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avoids the ‘Bad King John/Good Queen Bess’ approach to historical analysis and reporting of data. Building on the criticisms lodged at discourse analysts of having pre-empted outcomes and using data to prove this, rather than enabling the data to ‘speak for itself’, is the mistake of over quoting data or quoting data out of context or without proper explanation of context. This is a potential fault that is avoided through the ways outlined here. The potential to select phrases from the data and to not make the reader aware of their context is avoided as this research agrees that it is important to let the reader understand the wider context of the content. Antaki et al. describe this as failing as “…it leaves the text behind” (2003, p. 11), and Widdowson as “…disregard(ing) the information that is inconvenient” (1998, p. 147). This does, however present some difficulties, given the large volume of text available for analysis. If the focus of the research was a conversation analysis, it would be easier to present the transcript of the conversation, and then to carry out the analysis required. However, with so much data, it is unreasonable to expect all of it to be included in the research, or to even form an Appendix. It is agreed that it is important to let the reader view the text in its entirety and to explicitly draw on it; however doing this every time is not realistic, given the large volume of data. Instead, this project avoids the criticism of quoting and subsequently analysing out of context by including a selection of full raw data material as a sampling of the analysis that then takes place, so that common principles of analysis that have been used, in adherence to the approaches established, which also then maintains the integrity of the research (see Appendix D). In this way, the data can be seen within its discursive context, made explicit. This openness is, as Chenail points out an important step in establishing trustworthiness and reliability of data, as it “allow[s] the reader to see what they can see in the data. It is a way to ‘share the wealth’ and to invite another to continue the inquiry and conversation…” (1995, p. 2). Furthermore, this sampling of primary source (or raw) data, enables the reader to determine that a significant criticism of analysts, that “…tell-tale signs of Under-Analysis through Over-Quotation would be the small amount of analyst’s writing in proportion to the large amount of quotation…” (Antaki et al., 2003, p.11) has been avoided. False survey is another potential area that limits the integrity of analysis. As described by Antaki et al., it results in analysis that makes it easier to “…fatally…slip into treating one’s findings as if they were true of all members of the category in which one has cast one’s respondents” (2003, p. 15). False survey refers to quantifying the data analysis in ways that 96

the original source or data would not have intended. Aligned closely with this, is what Fairclough claims is important when analysing and extracting ideologies from multiple texts, that is he “…argues that ideologies can be understood only by looking at the ‘patterns and variations in the social distribution, consumption and interpretations of texts’ (p. 50), not in individual texts and the specific readings of them” (Price, 1999, p. 584). Texts need to be examined for their combined effect, not individually and/or out of context. By including concerns from those who disagree with using CDA as a rigorous research, as well as the identification of common problems faced by researchers who regularly use this approach, this section has strengthened the reasons for using of CDA within a bricolage approach which could otherwise have inadvertently led to a non-rigorous or inadequate analysis. The work of Slembrouck (2001); O’Halloran (2005); Bucholtz (2001); Toolan (1997); and Pennycook (2001) are recommended for consultation for more specific arguments for, against and in responses to criticisms about the rigorous use of this approach in research, and can be applied to educational research. 3.5 Introduction and Theoretical Framing of Visual Analysis As a wide range of approaches are used in the field of visual analysis, establishing a contextualised definition for how the term is used in this project forms this section. In particular, visual analysis is applied directly to the CDA approach taken in this project, ensuring a consistent analysis framework between written and visual analyses. To begin, the type of visual analysis conducted in this research, “…is qualitative and…focuses on each text…” (Bell, 2001, p. 15), and aligned with visual culture perspectives, framed by Mitchell (2002, p. 87) as a preferred option as “…it is less neutral than ‘visual studies,’ and commits one at the outset to a set of hypotheses that need to be tested – for example, that vision is (as we say) a ‘cultural construction,’ that is learned and cultivated, not simply given by nature…” This approach differs to other types of visual analysis, aligned with quantitative approaches, such as a purely content analysis approach. Fairclough and Wodak (1997) and Wodak (2004, 2001b) clearly designate visual analysis as an approach to CDA, and this research also adopts this perspective, with the understanding that visual representations of information are no less important than words in conveying information and meaning. Van Leeuwen describes the relationship between visual analysis and CDA as being able to “…contribute some tools for the critically analysis of the ideological dimensions of visual texts…” (Reitstaetter et al., 97

the original source or data would not have intended. Aligned closely with this, is what<br />

Fairclough claims is important when analysing and extracting ideologies from multiple texts,<br />

that is he “…argues that ideologies can be understood only by looking at the ‘patterns and<br />

variations in the social distribution, consumption and interpretations <strong>of</strong> texts’ (p. 50), not in<br />

individual texts and the specific readings <strong>of</strong> them” (Price, 1999, p. 584). Texts need to be<br />

examined for their combined effect, not individually and/or out <strong>of</strong> context.<br />

By including concerns from those who disagree with using CDA as a rigorous research, as<br />

well as the identification <strong>of</strong> common problems faced by researchers who regularly use this<br />

approach, this section has strengthened the reasons for using <strong>of</strong> CDA within a bricolage<br />

approach which could otherwise have inadvertently led to a non-rigorous or inadequate<br />

analysis. The work <strong>of</strong> Slembrouck (2001); O’Halloran (2005); Bucholtz (2001); Toolan<br />

(1997); and Pennycook (2001) are recommended for consultation for more specific<br />

arguments for, against and in responses to criticisms about the rigorous use <strong>of</strong> this approach<br />

in research, and can be applied to educational research.<br />

3.5 Introduction and Theoretical Framing <strong>of</strong> Visual Analysis<br />

As a wide range <strong>of</strong> approaches are used in the field <strong>of</strong> visual analysis, establishing a<br />

contextualised definition for how the term is used in this project forms this section. In<br />

particular, visual analysis is applied directly to the CDA approach taken in this project,<br />

ensuring a consistent analysis framework between written and visual analyses. To begin, the<br />

type <strong>of</strong> visual analysis conducted in this research, “…is qualitative and…focuses on each<br />

text…” (Bell, 2001, p. 15), and aligned with visual culture perspectives, framed by Mitchell<br />

(2002, p. 87) as a preferred option as “…it is less neutral than ‘visual studies,’ and commits<br />

one at the outset to a set <strong>of</strong> hypotheses that need to be tested – for example, that vision is (as<br />

we say) a ‘cultural construction,’ that is learned and cultivated, not simply given by nature…”<br />

This approach differs to other types <strong>of</strong> visual analysis, aligned with quantitative approaches,<br />

such as a purely content analysis approach. Fairclough and Wodak (1997) and Wodak (2004,<br />

2001b) clearly designate visual analysis as an approach to CDA, and this research also adopts<br />

this perspective, with the understanding that visual representations <strong>of</strong> information are no less<br />

important than words in conveying information and meaning. Van Leeuwen describes the<br />

relationship between visual analysis and CDA as being able to “…contribute some tools for<br />

the critically analysis <strong>of</strong> the ideological dimensions <strong>of</strong> visual texts…” (Reitstaetter et al.,<br />

97

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