Towards an Automated Model to Evaluate Collaboration Through Non-Verbal Interaction in Collaborative Virtual Environments

Towards an Automated Model to Evaluate Collaboration Through Non-Verbal Interaction in Collaborative Virtual Environments

Luis Casillas (University of Guadalajara, Mexico), Adriana Peña (University of Guadalajara, Mexico) and Alfredo Gutierrez (University of Guadalajara, Mexico)
DOI: 10.4018/978-1-5225-5643-5.ch068
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Virtual environments represent a helpful resource for learning and training. In their multiuser modality, Collaborative Virtual Environments (CVE) support geographical distant people to experience collaborative learning and team training; a context in which the automatic monitor of collaboration can provide valuable and in time information, either for human instructors or intelligent tutor systems, about individual and group performance. CVE enable people to share a virtual space where they interact through a graphical representation, generating nonverbal behavior such as gaze-direction or deictic gestures, a potential means to understand collaboration. This paper presents an automated model and its inference mechanisms to evaluate collaboration in CVE based on the nonverbal activity of the participants. The model is a multi-layer analysis that includes: data filtering, fuzzy classification, and rule-based inference producing high-level assessment for group collaboration.
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Nonverbal behavior has been broadly studied in the real world and for the creation of artificial behavior in robots or animation (Breazeal, Kidd, Thomaz, Hoffman, & Berlin, 2005). However, there are few studies of the nonverbal cues people display in CVE through their avatars. In some cases, the developed CVE are focused on the automatic generation and scripting of nonverbal behaviors for autonomous agents; and in others on real-time interaction of human users with the primary goal to offer a tool that allows sending basic emotional nonverbal messages.

Guye-Vuillème et al. (1998) established the importance of non-verbal communication in face-to-face interaction and its conversion to an equivalent in virtual worlds, studying the advantages and disadvantages of complex embodiments. Using their Virtual Life Network (VLNET) they presented a solution that takes into account the practical limitations of input devices and social science aspects. Back then, their work exposed virtual environments as cold, dehumanized places, and with static avatars lacking emotions; while they stand out nonverbal communication as the most efficient way to communicate emotional content. About the use of avatars, Guye-Vuillème et al., (Guye-Vuillème, Capin, Pandzic, Thalmann, & Thalmann, 1998) recognized its importance as the means for the interaction with a virtual world and sensing various attributes of it. Also, that the avatar becomes more important in CVE because in addition, the avatar has crucial functions as: perception, localization, identification, visualization of others' interest focus, visualization of others' actions, and a social representation of self through the customization of the avatar.

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