Data analysis procedure

Following the compilation of raw data, the next phase consisted of the analysis. In this section, I will explain the procedures followed.

Step 1. Organizing the corpora

As I mentioned in the previous section, the text chats I collected from the on-line interviews were saved as text documents and the oral data from the face-to-face interviews and focus group discussions were recorded and saved as audio files. These were subsequently reviewed and listened to several times.

Replaying the conversation after the session is often like listening to it for the first time: it is amazing how much the human ear and brain can miss and how the memory can distort. (Cole & Knowles, 2000, p. 91).

Thus I read and listened to all the data several times in order to first familiarize myself with the corpus and to identify the first initial extracts most related to my research questions (issues related to capital, topics linked to English).

As I have mentioned, I collected large amounts of data since there were initially ten participants, and the data of each participant includes interviews conducted on-line and face-to-face, as well as the focus group discussion. It is beyond the scope of this thesis to present every participant’s ‘story’. Selecting several representative ‘stories’

seemed more appropriate. For this reason, four participants from different family backgrounds were selected due to their commonalities with other participants to represent the main themes emerging across the data. They were Lily, who was the only one who perceived English as cultural capital; Serena, who was a ‘left-behind’

child; Ding, whose mother was disabled; and Cherry, who was the only one from the upper-class, as her parents were officers.

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Usually multiple ways are employed to gather, compose and create field texts (data collection subsets) based on studying the experiences of the participants in a narrative inquiry. Field texts can include transcripts of conversations, field notes, family stories, memory box artifacts, photographs and other texts that are composed by narrative inquirers and participants to represent aspects of their lived experience (Clandinin &

Huber, 2006). The former have been collected in this study. As well, field texts aid the inquirer to move back and forth between full involvement with participants and at the same time to gain distance from them (Clandinin & Connelly, 2000).

Step 2. Transcribing the stories

Transcribing is one of the basic steps before beginning the analysis of the research material and it is necessary phase for narrative inquiry. It was necessary to transcribe the oral chats. This was done originally in Chinese in broad transcription format (content of the conversations).

Step 3. Reading the field text corpus thoroughly

After completing the data collection stages and completing the transcriptions, I familiarized myself with the corpus again by reading the data carefully and researching the connections and meanings among the data. It was necessary to be completely familiar with all of the material before I began to analyze the data. During the reading, it was important that I ‘empty my mind’ of my own conceptualizations in order to let the data ‘speak to me’ without any barriers of preconceived notions or assumptions. This implies maintaining an open attitude towards the field text corpora without looking for personal explanations so the full significance of the field text corpora would be revealed naturally.

Step 4. Revising the research questions

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During this process, some of original research questions needed revision and new research questions emerged, based on the data. For instance, it appeared that social capital played a more important role in the process of English learning for the participants than had been anticipated and that it had an impact on whether English can convert into a valuable form of cultural capital. Thus, a new research question focused on the effect of social capital was included. Moreover, it became clear that the participants’ motivation shifted after they graduated and began to work. Thus, it was decided that an optimal way to approach their actions and attitudes towards English would be to employ the concept of ‘investment’, because their identities change across time and space. So, I added motivation and investment to my research questions to explain their effect on English learning. These changes helped me understand more clearly the way in which these young people in rural China constructed specific relationships with English language learning in relation to their perceived current and future access to certain forms of social, cultural and economic capital.

Step 5. Selecting data

While I reread the field texts, I repeated the established research questions in my mind one after another. In order to answer these questions, I had to comprehend the historical and social context of the data while selecting data related to my research questions. This process of reading is very important since it aims to hunt for the essential meanings which can be found in the data. Recurrent themes found throughout the data began to emerge with each reading and relevant topics related to the driving research questions and fragments with these themes were selected to tell the ‘stories’ of participants.

The selected themes were in relation to the subjects’ “perceived benefits” (e.g. future

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job, travel) derived from their learning investment, their intersubjective “positionings”

(e.g. identities as learners, as professionals, as family members) and the “systemic patterns of control” (e.g. Chinese education policies, university exams). These categories were derived from the proposed model by Darvin and Norton (2015, p. 42).

Figure 3. Darvin and Norton’s 2015 Model of Investment

Step 6. Translating and coding

Before translating the data, I went through all my textual data (interview transcripts, direct notes, field observations, etc.) in a systematic way. With the help of my two colleagues who hold a master’s degree in translation and interpretation (English and Chinese), all selected fragments were translated into English (see the corpus in the appendix of this document). Then the ideas, concepts and themes were coded to fit the categories according to the most frequent themes found in their narratives. In the English transcripts, T is the researcher and the participants are identified by the first two initials of their names.

IDENTITY

CAPITAL

IDEOLOGY

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In narrative inquiry, coding is a useful way for creating a conceptual frame for analyzing the material. In general, before coding, it is vital to develop the storyline of the participants. The storyline is the analytic thread that unites and integrates the major themes of the study. As my data were coded, the coding scheme was constantly refined, which meant I added to or expanded at times, or narrowed and revised the coding categories. In the analysis, when I quote the coded material to prove my points, both Chinese and English versions are provided to ensure reliability of the interpretation and coding. For the textual data from the online interviews, the capital letter ‘LOC’ are adopted and followed by the first letter of participant’s name (D refers to Ding; C refers to Cherry; S refers to Serena and L refers to Lily) as well as the date when the conversation took place. For example, LOC_L_20130612 stands for the data from the online interview with Lily on 12^th June, 2013. The data from face-to-face interviews is coded by the letters ‘LF2F’. I categorized the data according to the main theme as well as the date throughout the whole process and I used the abbreviation. Equally, the first letter of the participant’s name is employed. For instance, LF2F_S_FAM_20131129 refers to the data from the face-to-face interview of Serena whose theme is family and was taken on 29^th November, 2013. Based on the different topic of the interview, FAM refers to family; JOB refers to the theme related to their experience as well as expectation of jobs; CEL refers to their current station of English learning, IFEL refers to the influencing factors of English learning and HOB refers to their hobbies. Since there was only one focus group discussion, the letters FGD_20131216 are used to refer to the data from focus group discussion which was organized on 16^th December, 2013.

Step 7. Retelling the story

Narrative inquiry includes a process of reorganizing the basic themes or story lines based on narrative clues and reordering them to form a composite narrative frame that relates the ‘lived experience’ of each participant. Retelling the story is a challenge for

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many narrative researchers since narration should link two necessary factors: story and narrator. The different relations between them may result in different narrative contexts. I chose to simply ‘tell the story’, which means I acted as audience, placing myself outside of the story and acting as the medium for conveying the information.

So, I just recorded, then told, commented and explained their stories.

The whole process from composing the field text corpora to composing the research text is a tough and complex transition. “Dissection is an essential part of scientific method, and it is particularly tempting to disassemble people’s experience when narrative inquirers leave the field and begin analysis and interpretation at a distance from participants” (Bateson, 1989, p.10). Narrative inquiries are about autobiographies to some extent. It is easy for the researcher to shape the narrative inquiry plotlines according to the interests of the researcher’s own narrative and personal experience. A great deal of effort must be made to resist this temptation.

Connelly and Clandinin (2000) argue that the main change from the field text to the research text is that the research text is written for other researchers and the participants and it goes beyond the particularity of personal experience from the field text corpora. So it is necessary that narrative inquiry should not be limited to simply narrating the story and telling a life story, but also about constructing a theory that emerges from analyzing the narratives.