Using Representations to Assess Level of Membership in a Community of Practice

Nearly every community of practice develops its own representations to support the practices of the community. For example, the community of electric circuit designers has developed circuit diagrams to represent electric circuits. Members of that community rely on such diagrams to discuss, communicate, and document what they do. Past research has established that members of a given community not only tend to interpret the community's representations in a similar way, but also tend to construct similar representations for a given problem or concept. I argue that the way in which an individual interprets and constructs the representations of a given community serves as a useful gauge of the individual's membership in the community. Drawing on cultural consensus theory, a framework developed within cognitive anthropology, I introduce an empirical method that uses the way in which individuals read and construct representations as a basis for substantiating the existence of a community, and as a basis for assessing an individual's level of membership in a community. To illustrate how the method can be applied, I present an example drawn from my own research into the use of graphical representations of algorithms (“algorithm visualizations”) in computer science education. If one accepts the social constructivist premise that learning amounts to becoming a fuller member of a community of practice, then the method I introduce constitutes a richer and more valid means of measuring learning than traditional knowledge testing.