Conversation Analysis Methodology

The methodology for applying CA very much reflects the dynamic nature of talk-in-interaction itself: in relying directly on the data, a CA methodology starts from a bottom up, unmotivated (i.e. where the analyst comes to the transcript with an open mind and is not constrained by a priori categories), detailed and systematic analysis of turns as they unfold. A number of handbooks provide practical guidance on carrying out CA-informed analysis (e.g., Heritage, 1997, 2004; Seedhouse, 2004; Sidnell, 2010; ten Have, 2007). The approaches are

summarised and synthesised here and can generally be found to include the following stages:

 collection of naturally occurring data (audio and/or video)

 preparation of detailed transcripts

 identification of overall structural organisation

 identification of “episodes” of talk and compilation of “collections”

 detailed analysis of phases/episodes (e.g., sequence organisation, turn construction, repair)

 comparisons (e.g., to other speech-exchange systems; to “deviant”

examples).

3.3.1 Naturally Occurring Data and Transcripts

In order to apply CA as an approach, analysts make use of transcripts of naturally occurring data. Very detailed transcripts are produced based on repeated listenings and, if practical, may even include analyst conference discussions, where a number of researchers come together to discuss their descriptions (e.g., Glenn et al., 1999). Since the transcript is the primary

resource for analysis, recording as much detail as possible is desirable. Nowadays audio can often be aided by visual recordings, allowing for the study of gaze and the use of other non-verbal artefacts (e.g., gesture). However, although this can provide for a fuller description, the use of one or a number of cameras in itself can affect the naturalness of the data and should be considered with caution (ten Have, 2007).

Nonetheless, as detailed a transcription as possible is encouraged. Jefferson (2004) produced a very detailed transcription system, which is often used as the basis for CA studies. Modified, ‘slimmed-down’ versions are also made use of, adapted to reflect the aims of specific research and practical limitations. For example, as in this research, the size of the corpus and the use of computer software for other aspects of the analysis may restrict orthographic

modifications that might reflect how something is said and annotations of word or vowel lengthening. An example of a modified system used in order to apply CA to a corpus of already transcribed data can be found in Walsh et al. (2011)

(for example, they add pause information and line numbers to specific stretches to reflect CA presentation conventions). As ten Have (2007, p. 96) says,

transcriptions are “always and necessarily selective”.

3.3.2 Identification of Patterns

CA starts with ‘unmotivated’ reading, from which can emerge specific aspects for more in-depth analysis. While an analyst will always have some purpose, this merely means not trying to impose patterns onto the data. The analysis could include overall organisational structure and “episodes” of talk, stretches of talk with a distinct pattern, that stand out. A number of examples of episode can be built into “collections”, allowing for similar patterns to be explored. During the analysis of specific aspects, comparisons to other speech-exchange systems and deviant examples (i.e. ones that do not appear to ‘fit’) might be made. Since the analysis and reporting should be evidenced in the transcripts, no a priori categories or additional contextual information is assumed: the core data should speak for itself, with all comments seen as locally relevant. Ten Have (2007, p.

31) explains that from a strict CA point of view, the perspective of others even by participants, e.g., post-event interpretations, may be just that: an

interpretation rather than evidence of actual action.

3.3.3 Limitations of Conversation Analysis

While CA’s strength lies in focussing specifically on natural data and in taking a dynamic view to understanding interactions, limitations should also be

acknowledged.

Although CA does not discount the larger context, it maintains that all relevant aspects (e.g., identity, shared knowledge) should be evident in the talk at some point; the evidence in the interaction is the only source of data for the strict CA researcher. However, there may be other layers and contextual information that might be relevant and indeed some applied or CA-informed studies do now provide additional contextual background information (see, for example, Dalton-Puffer, 2007; Mori, 2002; Morton, 2012; Peräkylä, 1997). Morton (2012), for example, notes that additional layers of information about participants may aid

understanding. Morton also notes that the pre-occupation with small, specific data sets and what can immediately be observed means it is not suited to documenting learning over time or internal cognitive processes. Beyond CA, Mercer (2008) also emphasises the importance of temporal aspects to be taken into consideration when investigating classroom learning, as learning typically progresses over time.

Requiring that the evidence be found directly in the talk, CA is a “militantly behavioural discipline” (Markee, 2007, p. 1023) in that it focusses on the manifestation of understandings through talk and actions. Although it cannot claim to show internal cognitive states or provide a comprehensive account of how learning takes place (e.g., in the case of education and language teaching), it does provide a perspective on how talk and actions may embody aspects of thought and learning and may be, in part at least, an observable indicator of learning or the application of skills (e.g., Firth & Wagner, 2007; Pekarek-Doehler, 2010).

The focus in CA is on social actions, rather than attempting any form-to-function mapping. As such, researchers are interested in what people do and how they co-construct talk but much less so on detailing language forms. That is not to say specific items are not studied. Beach (1993), for example, considers uses of

‘okay’ and Bolden (2009) looks at ‘so’ in turn openings. However, the focus is very much on situated interactional use. For an investigation of language use across collections or corpora, alternative additional approaches may need to be employed. For example, Walsh and O’Keeffe (2010) and Walsh et al. (2011) make use of Corpus Linguistics (CL) in conjunction with CA to shed light on the use of a number of linguistic items and how they are interactionally relevant.

Applying a ‘full-blown’ CA transcription system is only realistically possible with very small data sets due to the time-intensive nature of the process.

Additionally, the very detailed analysis of small data sets means findings are not generalisable. That said, by using a modified transcription system, as is the case here, and by building collections of data sets, an indication of patterns can be provided.

Notwithstanding the limitations, the benefits of using a CA-informed approach lie in the insights it can provide into how interactions develop, and how

participants respond and shape interactions to co-construct the discourse and achieve institutional aims. Examples of how this has been applied in classroom settings are provided in the next section.