Analysing university spoken interaction

Abstract

In this article, we consider how corpus linguistics (CL) and conversation analysis (CA) can be used together to provide enhanced descriptions of spoken interaction in the context of small group teaching in higher education. From our analysis of the data, we show how the two approaches can be combined in an iterative process to account for features of spoken discourse at both micro (word) and macro (text) levels. Beginning with CL and focusing largely on words and combinations of words, we then use CA to highlight pertinent interactional features. Our methodology follows an iterative process: from CL to CA, back to CL and so on. This approach to analysis provides powerful insights into the ways in which interactants establish understandings in educational settings and, in particular, highlights the inter-dependency of words, utterances and text in the co-construction of meaning.