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One of the more vexing problems in teaching fully-online classes concerns the development of community. As Rovai (2001) identified, online courses must combat feelings of isolation and impart a sense of personal and individual attention. To create a sense of belonging and togetherness, instructors typically need to surmount numerous technological hurdles inherent in online delivery, not least of which is the inescapable conclusion that the one factor most basic to the formation of community-face to face interaction-is by definition absent in an online class. Many new tech-based teaching tools have been developed in an attempt to ameliorate the digital alienation and promote interaction, such as discussion boards, synchronous chat rooms, and emerging media like wikis, blogs and podcasts, as well as virtual worlds, such as Second Life. As the frequency of interaction grows, so does the sense of belonging to a learning community (Dawson, 2008). Yet as difficult as it is to craft a community among online learners, it is even harder to measure where and when the community is functioning (and perhaps more crucially, to know when it is not). Most Learning Management Systems (LMS) usually provide crude frequency data, so instructors will know how often students are visiting pages, and perhaps reading or posting information. However, what is lacking in this less-than-dynamic system is an overview of the type, amount and direction of activity, which students' may be engaging (Mazza & Dimitrova, 2007).