Modelling choice in digital writing: functional revisions and 'texture'

Abstract

In this thesis, the digital writing practices of two 2nd year undergraduates are examined in terms of the functions and structures of their revision activity. Using systemic functional linguistics as an underlying framework, the project takes a first step toward to a dynamic description of written text in functional terms. To date, research into dynamic descriptions of language (i.e. the logogenesis, or unfolding of meaning in a text) has been almost entirely based upon data related to the spoken mode. Furthermore, research into revision activity has tended to ignore the functionality or meaning inherent in such revisions. The existing research has, instead, primarily focused on cognitive processes (for e.g., pause times) or which language structures, such as parts of speech, are more frequently involved in revisions that others. Ultimately, this thesis works toward providing a dynamic description of the language functions and revisions involved in revision activity in two student writers. To do this, it makes use of software called keystroke logging to record how two writers compose four academic essays on their computers. Such technology allows us to model the unfolding of a written text in much the same way as a tape recording allows researchers to model the unfolding of a speech. By examining how these writers revise text in light of academic expectations (a 'valued' configuration of field, tenor, and mode register variables present in language choices) and digital mediation (computer afforded composing practices), the thesis shows how certain language functions and structures may play a key role when it comes to shaping an academic essay. In this light, this thesis takes a first step to providing a dynamic description of what is usually analysed solely in synoptic terms, by showing how we can analyse written text as process (an evolving entity) rather than just a product (a static entity). Because of this, a new model of analysis – a combination of keystroke data and functional systemics – is proposed, which can provide an additional perspective to the already existing methods of examining writer behaviour by looking at meaning making practices in revision activity