This section presents the approach employed for analysis of data generated from research instruments: the interviews and classroom observations. This study employed three elements of data analysis and interpretation for the analysis of results of both data from interviews and observations, namely: 1) stance; 2) process; and 3) categories as suggested by Freeman (1996c).
Stance is the attitude that a researcher adopts towards the participants when analyzing data (Freeman, 1996c), which can be either participatory or declarative. Whereas participatory stance allows the inclusion of participants as a co-analyst of the data, a declarative stance provides more freedom to researchers to handle the analysis without
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input given by the participants. This study employed a declarative stance instead of participatory one because no further input or intervention was sought from the participants on the research outcomes whatsoever.
Process refers to “the way in which the data analysis unfolds throughout the research process” (Freeman, 1996c, p. 371). In analyzing the data, a researcher can go about in a linear way when they progressively break down the data and continue with analyzing them before arriving at findings. A researcher can also treat the data in an iterative fashion when they break the data down, assemble meanings based on the data, and then keep returning to those meanings for verification and interpretation of findings. This study employed a mix of the two forms of processes because the data were initially categorized before being analyzed. Often the data were also revisited in order to constantly reinterpret, redefine, supplement, or revoke the available categories as well as to establish linkages between them.
The choice of the categories determines both the stance and process in the data analysis. The literature on data analysis in qualitative research commonly distinguishes between two types of categories: 1) a priori; and 2) grounded (Miles & Huberman, 1994; Strauss, 1987). Whereas a priori categories are used as a framework to organize and classify data so that findings emerging from the study are treated respective to the predetermined categories, grounded categories are developed from the data. Hence, the categories are grounded in the data themselves as the researcher restrains themselves from making prior assumptions about what may be significant data emerging from the study. Both a priori and grounded categories were employed in this study when analyzing the data emerging from the interviews and classroom observations.
4.3.1 Interviews
The analysis of the interviews was conducted in several stages. First and foremost, the data collected was transcribed in full using a transcription convention outlined by Roulston (2010) (see Appendix 8). Relevant excerpts from interviews conducted in English
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(e.g. LTE1 and LTE4) were quoted verbatim in the thesis for the purpose of the discussion of the study. On the other hand, relevant excerpts from interviews conducted in Indonesian language were highlighted and translated into English before being quoted in the thesis. In each of the interview transcriptions, information with personal identification was removed and was replaced by acronyms. This means participants in the interviews are referred to by letters according to the type of group they belong to + a number, e.g. PSET1 = interview of Primary School English Teacher no. 1. Quotations of lines from interviews are cited with a dot point and number of lines, e.g.:
259 : After teaching here... (PSET9)
Quotations in Indonesian were initially translated into English. In the thesis these quotations are shown in normal print, whereas quoted interview responses that took place in English are shown in italic.
The transcription of each interview was read meticulously several times in search for answers to the prepared questions. This means that in order to find relevant and significant data in unexpected places, answers to a particular question were searched throughout the transcript rather than in the direct answers to a particular question. This is particularly important especially because of the digressive character of responses provided by participants during interviews. In doing so, initial codes were identified in a transcription excerpt by selecting appropriate key words and associates to “open up data” (Birks & Mills, 2011, p. 95). These initial codes were then classified under broader conceptual categories in order to facilitate theoretical development in a process called focused coding (Coffey & Atkinson, 1996). The focused coding commenced as the initial coding progressed when certain sub-categories became identifiable within the data.
These sub-categories housed the existing and emerging initial codes. They were then put under scrutiny during the process of theoretical coding in order to identify core categories (Dey, 2004) that were central to the phenomenon of language teacher education policy for primary school English teachers in Indonesia. In an attempt to connect categories and to reveal supporting and challenging evidence between the categories, memos were
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written out. Memos have the function “to report data, tie different pieces of data together in a cluster” and “show that a particular piece of data is an instance of a general concept” (Miles & Huberman, 1994, p. 69). A detailed example of the coding process that shows a direct link between the raw data and final conceptual categories is available in Appendix 14.
A Computer-Assisted Qualitative Data Analysis Software (CAQDAS) package, NViVo9, was used to facilitate managing and analyzing the data. The use of CAQDAS in this study was significant because it is a useful tool to provide an effective system of storing, locating, and accessing large amounts of data (Creswell, 1998). In this study NViVo9 was used to adapt codes and categories and to facilitate data display, so that transcripts, codes, and memos could be accessed simultaneously. Initially the transcription of each interview was entered into NViVo9 and key words were selected to identify patterns of responses given by each group of participants. Constant comparisons of responses between one group of participants and another were viable through this process. This is followed by comparing the results generated from NViVo9 with the results generated from thorough readings.
Initial codes and focused codes emerging in each sub-category generated from NViVo9 were mainly used to supplement and corroborate data from thorough readings of transcripts of interviews and fieldnotes from observation sheet. Such constant comparative analysis was significant to drive theoretical sampling and the ongoing generation of data (Birks & Mills, 2011). NViVo9 was used in this study only to facilitate the analysis and was not the substitute for the hefty intellectual process required for in- depth data analysis.
The process of categorization was demanding. Not all coded data were used in the theoretical development, and certain codes unfitting into the emerging conceptual categories were removed from the analysis. On the contrary, when a large number of important codes emerged did not comfortably fit into the proposed categories the categorization structure of the study was reconsidered. As a consequence, initial codes
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were revisited and all categories were reexamined to ensure whether these categories were appropriate and relevant. This process was very time consuming and intellectually challenging, but ultimately benefitted the overall analysis of the study (Creswell, 1998).
After that several new categories were introduced, others eliminated, and others merged or renamed, in a process called focused coding. This process was necessary to ensure the relevance of all codes to the purpose and structure of the study. This process generated conceptual categories to encapsulate existing and emerging initial codes, produced 56 sub-categories (See Appendix 15). These sub-categories were then presented in tables to provide visual overview of sections of the data that includes both the codes pertaining to the categories as well as their frequency of references. In a process called theoretical coding, these sub-categories were subsequently structured into six core categories that create the structure for the five chapters of research findings that follow this present chapter. These core categories are:
-The profiles of teachers (Chapter 5) -The needs of teachers (Chapter 5)
-Pre-service education for PSETs (Chapter 6) -In-service education for PSETs (Chapter 7)
-Learning-teaching options in language teacher education for PSETs (Chapter 8) -The need for policy on language teacher education for PSETs (Chapter 9)
4.3.2 Classroom observations
Several stages were employed when analyzing the data from classroom observations. First, information relevant to the practices of teachers on particular teaching behaviors was entered into the observation scheme (See Appendix 12). The scheme was used to outline a set of a priori categories on teaching behaviors such as classroom organization, language skill integration, and teachers’ use of students’ first language. After numerous readings of fieldnotes from classroom observation, connections between the categories were then established through the writing of memos to obtain supporting and challenging evidence between categories (Bryman, 2008).
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Parallel analysis was made to compare data that yielded from the classroom observations on the pedagogical practices of teachers and the responses of the participants in the interviews. Triangulating the analysis of the data related to the practice of teachers on observable teaching behaviors was useful to depict possible discrepancies between teachers’ views on their practices as opposed to their actual pedagogical practices. Furthermore, it also helped reduce possible bias resulting from the interpretation of results when using only a single research instrument (Johnstone, 2000).