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COMPUTER-MEDIATED COMMUNICATION AND CONVERSATION ANALYSIS
Vincenza Tudini and Anthony J. Liddicoat
ABSTRACT
An increasing number of researchers use Conversation Analysis (CA) methodology to
investigate interactional dimensions of Computer-Mediated Communication (CMC) and their
impact on language and learning. While there is a significant body of CA research focusing
on naturally-occurring telephone and face-to-face conversation, researchers’ attention since
the late 1990s has shifted to new contexts where communication between human beings is
mediated by computers. This entry is focused on CA research in the educational sphere,
where participants are using an additional or a foreign language. CA research on human
interaction developed robust analytical tools to identify and understand the unique
interactional resources which are available to users in technologically mediated contexts. In
particular, researchers are able to draw on previous CA research on face-to-face and
telephone interaction to explore affordances and constraints of new technologies for learning,
and how users use language to adapt to new and evolving interactional contexts. This entry
will therefore provide a brief overview of early CMC and CA research on technologically-
mediated interaction. Following this overview, major contributions where CA is
systematically applied to computer-mediated talk will be presented, focusing specifically on
findings related to language and interaction in L2 educational settings.
INTRODUCTION
An increasing number of researchers use Conversation Analysis (CA) methodology to
investigate interactional dimensions of Computer-Mediated Communication (CMC) and their
impact on language and learning. While there is a significant body of CA research focusing
on naturally-occurring telephone and face-to-face conversation, researchers’ attention since
the late 1990s has shifted to new contexts where communication between human beings is
mediated by computers. This entry is focused on CA research in the educational sphere,
where participants are using an additional or a foreign language. However, CA methodology
was originally developed in sociology in the 1960s and since then has been applied to a range
of social and institutional contexts, including educational. The introduction of CMC tools in
foreign language programs to promote connectivity and interaction between L1 and L2
language speakers also led to research interest in how interaction unfolds in new, mediated
forms of intercultural talk. CA research on human interaction developed robust analytical
tools to identify and understand the unique interactional resources which are available to
users in technologically mediated contexts. In particular, researchers are able to draw on
previous CA research on face-to-face and telephone interaction to explore affordances and
constraints of new technologies for learning, and how users use language to adapt to new and
evolving interactional contexts. This entry will therefore provide a brief overview of early
CMC and CA research on technologically-mediated interaction. Following this overview,
major contributions where CA is systematically applied to computer-mediated talk will be
presented, focusing specifically on findings related to language and interaction in L2
educational settings.
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EARLY DEVELOPMENTS
Though CA was initially conceived as an account of face-to-face interaction (Sacks, 1992),
technologically mediated human interaction was an investigative focus from the beginning in
studies of telephone talk (Schegloff, 1968, 1979). One significant aspect of Schegloff’s work
for understanding CMC was the observation that the technology itself was a constituent part
of the interaction and not merely the channel through which communication was conducted.
In the case of telephone talk, Schegloff showed that the ringing of the telephone was a key
element of the orderliness of such interactions and that telephone openings could not be
properly understood without reference to it. Thus from the beginning CA has acknowledged
that its main focus ‘talk’ needs to be more broadly understood than simply referring to oral
language use. Subsequent studies have also shown the saliency of technological systems for
understanding CMC. For example, Liddicoat (2011a) has shown that i
CA takes the starting point that human action is orderly, and orderly at all levels, and seeks to
understand how orderliness in interaction is achieved by participants through micro-analysis
of talk. In understanding orderliness in interaction, three key elements have come to hold a
central place in CA accounts of language use: turn-taking (organising participation of
interlocutors in talk), sequence organisation (organising interlocutors’ turns into coherent
actions) and repair (dealing with interactional problems as they occur) (Liddicoat, 2011b).
These elements are also relevant to the study of technologically mediated forms of
communication including both spoken (e.g voice chat) and written (e.g. text chat,) forms of
interaction. n video-conferencing it is necessary to consider not only the spoken language but
also written language and computer generated language to understand how participation is
established and enacted.
While technology permits users to talk across distances without being physically co-present,
it has also created constraints in relation to key interactional resources such as eye gaze,
facial expressions, gesture and body movements which are accessible in face-to-face talk but
unavailable or altered in mediated contexts. This is where CA researchers provided
significant first insights on technologically mediated interaction which are also relevant to
computer-mediated interactional contexts (see Schegloff, 1968; 1979). One constraint that
telephone and computer-mediated interaction have in common is that users cannot see one
another. While they are temporally co-present, they are not physically co-present, which
impacts on the ‘procedural infrastructure of interaction’ (Schegloff, 1991, p. 1338), including
sequence organization, turn-taking, repair and conversational openings. In the case of
telephone conversation openings, specific practices are deployed by users to deal with the
constraints imposed by the medium. For example, identification in telephone openings in
English is done through voice recognition, through practices that provide voice samples to
permit recognition and identification activities that show that recognition has been
established. In other languages, and in institutional contexts in English, however, explicit
self-identification practices have been adopted as part of telephone openings (e.g. Houtkoop-
Steenstra, 1991, for Dutch). In CMC, emoticons (emotion icons) have become an integral
component of text chat, given the lack of access to prosody and facial expressions in written
forms of interaction. Changes in telephone technology have introduced new possibilities for
identification (such as caller recognition) but speakers continue to need practices that
specifically attend to the consequences of technological mediation on social interaction
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(Arminen, 2005, 2006). Interactional practices will therefore continue to need to adapt to the
affordances of the media used.
Increased access and use of communication technologies in the nineties led to numerous CA
investigations on how users use language to adapt to and manage interaction in a variety of
computer-mediated contexts. CA perspectives have provided insights on how interaction and
language change according to specific interactional configurations created by different
softwares. For example, interactional features change according to whether users can see or
hear one another, or whether they are interacting with one person or in a group, as linguistic
resources vary accordingly. Online text chat, a form of mediated real-time written interaction,
was one of the first interactional contexts to be investigated from CA perspectives for a
number of reasons. Firstly, it was one of the first synchronous forms of computer-mediated
communication to become widely used in educational contexts, since its beginnings in 1970s
at the University of Illinois, where it was known as Talkomatic (Grubbs, 2004), and used both
for professional and social purposes. Secondly, researchers became interested in chat’s
apparent similarity to spoken interaction (Beauvois, 1992; Negretti, 1999), despite the fact
that users could neither see nor hear each other. The inability to hear one another in fact
added a significant further constraint when compared to telephone interaction where talk was
at least audible. This required users to interact without the interactional support of prosody
and other non-verbal cues, and rely entirely on the co-constructed written conversation to
create meaning.
Since the late nineties, CA researchers therefore began to investigate the nature of interaction
in online text chat (e.g., Garcia & Jacobs, 1999; Herring, 1999; Hutchby, 2001), to shed light
on conversational resources which are available and deployed by users in a unique
interactional environment. Garcia and Jacobs’ (1999) ground breaking study on turn-taking in
group chat identified unique features of text chat, such as the quasi-synchronous nature of
interaction whereby users’ composition processes and systemic constraints delay the
appearance of posts on screen. The features of the composition of language in chat had
consequences for the orderliness of interactions, because users are unable to access
composition processes and are technically unable to monitor for transition-relevance places
(TRP) for the purpose of turn-taking, and posts may not appear where the user intended.
Furthermore, the authors note that users treat each post on screen as a signal that a next post
is due. This creates problems for understanding processes of next speaker selection which
leads to increased addressivity in group chat where a post is intended for a specific user. This
promotes understanding and avoids the creation of ‘phantom’ adjacency pairs (Garcia &
Jacobs, 1999), where users construct adjacency pairs that are not intended as such.
Herring (1999) also observes that speakers’ inability to control the placement of their turns in
relation to those of others creates problems for sequence organisation though the disruption
of adjacency pairs such as question-answer pairs which in face-to-face conversation normally
follow one another (Schegloff & Sacks, 1973). Thus the sequence organisations of CMC are
potentially different from those of spoken interaction, as adjacency pairs, which are defined
in CA terms as turns “which are placed next to each in their basic minimal form” (Liddicoat,
2011b, p. 139), can no longer be understood in such a way. In fact, adjacency has to be
reconstructed by participants in the interaction through reading processes (Zemel & Cakir,
2009), rather than being a feature of its orderly design.
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Despite its significant interactional constraints, text chat was one of the first technologies to
attract the attention of teachers, especially language teachers, who began to explore possible
uses and affordances of text chat for L2 teaching and learning through interaction. For
example, L2 researchers suggested that chat could provide a bridge to face-to-face interaction
(Beauvois, 1992; Kern, 1995; Negretti, 1999 ) and greater equality of participation for shy
learners (Kern, 1995; Warschauer, 1996). Text chat was also perceived by some L2
researchers as an optimal environment for second language acquisition (Pellettieri, 2000;
Smith, 2003; Tudini, 2007) due to its visual saliency and opportunities for negotiation of
meaning, both linguistic and intercultural. The diffusion of text chat and other technologies in
educational circles eventually lead to research interest in micro-analysis of features, resources
and affordances for learning, and exploration of the unique interactional aspects of digital
environments.
MAJOR CONTRIBUTIONS
Given the central objective of developing speaking skills and intercultural communicative
competence in languages programs, it is unsurprising that teachers and researchers of second
language acquisition began experimenting with possibilities for interaction and learning
offered by CMC. Connectivity of language learners with expert speakers of the target
language was an especially promising feature of CMC in countries that are geographically
distant from the target language and culture. However most CMC research to date has
focused on what affordances are provided by CMC for language acquisition, and there is
currently little work which examines the interactional features of online conversations,
whether text, voice or video, between L1 and L2 speakers. Kern and Liddicoat (2008) point
out that language learners need opportunities to engage in interaction if they are to become
participants in communities of use and develop their capacity to communicate in and through
the target language. Technologically-mediated interactions are clearly an opportunity for
language use and participation in communities of use, however they require further micro-
analytic investigation based on previous CA work on face-to-face interaction between L1 and
L2 speakers (eg. Kasper, 2004; Markee, 2000).
Over the last fifteen years, CA has been applied to L2 contexts to “understand and explicate
how language is used as it is being acquired through interaction” (Firth &Wagner, 1997, p.
768). In addition to providing new insights on SLA processes in face-to-face contexts, Firth
and Wagner’s (1997) critique provided a major impetus for the application of CA to a range
of online L2 interaction contexts, including spoken, written, synchronous or asynchronous
modes. Unlike previous studies of online L2 learning, CA investigations adopt an emic or
participant-relevant perspective (see Firth & Wagner, 1997, for a detailed discussion) to
understand how specific technological contexts shape interaction and language learning, as
invoked by users during interaction.
One of the first CA studies of a technologically-mediated interactional context is Negretti’s
(1999) study of text chat between native and non-native speakers of English. While the
author concludes that chat promotes oral proficiency, the focus of the study is on
understanding differences between chat and face-to-face interaction. The study identified a
number of interactional resources which users deployed within the text chat environment to
ensure understanding, including sequence organization, turn taking, and adjacency pairs. The
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study also showed that sequencing and timing were dealt with differently in chat, compared
to face-to-face, with evidence of constantly disrupted or overlapping turns. While findings
echo Garcia & Jacob’s (1999) study of group chat, Negretti’s (1999) group chat study
included both group and dyadic postings. Findings might have been different if group and
dyadic interactions had been analysed separately, as interaction changes according to the type
of technological tool used, number of users and other factors. In other words, findings of
online talk investigations cannot be generalized across platforms and contexts, despite
identified interactional commonalities, as invoked by users within the ever-changing
multiplicity of platforms and technologically mediated interactional configurations.
One of the first monographs on online intercultural interaction (Tudini, 2010) focused
exclusively on dyadic text chat. This major study investigated turn-taking, adjacency pairs,
sequencing and repair in dyadic, text chat between native and non-native speakers of Italian.
However, a significant proportion of the analysis was dedicated to how different types of
conversational repair are deployed by users. CA differentiates repair according to who
initiates and resolves problems in understanding, which has implications for politeness and
face. For example, in face-to-face conversation, if a listener has a problem in understanding a
speaker’s talk, they initiate repair but give the speaker the opportunity to resolve the repair.
This is known as other-initiated self-repair, and has been shown to be preferred by speakers
over other-initiated other-repair, also known as correction (Schegloff et al., 1977). Jefferson
(1987) also showed that where correction does occur in face-to-face interaction, it is more
likely to be embedded in the topical talk rather than exposed, without disrupting the flow of
conversation and without drawing attention to the speaker’s momentary lapse. Tudini’s
(2010) study instead found that exposed other-initiated other repair was common in text chat
where participants have differential language expertise, regardless of whether there was a
problem in understanding. This was attributed to the permanency and reviewability of written
conversation, as well as the expert-novice roles and power relationships invoked by users due
to differential language expertise (see also Liddicoat & Tudini, 2012).
Tudini’s (2010) findings have implications regarding how non native speakers use and learn
languages in online dyadic text chat, as it appears that an otherwise social environment can
become a locus of language practice and pedagogical talk, which contributes to the hybridity
of text chat as both social and pedagogical interaction. The study therefore suggests that
though it is oriented to as a dispreferred action, as evidenced by use of mitigating actions
such as emoticons and positive evaluations of learners’ language, correction is perceived by
users as a way to ‘do language learning’ and pursue affiliation in written social conversation,
which may otherwise be managed differently in the rapid fade of face-to-face conversation or
voice chat.
A major CA study on spoken CMC is Jenks’ (2014) investigation of multiparty voice
conversations conducted via computer on Skype between three or more speakers of English
as an additional language. By adopting a CA perspective, this study shows how users deploy
various elements of voice as interactional resources to achieve understanding and promote
learning. For example, there is evidence that they manage turn construction and transition
through the production and coordination of vocal cues, including micro changes in intonation.
It also shows how participants use pauses to deal with overlapping utterances, though
prolonged spells of silence can lead to simultaneous talk. This leads the author to conclude
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that pauses in voice chat act both as an affordance and a constraint for learning. Jenks’
comparison of turn-taking in both text and voice chat on the Skype platform also reveals
numerous interactional differences between the two modes. For example, transition from one
turn to the next occurs in one sequential location in text chat and in multiple locations in
voice chat. Another significant finding is that background noises have interactional
consequences for the management of voice chat, as they may halt ongoing conversations or
force participants to re-establish mutual orientation. The study also identifies the specific
interactional work that is accomplished to enter an ongoing conversation, such as knowing
who to address and when to speak, an issue which is especially pertinent to multiparty
interaction.
The implications of this study’s findings are that specific interactional competencies are
required to manage interaction in multiparty voice chat, which are different to those which
are used in face-to-face or text chat contexts. This has consequences for task design in
language programs, especially since modern day language learners would benefit from
opportunities to engage with a variety of authentic interactional environments beyond the
classroom, including familiar social media platforms.
In their CA study of videogame interaction, Piirainen–Marsh and Tainio (2009) also
identified voice as a key interactional resource and affordance for learning, both of the game
activity and English as L2. In particular, co-present Finnish videogame players’ voice
repetition of game characters’ English utterances was found to be an important game and L2
learning resource through co-construction of collaborative play.
CA has also been usefully applied as single-case analysis which reflects the premise that
“social action done through talk is organized and orderly not, or not only, as a matter of rule
or as a statistical regularity, but on a case by case, action by action, basis” (Schegloff, 1987
p.102). For example, González-Lloret (2008) uses CA in a longitudinal case study of a
Spanish L2 learner engaged in text chat interaction with a L1 Spanish speaker. This study
found that repair was a key resource for participants to promote understanding of rules of
addressivity in Spanish.
WORK IN PROGRESS
While computer-mediated spoken interaction is becoming increasingly popular in language
programs, the dominant form of social interaction globally is written interaction, with
Facebook reported to be the leading social network as at August 2015 (Statista, 2015). This
platform offers users multiple interactional choices from a temporal perspective, with
asynchronous interaction as the dominant mode for one to many multiparty communication,
and quasi-synchronous for private one-to-one or small group chat. However, in these
environments users no longer rely solely on text and emoticons to interact, as occurred in
early forms of text chat described above. With the advent of Web 2.0, written interaction has
become multimodal with a variety of embedded semiotic devices, including photos and
Youtube videos, which have specific interactional functions according to recent CA research
on Facebook in Italian (Farina, 2015). For example, in his study of sequential organization of
Facebook Wall threads, Farina (2015) found that first posts were designed by users to project
multiple responses, including ‘likes’ from ‘friends’, and that these posts may be composed
with text, video and photos, on their own or in combination. Friends in fact oriented to the
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first post in a thread as the first pair part of an adjacency pair, by responding with relevant
second pair parts, and often ignored posts of other users in the thread. While this study does
not specifically deal with affordances of multimodal interaction for learning, it has learning
implications, especially for language programs, as it suggests that interactional features of
Facebook are fundamentally different from face-to-face, and need to be integrated by
teachers as a specific type of written interaction task, rather than a spoken conversational
task. CA research on multimodal multilingual written interaction, where users are using an
additional or foreign language has barely started, and is likely to have implications for
learning.
PROBLEMS AND DIFFICULTIES
The analysis of CMC using CA, in education or other settings, raises some key difficulties at
both a conceptual and analytic level that need to inform thinking about the ways interaction is
understood and analysed.
A first key problem confronting the application of CA to CMC lies in the potential mismatch
between the modalities of talk for which CA was developed and those on which it is applied.
As CA is an analytic approach designed for the study of spoken interaction, the use of written
and multimodal forms of language in online environments poses some problems for the direct
application of CA concepts and methods. One key problem for using CA to understand
interaction in written interactions is the idea of turn construction. In conventional CA
understandings, turn construction and turn-taking are based on projections of possible
completion, but in written environments, this is not such a useful way of thinking as turns are
completed when posted (and so are actually rather than possibly complete). At the same time,
an orientation to short posts as the norm in synchronous or quasi-synchronous online
environments makes holding the floor for longer posts interactionally problematic as there is
a need to avoid long gaps between contributions, suggesting that the interactional
accomplishment of ‘incompleteness’ may be a more significant interactional issue than that
of completeness (see also Tudini, 2014).
A second key issue for CA analyses of CMC is the role of the technology itself as a frame for
the interaction and its effect on how interaction is conducted and understood. The computer
brings distal participants into quasi-co-presence, especially when the technology uses a visual
channel (e.g. Skype or video-conferencing). This creates a sense in which participants share a
context, although the reality is that participants share only a part of their own contexts with
each other – that mediated through the technology. This does not mean, however, that only
that part of the context which is mediated is pertinent to understanding the interaction.
Malinowski & Kramsch (2014) for example have argued that the computer screen “fixes the
user in disembodied, spectatorial relation to a removed ‘scene’ on the other side” (p. 159).
The question is whether a focus on this removed scene is the legitimate focus of analysis or
whether it constrains analytic possibilities.
CA has usually focused on the interaction as it unfolds for the participants and has tended to
consider features of interaction that are not available to all participants through talk as less
relevant for understanding the nature of talk in interaction. In mediated contexts, and
especially in contexts where education is a central concern, this would appear to be a
problematic analytic starting point. In mediated interaction, there are observable elements of
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the interaction that are available only to one participant, such as the composition process and
off-screen behaviours, which can be interactionally or acquisitionally salient (Suzuki, 2013).
Software is currently available that can record aspects of the interaction such as tracking key
strokes, timing of contributions or capturing on-screen activity and video-recording of
participants during interaction, which can provide further data. Some of this information is at
least partially available to recipients with software showing that one’s interlocutor is
currently composing a message. Understanding the composition process may provide
significant information about how interaction is constructed, including how adjacency
structures responses, even where adjacency itself may be split in the online representations of
the talk, how self-repair processes work, and how participants bring external resources to
bear on their language production that may be especially significant in understanding
language acquisition and use. This is not simply a case of collecting information about
interaction as developing an understanding of what information is salient for understanding
interaction that problematizes the accepted CA dichotomy between participants’ and analysts’
categories.
The technology as frame for the interaction also has effects on the representation of the
interaction that is mediated between participants. That is, the interaction on screen is not
simply perceived by participants but is constructed for them in ways that may alter what is
perceived. For example, in visually mediated interactions, eye gaze is potentially available as
part of the representation, but the way that eye gaze is mediated is not actually a ‘true’
representation. As the camera capturing the speakers’ image is not positioned at the focal
point of gaze, the participants’ gaze is misrepresented. This means that eye gaze information
is not available for participants in the same way that would be the case for co-present
interlocutors. Goodwin (1980) has shown that eye gaze plays an important role for
coordinating speakership and that participants deploy repair practices to secure appropriately
gazing participants. Research has not currently investigated the consequentiality of the
disruption of eye gaze for the nature of interaction and the interactional practices that
speakers’ deploy as a result of the disruption.
FUTURE DIRECTIONS
The use of CA to study CMC is a relatively new area of scholarly activity and there remains
much to be done.
One key area for future work will be to develop an understanding of the affordances and
constraints created by the technological mediation of talk. These constraints and affordances
exist at the interactional level and, in educational contexts, at the level of learning and there
are complex interactions between each of the levels that as yet have been little researched.
Moreover, there is a need to understand how CMC as language learning provides or limits
interactional possibilities, which in turn influence learning experiences. For example,
Balaman (2015) has used CA to show how the design of online tasks constructs interactional
possibilities that create affordances for learning.
There is also a need to understand more about the interactional (re)construction of talk
through CMC. In particular, there is a need for research on how users of written CMC
construct sequentiality when sequentiality is not directly inferable from the ordering of
contributions. In reconstructing sequences of interaction, users must orient to adjacency pairs
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to understand the interaction as a coherent activity, but we know little about how they draw
on sequence organisation as a resource for reconstructing coherence or the consequences the
need to restore sequentiality has for language learners as users of CMCs.
A third area of future research would appear to relate to the complex interactions of on-screen
and off-screen activities in the interactional processes involved in CMC. This would require a
more critical engagement with the idea of CMC talk as interaction and a reconsideration of
the saliency of “external” activities to talk. This involves more than simply studying off-
screen activities, such as the composition process, to consider how such processes are
implicated in and constituent of the interaction. This research is also relevant to
understanding the interactional complexities and concurrent interplay of on-screen, off-
screen, voice and text conversations with in-game actions of multilingual gamers, to
understand affordances for language learning within ludic environments. The impact of
mobility on talk-in-interaction, including embodied deixis during mobile augmented reality
game play (Thorne et al, 2015), adds a further dimension which is ripe for microanalytical
investigation.
CROSS-REFERENCES
See Also: Hansun Zhang Waring: Conversation Analytic Approaches to Language and
Education (Volume 10); Doris Warriner and Kate Anderson: Discourse Analysis in
Education Research (Volume 10).
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