Process of data description

The next step in the process was data description and interpretation which was intended to support the emergence of viable research themes. The transcription of the data helps to describe data for the purpose of interpreting and then analysing it. Wolcott (1994) described the process of data analysis by introducing three terms in qualitative inquiry. These are description, interpretation and analysis. He stated that

‘description addresses the question, what is going on here?’; ‘Interpretation addresses processual questions of meanings and contexts’; ‘Analysis addresses the identification of essential features and the systematic description of interrelationships among them - in short, how things work’ (p.12). I observed the video based raw data slowly and closely, moment by moment, unfolding each of the episodes. In the light of my research questions this brought in different concepts of transcribing and describing data in the provisional stages. This was the initial exploration just to see whether they could help to illuminate what was going on. For this immersion process, I tried to work out a set of principles by thinking rather than writing. I spent hours and days characterising interactional meaning–making by the children. In order to do so, a multimodal process of transcription was required. Multimodal transcription helped me to constitute the data as descriptive resources, to refine my interpretation and analysis. In addition to video data, some descriptive account is also needed of the data obtained through my social visits. This data also required organisation and interpretation (described earlier).

Since so much of my research relevant data is video based, consisting of both visual and speech communicative modes, which involved multiple modes of communicative practices, I decided to address my video based data using multimodal transcription. This supported a rich representation of the continuous interaction between method, data analysis, and theory. Norris (2004) and Flewitt (2006) suggest that, in order to describe the nature of the video based data, multimodal transcription is required. Flewitt (2006) acknowledges that video recording produces rich data for ethnographic study although the researcher needs other supplementary methods, such as field notes and interviews.

Flewitt (2006, p.39) states that:

This multimodal matrix reveals more about the sequencing and simultaneity of speech, gaze and movement. The separate columns display how different modes operate simultaneously as interwoven rather than sequential separate elements in the discursive practices of the setting.

Flewitt acknowledges that while different modes are displayed in separate columns in the multimodal transcription they are not separate elements to consider in the context of meaning. It is also problematic for the researcher in deciding which and how many modes to include in the descriptive transcription.

I also took the precaution of checking with the children my interpreted meaning of the transcribed data of their digital practices. The stages I followed in order to transcribe the video data are presented with a small sample example in table 5.4.

Stages of transcription of video recording data:

In my study, I transcribed video data from my observations and also incorporated the participants’ views. Transcribing video data is complex as it involves multiple modes (gaze, gesture, posture, spoken language, colour, screen-based text) of communication. This multimodal transcription requires translating both visual and audio aspects of data. There is no single prescribed way to carry out this multimodal data analysis process (Flewitt et al, 2009). It is however useful to describe how I experimented and analysed video data to deal with audio and visual aspects (images, gaze, gesture, posture, symbols, and screen based text) of children’s interactions with digital technologies. This was helpful for me in understanding the process I was using to transcribe and then describe my data.

Goodwin (2001) also made the point that representing modes other than language needs multimodal analysis and, at the same time, multimodal transcriptions need to be accessible to the reader. My multimodal transcriptions are included in Appendix 3. In Appendix 3 the transcription symbols for the participants speech following: ‘..’ indicates a pause and ‘...’ indicates a long time pause (approximately 2 to 3 minutes).In Chapter 6 and 7 the transcription style used for participant speech is indicated by inverted commas and is italicised. In some cases data was in a different language, this appears in italics with an English translation following in brackets. Mixed language was also in Italics. In the appendix, different speech (not English) appears in Italics as I needed to translate it in English. Occasionally, in the speech column, non-verbal communication is described in brackets – this should not be taken for analysis or commentary (for example see table 5.6 (the child holds the DS as if it were a book). Reported field notes are indented (see section 5.1.2 as well as in Chapter 4, section 4.5.3).

I have presented in Table 5.6 below a small example to describe the process for multimodal transcription. For each transcript I used the same framework features for all modes in the video regardless of modal density (that is, the frequency or emphasis of

particular modes or actions). Stages of transcription of video recording data consist of turn, speech, screen-based action, gaze, gesture and posture.

In my study children’s screen-based communicative practices are mainly mediated by their use of computers, mobile phones and Nintendo-DSi game play. These are described in the next process of data analysis where possible themes emerged.

My main focus of the data analysis process is to observe children’s screen-based activities while using digital technologies. Therefore, the video camera positioning was mainly focused on children’s screen-based activities. It was not always possible to present visual images of the facial expressions of each of the children in the thesis. Part of the reason was my research interest was directed towards the capture of screen based activities. The digital technology mediated interactions of children were the central focus of my research.

I divided these interactions into six columns in the transcription grid presented below in table 5.6. These are turn, speech, screen-based action, gaze, gesture and posture. The first column is simply a numerical reference number of each individual activity in the video film. Each individual activity is a child’s communication act as part of the overall activity in the total event on the video recording. The next column is ‘speech’ engaged in by participants during the digital activities. The column ‘screen-based action’ describes mainly the children’s activity and performance in relation to their specific digital practices. The multimodal element of gaze relates to the child’s concentration and point of attention on the screen. Gesture was related to the signals that the child was using in order to carry out and communicate regarding their activities. ’Posture’ was to indicate that whether positioning was important to carrying out activities. I have considered these modes in order to understand the ways in which children construct meaning, in what way does this meaning contribute to children's literacy learning and how do these children learn through their use of digital technology at home?

In the context of multimodality Norris (2004.p.109) discussed modal density as ‘the number of modes utilized does not give insight into the level of attention/awareness that an individual in interaction employs to construct a specific higher- level action’. This means that modal density is not the only contributor to the level of interaction. In

my study the depth of children’s meaning-making can also be significant, regardless of its modal density. Therefore, I have not used the term ‘modal density’ in my thesis to describe children’s interaction. I used the concept of multimodality that involves a combination of images, animations, texts and sound (Jewitt, 2009; Gee, 2003; Kress 2003; Norris, 2004). This contributes to the analysis of digital data and environments within social research. This is described in greater detail in the literature review chapter in section 3.7.

The basic assumption of multimodality is that meanings are made, disseminated, interpreted and interacted through many representational and communicative modes - not only through language or writing. I looked at the construction of multimodal texts on screen created by children through their digital practices. The data analysis focused on children’s communications while playing computer games and video games and different communicative modes (language, gestures, gaze, images, written texts, music, and drawings) in relation to multimodal interaction. According to Norris (2004) a mode has no clear boundaries. Modes of communication are not a fixed set of rules because they are created through social processes. Social semiotics are an approach to communication that is associated with rules in order to understand texts as complex signs in particular social settings (Kress and Van Leeuwen, 2001; Kress, 2010). With this emphasis, a key question is how people make signs in the context of interpersonal and institutional power relations to achieve specific aims. Kress (1997; 2003; 2010) and Gee (2003) highlighted that on-screen digital practices are multimodal, involving sounds, colours, written texts, images and icons.

O’Halloran (2009) pointed out that digital technologies have a widespread scope for multimodal facilities. My study recognises how technology and multimodality relate to each other. Multimodal research has been conducted on digital practices and communication in order to theorise the nature of images, texts, on-line communication, digital narrative and literacy practices (e.g. Marsh, 2005, 2006; Lankshear and Knobel, 2003; Cope and Kalantzis, 2000; Jewitt, 2002, 2005). My research explored the ways in which children’s multimodal communicative practices have significant impact for learning through their use of digital technologies with a particular reference to South Asian families and their children.

Jewitt (2009) proposes that multimodal analysis is essential in order to understand children’s multiple modes of communication (through images, sound, and music). This is the reason I conducted multimodal analysis as a means of transcribing my video recordings. Digital technologies are also a mode of hypertext, which embeds writing, images, and sounds into layers of information on webpage or as part of game play. These presentations enable children to make meaning within the literacy learning process. I have presented an example below of multimodal transcription from a small video clip.

Table 5.6: Small example for multimodal transcription grid

Turn

Speech Screen based-

action (relates to the use of digital technology)

Gaze Gesture Posture

18th March 2012 A: This is a Nintendo DSi play. My dad brought this for me in my birthday. I am going to play Brain training. I have to hold like this way (the child hold the DS like the way open the book). P: OK, hold it the way is right to play. A: Yes, and the whole game called, ‘Dr. Quashi’ A was sitting on the floor and his concentration was on the screen for game playing.

A: He was pointing on the

screen by

using DS pen and said ‘it means brain training and how old your brain? P: Ok

He was sitting on the floor in a semi- kneeling position and opening the Nintendo DS- i screen.

I made a detailed multimodal interaction study (Norris, 2004; Jewitt, 2011) of 12 examples of children’s communicative practices through their use of computers, mobile phones and the Nintendo DSi. My data analysis process focussed on how different modes work together to create meaning in different media and how they are linked with technologically mediated worlds. I have considered embodied modes such as language, gesture and gaze, and disembodied modes such as images, written texts, music, drawings and other semiotic resources used by the children while they worked with computers or played with digital games. I worked with these modes of communication but also incorporated supplementary methods such as semi-structured interviews (Spradley, 1979) and field notes (Wolcott, 1994) in relation to the video recording. This supplementary method is useful to gather relevant information that was not captured through video recording.

Stages of data description:

Flewitt et al (2009) acknowledge that multimodal data presents a diversity of modes that requires transcription, description and analysis. This concept also supports my study in that I needed to provide an in-depth description of the examples I selected. Wolcott (1994, p.57) also pointed out that a descriptive account is required for the purpose of analysing data: ‘Whatever is to be included in a descriptive account needs to be assessed for its relevance and contribution to the story being developed’. My descriptive accounts were to describe the context and ethnographic observation and to demonstrate the cultural context for each of the examples of the video data I collected. Video observation was described together with multimodal data description. In total it aimed to show how primary themes emerged from the descriptive accounts which are now presented in Chapter 6. Following this I present an analytical discussion where I draw these examples together with the emerging sub-themes in Chapter 7. The findings and conclusions drawn on the basis of each theme are then presented in Chapter 8.

Throughout the process of dealing with data, I slowly reviewed the video clips and improved upon my strategies to identify the best possible ways of analysing the data. I reflected upon the process and learned while doing this. Dey (1993, p.78), explained that qualitative researchers ‘learn by doing’. While Cresswell (1998,p.140, 142) made the observation that ‘no consensus exists for the analysis of the forms of qualitative

data … There is no manual on how to do this; it is “custom built…”’. In my view this does not imply total freedom. Whatever analytic process is adopted, there is a need to establish credibility and terms of reference for that choice. My response to this responsibility is to make explicit the guidelines I followed in performing analysis; to address the analytic processes to be followed within those guidelines; finally to present a conceptual framework to show the relationship between my research materials and the analytic processes. The next section will explain how thematic analysis was employed in my study in order to reach viable conclusions.