
Maik Beege ◽  
Günter Daniel Rey
Keyword(s):  
Nonverbal Communication ◽  
Facial Expressions ◽  
Pedagogical Agents ◽  
The Impact

scholarly journals Out of Focus: Facial Feedback Manipulation Modulates Automatic Processing of Unattended Emotional Faces

2019 ◽  
Vol 31 (11) ◽  
pp. 1631-1640 ◽  
Author(s):  
Maria Kuehne ◽  
Isabelle Siwy ◽  
Tino Zaehle ◽  
Hans-Jochen Heinze ◽  
Janek S. Lobmaier
Keyword(s):  
Nonverbal Communication ◽  
Facial Expressions ◽  
Visual Detection ◽  
Automatic Processing ◽  
Detection Task ◽  
Emotional Expressions ◽  
Facial Feedback ◽  
Emotional Faces ◽  
Electrophysiological Studies ◽  
The Impact

Facial expressions provide information about an individual's intentions and emotions and are thus an important medium for nonverbal communication. Theories of embodied cognition assume that facial mimicry and resulting facial feedback plays an important role in the perception of facial emotional expressions. Although behavioral and electrophysiological studies have confirmed the influence of facial feedback on the perception of facial emotional expressions, the influence of facial feedback on the automatic processing of such stimuli is largely unexplored. The automatic processing of unattended facial expressions can be investigated by visual expression-related MMN. The expression-related MMN reflects a differential ERP of automatic detection of emotional changes elicited by rarely presented facial expressions (deviants) among frequently presented facial expressions (standards). In this study, we investigated the impact of facial feedback on the automatic processing of facial expressions. For this purpose, participants ( n = 19) performed a centrally presented visual detection task while neutral (standard), happy, and sad faces (deviants) were presented peripherally. During the task, facial feedback was manipulated by different pen holding conditions (holding the pen with teeth, lips, or nondominant hand). Our results indicate that automatic processing of facial expressions is influenced and thus dependent on the own facial feedback.

The Roles of Animated Pedagogical Agents’ Presence and Nonverbal Communication in Multimedia Learning Environments

2010 ◽  
Vol 22 (2) ◽  
pp. 61-72 ◽  
Author(s):  
Casey Frechette ◽  
Roxana Moreno
Keyword(s):  
College Students ◽  
Learning Environments ◽  
Nonverbal Communication ◽  
Facial Expressions ◽  
Pedagogical Agents ◽  
Learning College ◽  
Pedagogical Agent ◽  
Moderate Effect Size ◽  
Static Version ◽  
Moderate Effect

We examined how the presence and nonverbal communication of an animated pedagogical agent affects students’ perceptions and learning. College students learned about astronomy either without an agent’s image or with an agent under one of the following conditions: a static agent (S), an agent with deictic movements (D), an agent with facial expressions (E), or an agent with both deictic movements and facial expressions (DE). Group S outperformed group E on a comprehension test, but no other differences were found on students’ learning or perceptions. The results show that the presence of the studied agent – regardless of nonverbal abilities – did not produce at least a moderate effect size. Further, a static version of the agent was preferable to one with only facial expressions.

P.2.040 Size matters: The impact of the volume of the amygdala on its activation during the processing of facial expressions of fear

2003 ◽  
Vol 13 ◽  
pp. S296
Author(s):  
P. Shaw ◽  
K. Kucharska-Pietura ◽  
T. Russell ◽  
F. Zelaya ◽  
E. Amaro ◽  
...  
Keyword(s):  
Facial Expressions ◽  
The Impact

Spill-over of memory effect in younger and older adults : can emotional information become associated with neutral episodic details

2018 ◽  
Author(s):  
◽  
Sanchita Gargya
Keyword(s):  
Older Adults ◽  
Facial Expressions ◽  
Neutral Stimulus ◽  
Emotional Content ◽  
Memory Representation ◽  
Extensive Literature ◽  
Emotional Information ◽  
Emotional Context ◽  
Information Research ◽  
The Impact

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] An extensive literature on the influence of emotion on memory asserts that memory for emotional information is remembered better than information lacking emotional content (Kensinger, 2009; Talmi et al., 2007; for review see Hamann, 2001). While decades of research have agreed upon memory advantages for emotional versus neutral information, research studying the impact of emotion on memory for associated details has shown differential effects of emotion on associated neutral details (Erk et al., 2003; Righi et al., 2015; Steinmetz et al., 2015). Using emotional-neutral stimulus pairs, the current set of experiments present novel findings from aging perspective to systematically explore the impact of embedded emotional information on associative memory representation of associated neutral episodic memory details. To accomplish this, three experiments were conducted. In all three experiments, younger and older participants were shown three types of emotional faces (happy, sad, and neutral) along with names. The first experiment investigated whether associative instructions and repetition of face-name pairs influence and promote formation of implicit emotional face-name associations. Using intentional and incidental instructions to encode face-name associations, in Experiment 2 and 3, respectively, participants' memory for whether names, shown with different facial expressions, can trigger emotional content of a study episode in the absence of the original emotional context at test, was assessed. Results indicate that while both younger and older adults show that names are integrated better with happy facial expressions than with sad expressions, older adults fail to show a benefit for associating a name with a happy emotional expression in the absence of associative encoding instructions. Overall, these results suggest that happy facial expressions can be implicitly learnt with or spilled over to associated neutral episodic details, like names. However, this integration is accomplished by older adults only under instructions to form face-name association.

Effects of Pedagogical Agents on Students’ Mathematics Performance: A Comparison Between Two Versions

2017 ◽  
Vol 56 (5) ◽  
pp. 701-722 ◽  
Author(s):  
Rex P. Bringula ◽  
Ian Clement O. Fosgate ◽  
Neil Peter R. Garcia ◽  
Josf Luinico M. Yorobe
Keyword(s):  
Experimental Study ◽  
Facial Expression ◽  
Prior Knowledge ◽  
Facial Expressions ◽  
Mathematics Learning ◽  
Mathematics Performance ◽  
Pedagogical Agents ◽  
Pedagogical Agent ◽  
Mathematics Scores ◽  
Mathematics Problems

This experimental study investigated the effects of the use of two versions of a pedagogical agent named personal instructing agent (PIA) on the mathematics performance of students. The first version exhibits synthetic facial expressions while the second version does not exhibit facial expression (i.e., neutral facial expression). Two groups of students with the same levels of prior knowledge in mathematics utilized two different versions of PIA. The first group—the facial group—utilized a PIA that provides textual and facial expressions feedback (happy, sad, surprise, and neutral facial expressions). The second group—the nonfacial group—used the same software except that PIA only exhibited neutral facial expression. The study showed that the mathematics scores of the students in the facial group significantly improved as compared with those who are in the nonfacial group. The posttest scores of the facial group were found significantly higher than those of the nonfacial group. The study showed that PIA that exhibited synthetic facial expressions improved students’ mathematics learning. It is concluded that synthetic facial expressions and textual feedback of pedagogical agent can be utilized to help students learn to solve mathematics problems. Limitations and recommendations are also presented.

scholarly journals Facial Expression Recognition of Instructor Using Deep Features and Extreme Learning Machine

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Yusra Khalid Bhatti ◽  
Afshan Jamil ◽  
Nudrat Nida ◽  
Muhammad Haroon Yousaf ◽  
Serestina Viriri ◽  
...  
Keyword(s):  
Facial Expression ◽  
Extreme Learning Machine ◽  
Facial Expressions ◽  
Classroom Environment ◽  
Facial Expression Recognition ◽  
Parameter Tuning ◽  
Expression Recognition ◽  
Fast Learning ◽  
Learning Machine ◽  
The Impact

Classroom communication involves teacher’s behavior and student’s responses. Extensive research has been done on the analysis of student’s facial expressions, but the impact of instructor’s facial expressions is yet an unexplored area of research. Facial expression recognition has the potential to predict the impact of teacher’s emotions in a classroom environment. Intelligent assessment of instructor behavior during lecture delivery not only might improve the learning environment but also could save time and resources utilized in manual assessment strategies. To address the issue of manual assessment, we propose an instructor’s facial expression recognition approach within a classroom using a feedforward learning model. First, the face is detected from the acquired lecture videos and key frames are selected, discarding all the redundant frames for effective high-level feature extraction. Then, deep features are extracted using multiple convolution neural networks along with parameter tuning which are then fed to a classifier. For fast learning and good generalization of the algorithm, a regularized extreme learning machine (RELM) classifier is employed which classifies five different expressions of the instructor within the classroom. Experiments are conducted on a newly created instructor’s facial expression dataset in classroom environments plus three benchmark facial datasets, i.e., Cohn–Kanade, the Japanese Female Facial Expression (JAFFE) dataset, and the Facial Expression Recognition 2013 (FER2013) dataset. Furthermore, the proposed method is compared with state-of-the-art techniques, traditional classifiers, and convolutional neural models. Experimentation results indicate significant performance gain on parameters such as accuracy, F1-score, and recall.

scholarly journals The impact of gender on visual strategies underlying the discrimination of facial expressions of pain.

2019 ◽  
Vol 19 (10) ◽  
pp. 154c
Author(s):  
Camille Saumure ◽  
Marie-Pier Plouffe-Demers ◽  
Daniel Fiset ◽  
Stéphanie Cormier ◽  
Miriam Kunz ◽  
...  
Keyword(s):  
Facial Expressions ◽  
Visual Strategies ◽  
The Impact

The Role of Facial Expressions in the Art of Musical Conducting

2021 ◽  
Vol 66 (2) ◽  
pp. 247-253
Author(s):  
Aurel Muraru
Keyword(s):  
Nonverbal Communication ◽  
Facial Expressions ◽  
The Body ◽  
Large Array ◽  
Level Of Education ◽  
External Influences ◽  
Unitary System ◽  
Accurate Reflection ◽  
Entire Array

"Facial expressions can be regarded as an accurate reflection of the inner emotions people manifest towards the surrounding reality, filtered through their own emotional „strainer”. The source of these feelings lies not only in external influences, but also in a man's own thoughts, experiences, level of education and culture, as well as the degree of development of their own volitional and emotional capacities, in which muscle movements are merely just a simple mechanical means of rendering. The entire array of facial expressions acts as a unitary system which does nothing but complete the movements of the conductor's hands, filling them with meaning. We can say that this type of communication represents a way of combining the most delicate, vibrant, profound, and subtle feelings. It would be impossible to imagine that the movement of the arms, unsupported by the expression of the eyes and face or by the position of the body, were able to express a large array of emotions (joy, pain, sadness, rage, fear, surprise, or confidence) accurately and unequivocally. Keywords: facial expressions, mimicry, nonverbal communication, conductor, performance. "

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