Thematic Analysis

Thematic analysis was used to interpret data collected from the semi- structured interviews. This method was selected because of its flexibility in using different theoretical frameworks to explore interview data (Braun & Clarke, 2006), and such flexibility was particularly important because the interview phase in the current study was based on a pre-existing theoretical framework representing key issues outlined in the literature and in the earlier questionnaire analysis. The main goals of the interview analysis were as follows: 1) to investigate teachers’ attitude towards the inclusion of students with AD/HD-related behaviours and 2) to explore and elaborate on the key findings of the questionnaire analyses, and specifically the significant predictors of teachers’ attitudes towards inclusion. Therefore, an

analytical technique was needed that would allow the interview phase to identify themes which spoke to or expanded on the questionnaire data.

Themes or patterns within the data were identified by applying a theoretical thematic analysis; this was driven by a pre-existing theoretical framework or analytical interest in the area. This form of thematic analysis is more analyst driven and tends to present a more extensive analysis related to some aspects of the data (Braun & Clarke, 2006). One advantage of this approach is its flexibility, as it allows the researcher to establish themes in a number of ways. According to Braun and Clarke (2006), “a theme captures something important about the data in relation to the research question, and represents some level of patterned response or meaning

within the data set” (p. 82). This illustrates that the importance of a theme is not necessarily determined based on its repetitions, but rather in terms of its relevance to the research questions.

Braun and Clarke (2006) proposed a comprehensive framework for developing thematic analysis. This framework involves six basic phases: 1) establishing familiarity with the data, 2) generating initial codes, 3) searching for themes, 4) reviewing themes, 5) defining and naming themes, and 6) producing the report. These phases of analysis may seem straightforward; however, it is important to recognise that thematic analysis is not a linear process of simply moving from one phase to another; rather, it is a recursive process of moving back and forth between the phases as needed (Braun & Clarke, 2006). It is also noteworthy that the

guidelines for qualitative analysis are by no means steadfast rules; rather, guidelines that should be applied in a flexible manner to fit the research questions and data (Patton, 2002). Taking these considerations into account, Braun and Clarke’s (2006) framework was employed for the current study, as discussed in the following

subsections.

Establishing familiarity with the data

First, the interviews were conducted and transcribed in Arabic, and then key quotes were translated into English to serve as illustrations in this research. The translation of the quotes was performed by a certified translator and then reviewed by the researcher and a PhD student, who is bilingual in English and Arabic. Once the interviews were transcribed into Arabic, the researcher immersed himself in the data through repeated readings of the interview transcripts for the purpose of becoming familiar with the data at this stage. The repeated readings were conducted in an “active way”, which involved searching for meanings and patterns within the dataset

(Braun & Clarke, 2006, p. 87). During this phase, notes were taken and key ideas were formulated in order to generate the initial codes used in the next phase of analysis (Braun & Clarke, 2006; Maxwell, 2005).

Generating the initial codes

At this stage, initial codes were generated by “coding interesting features of the data in a systematic fashion across the entire data set” and “collating data relevant to each code” (Braun & Clarke, 2006, p. 87). The purpose of coding at this phase was to “fracture” (Strauss, 1987, p. 29) the data and organise them into meaningful categories (Tuckett, 2005). Such coding allowed for comparisons between ideas in the same category, as well as aiding in the development of theoretical concepts (Maxwell, 2005). During this phase, to avoid overlooking any interesting details reported by the interview participants, as many potential patterns were coded as possible. Once the data were arranged and coded with preliminary categories, the data and supplementary notes were again reviewed. In order to facilitate the process of organising the data and generating initial codes, NVivo 10 was used. This is a software program designed for coding, organising, searching, and analysing qualitative data; this was developed by Richards and Richards (1994). This phase ended with a significant number of codes, which prepared the codes for use in the next phase − searching for themes.

Searching for themes

The initial codes generated in the previous phase were utilised to identify emergent themes that were common across the data. In particular, the initial codes were divided into potential themes and all data pertaining to each potential theme were collated (Braun & Clarke, 2006). These themes were identified by applying a theoretical thematic analysis. Using this approach, the researcher read and re-read all

coded data to identify any themes related to teachers’ attitude towards the inclusion of students with AD/HD-related behaviours in regular classrooms, paying attention to key factors which emerged in the earlier questionnaire analysis, particularly the significant predictors of teachers’ attitude towards inclusion. Through this activity, the researcher developed an interest in the way these key factors played out across the data. Thus, a number of themes emerged in relation to teaching students with AD/HD-related behaviours in inclusive classrooms which might speak to, explain or support the questionnaire findings.

Reviewing the themes

The aim of this phase was to determine the accuracy and consistency of the themes using a two-step procedure. First, all of the collated extracts for each theme were read to ascertain whether they presented a coherent pattern; if not, the themes were reworked and revised until it was determined that the coded data cohered meaningfully with the distinct themes. The second step in this phase involved re- reading the dataset to verify whether the themes “worked” in relation to the data and to code any additional data within the themes that had been overlooked in the initial coding stages (Braun & Clarke, 2006, p. 91).

Defining and naming themes

During this phase, the themes were defined and refined by identifying the ‘essence’ of what the individual themes and the themes overall were about and determining which aspect of the data each theme represented. Further, a detailed analysis was conducted and written in relation to the ‘story’ told by each individual theme and how this story connects to the broader story told by the data set as a whole in relation to the research questions (Braun & Clarke, 2006, p. 92). Thus, the themes were considered separately, as well as in relation to the others. As a part of the

refinement process, the themes were again carefully reviewed to determine whether or not they involved subthemes. Subthemes can be useful for structuring a detailed theme (Braun & Clarke, 2006); thus, some subthemes were included in the current study when needed. As this phase was terminating, it started to become possible to distinguish between themes and elements that were not themes. At the final stage of this phase, the themes were given concise, punchy labels in order to give the reader an immediate idea of their scope (Braun & Clarke, 2006).

Producing the report

The sixth and final phase of thematic analysis involved writing up. Before and during this process, a number of meaningful questions were posed to stimulate further thinking about the selected themes. These questions included the following:

What does this theme mean? What are the assumptions underpinning it?

What are the implications of this theme? What conditions are likely to have

given rise to it? Why do people talk about this thing in this particular way (as

opposed to other ways)? What is the overall story the different themes reveal

about the topic? (Braun & Clarke, 2006, p. 94).

Thinking about these questions helped to clarify the main points related to each selected theme. In this phase, the themes emerging from the interview data were reported on and discussed, and vivid examples of participants’ quotes were presented to illustrate teachers’ perception concerning the inclusion of students with AD/HD- related behaviours in regular classrooms.

In summary, the data collected from eight participants in the semi-structured vignette-based interviews were analysed by using thematic analysis. This technique involved six phases: establishing familiarity with the data, generating the initial codes, searching for themes, reviewing the themes, defining and naming themes, and

mentioned analysis phases were not conducted in a linear process, but a recursive process with a constant movement back and forth between the phases as needed (Braun & Clarke, 2006).