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In a Collaborative Virtual Environment (CVE) for learning, an automatic analysis of collaborative interaction is helpful, either for a human or a virtual tutor, in a number of ways: to personalize or adapt the learning activity, to supervise the apprentices’ progress, to scaffold learners or to track the students’ involvement, among others. However, this monitoring task is a challenge that demands to understand and assess the interaction in a computational mode.

The Users' Avatars Nonverbal Interaction in Collaborative Virtual Environments for Learning