DATA ANALYSIS AND CODING

Over the duration of the time in the research field a large amount of data was accumulated and there are differences in the literature as to how much of the data corpus should be coded. Opinions vary, with some considering that every detail that has been recorded should be considered (Lofland et al, 2004; Wolcott, 2008). There is also the danger of data overload (Miles and Huberman, 1994), but there does surface a general ambiguity in advice with the impression that it is ultimately the researcher’s decision. No matter if every minutia of the data is scrutinised, or a percentage, the coding categories, or themes emerge through the engagement with the data (Richards, 2009). Although there are also warnings of over coding by being carried away with the process (Richards, 2009). Coding is data analysis and defined as ‘tags or labels for assigning units of meaning to the descriptive or inferential information compiled during a study’ (Miles and Huberman, 1994: 56). Saldaña (2009) advises that if only what appears to be the most salient portions of data are analysed there is a risk that there might be an exclusion of some, which could later make the data more cohesive, or influence the reconsideration of some of the analytical descriptors, or findings.

With these thoughts in mind all the data were engaged with, as the volume meant that any attempt at reducing it before coding, could result in the oversight of some containing a yet to be recognised value. All the data, from both hand written sources and the transcription of the interview sound files had been word processed and although possibly an unnecessary process all of this was printed out, mainly due to a preference of initially engaging with it in hard copy.

Using a range of indicators, such as circling, highlighting and underlining anything in the text that initially emerged and appeared significant, or worthy of attention was identified. This ‘pre-coding or provisional coding’ (Layder, 1998: 54) was to indicate any ‘possibilities and potentialities’ (ibid: 56) as an initial and personally beneficial method of familiarisation with the data. These ‘important moment[s]’ (Boyatzis, 1998: 1) were the first stage of coding and this initial working through all the

data was also a very useful process for familiarising with the data again due to the time gap from when it was first recorded. From this process some initial core themes were established.

Following this all of the data was imported into NVivo software. Using NVivo, the material was studied and coded using a thematic analysis (Flick, 2009, Saldaña, 2009) based on the themes and patterns (Aronson, 1994; Miles and Huberman, 1994) that emerged from the data using an inductive approach, and also from ‘a priori’ deductive themes that were formed from the research questions. A ‘start list’ (Miles and Huberman, 1994: 58) of a priori codes can be selected from ‘theoretical or conceptual frameworks’ (Coffey and Atkinson, 1996: 32), or from research literature or other readings, such as the research questions (ibid.). There was some initial tentativeness towards the use of a priori themes, which were based on the focus of the research. There was always a risk that they could direct the focus too much and in that event, perhaps not be the most effective way of differentiating between some data. Tesch (1990) advises that categorisation systems whether they are a priori, or ones that emerge from the data will, at times, need some modification in order to render them relevant. In practice the themes were refined, rather than substantially changed.

The inductive themes were identified through the interpretive process of open and selective coding, so that the thematic units that were derived from patterns were grounded in the data but analogous across the interviews and observations. As Boyatzis (1998: 1) comments, ‘recognizing an

important moment (seeing) precedes encoding it (seeing it as something), which in turn precedes interpretation’ and succinctly adds that, ‘a good thematic code is one that captures the qualitative richness of the phenomenon’ (ibid: 31) which through the codes and categories then becomes ‘meaningful data’ (Coffey and Atkinson, 1996: 47). All these coding processes can, ‘be thought about as a way of relating our data to our ideas about these data’ (ibid: 30).

What follows is an illustration of how the data was typically approached and coded. For

convenience, all the examples apart from one interview extract are data that has been used within this thesis.

Initially, following the transcription of this part of the interview the data was read through with a focus on how students responded to their level of computer use during the timetabled sessions, and an overarching code was computer use. It was then thematically coded for different responses, for example: initial enthusiasm, boredom, duration, need for change, mundanity. Within these, the data would be scrutinised for opportunities for another level of coding. So, for Emma the duration,

mundanity and boredom resulted in demotivation, which could be as a result of a lack of support for

the affect that the duration of computer use was having on her. In NVivo 7, the qualitative data analysis software used, these would be listed using the tree node structure as child nodes, under the parent node of computer use, and also included with a parent node of perceptions of tutor and the child node of support. The advantage of NVivo in this exercise and my personal working

conditions was the collation of the corpus of data and consequently the ease of selective data retrieval from one source.

Emily: ….it was real exciting when you got to go on the computers, but now it's…

Liz: Yeah…

Emily: It's just boring.

AB: Why is that?

Emily: Cos we’re on them all the time.

Liz: Like on a Monday we're just sat on a computer all day, on a Wednesday afternoon

we're just sat on a computer all day and on a Friday -

Emma: Yeah, we're sat on a computer all day -

Liz: And we don't do anything else [Liz emphasised each of these words slowly]-

AB: And it's all day from nine 'til four -

Liz: I think that's almost too long [laughing]. Yeah...last year we used to do like in the

morning one subject and in the afternoon a different subject and like say it breaks it up a bit doesn't it ...but now we just do like the same thing ALL DAY.

AB: How do you cope with that?

Emily: I can't finish my work, I just get bored being at computers so I just stop working 'cos

I can't concentrate, or anything.

Emma: I've, I've go to the point where I can't even start working any more...so I don't

actually do anything all day.

The interview extract below was not used within the thesis itself and is an extract from an interview with Ian, a media tutor. I was hesitant about including Ian’s comments within the thesis and after some thought decided against it. I was partially letting my intimate knowledge of the context inform me, as I was aware that his thoughts towards students’ approach to their work were quite idiosyncratic.

The initial coding for this part of the interview included: literacies, skills deficit, tutor perceptions,

age categorising, unsupportive, confrontational, plagiarising, problemising, superior knowledge and putting on the spot. There was a tree node for tutors and a parent node for student academic

practices and those situated within literacies was placed within a child node of literacy standards and others with tutor support.

AB: That was one of the questions, what are their literacy skills like?

Ian: I would say that, I mean their literacy skills for some of them, I mean I'm aware that

some of them are obviously dyslexic, erhm, or dyspraxic, in some instances…erhm…but even the ones that aren't I notice a fundamental difference in the ones that are older, like the ones in their twenties compared to the ones just in their early teens, or should I say late teens, sorry, seventeen, eighteen compared to twenty three, twenty four, twenty five whatever it happens to be. There's a marked difference in the standards there but, err one particular student in question I would say, about three days ago they came to me and they told me that they got grades Bs in their English and they got a grade in their English higher than I got when I took mine and yet their standards seem absolutely appalling.

AB: Literacies is quite a broad term but how have you found their research skills?

Ian: They...again, it's all dependent on age. I've found the biggest problem they have, erhm,

some people just go and plagiarise and copy and paste, err with no understanding of what anything means…err…there was one prime example...they way I do it is I pick certain key words out, like for example they'll use words like ideology, which means err a belief system, or they'll use words like, erhm, cathartic, which is related to media violence, which is the quick release of strong suppressed emotion and I'll ask them if they understand this terminology or what does this mean, "you've written it, what does it mean?" and they'll be like "I don't really know" and I'll say "Well why do you not know?" and I'll be like, "Shall I tell you why you don't know? Because you cut and pasted it and you've got no

understanding of the material".

The section below is an extract from field notes made during a Friday afternoon in the media classroom, as used in the similarly named vignette on pages 153 to 157. The raw hand written notes were first engaged with as a pre-coding familiarity exercise and read through several times, before the utility of tidying them up by entering them into a Word document. In principle they would have been engaged with in a similar coding manner as the interview transcriptions. As these were made from observations there was also a deeper reading to identify the level of reflexivity in the notes, and the integrity of my interpretation of what I had observed and noted as occurring in the classrooms. Initially, I had coded some of the content of the notes below as students’ avoidance of coursework and being distracted by their ability to use the computers for non-coursework use. After some reflection I realised that I was not accounting for the conditions and how the students were experiencing them, and how this related to what some had commented on during interviews,

and also situating these actions within the overall duration of the session. I realised that some of the switching between YouTube videos, was not as a distraction away from studies but more to enable their continuity of engagement with the coursework and that remembering from closer observation they were in fact focusing on coursework, rather than being distracted away from it, therefore an initial code became media facilitation. For other non-educational resources, such as AutoTrader, these appeared to be used as a respite from the conditions, and I could empathise with students’ experience of the warmth of the classroom and how I was finding it hard to focus at times. My respite was a drink from my water bottle, or wiping the sweat off my face or hands, as I was uncomfortable having to sit in these conditions, although I could move around the room if needed. Initial codes were also: pattern, repetition, switching, focus, attention, digital social needs and

isolation and administration pressure for the tutor. This was later refined to administrative isolation and later opened up as a code for both the tutor and for the students, as the tutor was

isolated from their support and learning needs. I was aware that some tutors did take work home with them, so that they avoided any stressful confrontations with managers for not keeping up with their administrative expectations. This was discussed at a personal level and outside of any

research discussion, therefore these comments were not noted and recorded as informal research discussions; hence the tailoring of the code.

The room is noticeably quieter now, as everyone seems to have settled down and Bob is still focused on emails and has not checked on the students at all. Scott and Ash are sat next to each other and both are concentrating on Word documents on their screens. They both have an array of other windows open, including a social messaging application with an ongoing conversation that keeps being added to by others and Scott only occasionally types in it. It’s as if he just wants to monitor what friends are discussing. Both students, although engaged with the Word document are moving between other on-screen windows, such as unrelated websites, including AutoTrader and switching between numerous YouTube music videos. Not that the videos are intently watched, but more something to listen to through

headphones and any videos are in the periphery of their vision. There is something of a pattern that takes place, in that there will be a few minutes of focus on the assignment in Word and then the other resources that are loaded on the screen will be quickly checked and occasionally engaged with and then the focus reverts back to the coursework.