In the qualitative research pure induction is impossible to be the only form of data analysis approach, but several forms of research are more induction in nature than others. An inductive approach was employed, to analyse observation and interview data, although the analysis was not entirely inductive as some analytic categories were derived from the semi- structured schedules used for interviews and observation. For example, the main categories of the data were derived form the main questions included in the interviews and observation instruments. The inductive approach based on coding and categorising the data seeking for the theory that will emerge from the research strategies (Glaser & Strauss, 1967).
The main goal of data analysis, as Bassey (1999) states, is ‘an intellectual struggle with an enormous amount of raw data in order to produce a meaningful and trustworthy conclusion which is supported by a concise account of how it was reached’ (Bassey, 1999, p. 84). In this study, in order to obtain trustworthy conclusions, I have carried out the observation and interview data analysis through different stages, which were suggested by Bogdan & Biklen (1992) and Thomas, (2003). These stages were adopted as an analytical framework for data analysis of this study. The research identified several stages that qualitative researchers might go through.
1- Organising and sorting the data (interview transcripts, observation notes, and other written documents) in folders or computer files in order to access the data when starting the analysis task. In this stage similar data (i.e. interview transcripts and observation notes) are kept together and numbered to be easy to recognise when analysing the data.
2- Reading the data carefully several times, making a start of developing coding category lists and writing down any ideas or diagrams, which emerge.
3- Creating some generic codes to suit unfamiliar words or phrases which were used by participants.
4- Re-reading the data and assigning the coding categories abbreviation or numbers and choosing units of data (e.g. themes and paragraphs) and join them to the coding categories. This is a ‘test to discover the workability of the categories’ that have been created, accordingly some categories can be altered and others can be created.
The data analysis procedures of this study have followed the framework identified earlier and it went through different stages.
The first stage was transcribing interviews of the nine studied teachers, the thirty seven students and the four curriculum professionals. The transcriptions were written in Arabic language as the interviews were conducted in the Arabic language, the national language of Oman, the context of this study. I found that analysing the data as it has been given by participants will assist me to read transcriptions many times and go deeply into what has been said and done in the classroom practices and in interviews.
To transcribe the observed events and aspects that were video-tape recorded, I watched the video-cassette many times and wrote down, manually, in the observation schedule the
events related to investigated aspects of this study which, I did not take during the observation when taking notes. So there was a manual record (transcription) of the observation for each studied teacher and student.
To organise the interview data I have established folders for each group (i.e. teachers, students and curriculum professionals), each folder includes a file for each participant including his/her detailed information and a code for each person according to his/her position to be known when analysing the data. For example, PC1 is the code that was given for the first curriculum professional that I have interviewed, T1 on the other hand refers to teacher number one in first school, while P1 refers to student number one in teacher’s number one classroom. By looking at each code it was easy for me to recognise each participant, see table (4.2).
In order to generate themes from the interviews and observation transcripts, I read each single interview (9 interviews of teachers and 37 interviews of students and 4 interviews of curriculum professionals) and 9 observations schedule several times. Coding and categorising procedures were adopted to highlight the main concepts and themes of each interview and observation. During the coding stage, colouring was used to highlight the main themes by which it became easy to recognise that each colour is related to which theme in order to be able to draw a whole picture of each interview and observation (Fontana &Frey, 1994). This process involved what Miles & Huberman (1994) named as developing coding categories and generating themes.
Then sub- coding was done for each theme in the file of each group. For example, under the theme knowledge for writing two sub-categories (i.e. transcriptional and compositional
knowledge) were identified, and under each sub- category the coding identified many other categories. For instance, the sub- categories founded under compositional knowledge are vocabulary, meaning, ideas and imagination. After coding and sub- coding three new folders, for teachers, students and curriculum professionals were created to include data of each group that was organised according to the themes. For example, in the teachers’ folder all data from the nine teachers that related to the theme (knowledge for writing) were put in the same place. This is a process in which the ‘researcher takes a voluminous amount of information and reduces it to certain patterns, categories, or themes’ (Creswell, 1998, p. 145). This process was important to help me to see the ‘big picture’ (Hycner, 1985). Seeing the big picture provided me with a deeper understanding of these categories and themes and how they were related to each other. Moreover, understanding the deeper meaning of the categories and themes helped me to exclude unrelated data, bearing in mind Marshall & Rossman’s (1995) advice that ‘careful attention to how data are being reduced is necessary throughout the research endeavour’ (p. 113). However, this process was the most difficult one during the interview data analysis because it consumed a lot of time to reduce and categorise the themes under main and sub-themes.
The final stage in the data analysis process was summarising the data under each theme and interpreting it to be able to make some compressions and to find some relationships between presented information.