While a person's internal state might not be easily inferred through an automatic computer system, within a group, people express themselves through their interaction with others. The group members' interaction can be then helpful to understand, to certain extent, its members' affective behavior in any case toward the task at hand. In this context, a Collaborative Virtual Environment for learning represents a resourceful technology where students can interact with the environment and with each other by their graphical representation, i.e., their avatar; and all at once, each participant's action can be automatically followed. We propose the analysis of nonverbal interaction to identify affective behavior during the accomplishment of collaborative tasks, which can be extended to verbal content. An exploratory study was conducted to understand the possibilities of this approach; the results showed behavior patterns that can be associated with task-focused affective states.