Data Analysis and Representation

Regarding the analysis of the collected data obtained from the questionnaire, the data was analyzed quantitatively. However, the answers provided by the respondents to the open-ended questions were analyzed qualitatively. The qualitative analysis of the open-ended questions in the questionnaire was manually analyzed using a table in which the data was categorized according to the main constructs investigated in the questions. The frequency of some of the responses throughout the answers provided by the respondents facilitated the qualitative analysis of this particular section of the questionnaire as illustrated in a table (see Appendix 5). The data obtained from the semi-structured interviews were first transcribed and then analyzed qualitatively. The results of the administered questionnaire were entered into the Statistical Package for Social Sciences (SPSS) through which the data was analyzed quantitatively. SPSS is a reliable programme which can largely assess the educational researcher in scoring and analyzing the quantitative data quickly and accurately (Bryman & Cramer, 2001, p. 15). At this particular stage, the researcher is expected to gain an understanding of the participants’ general thoughts of challenging EAP curriculum elements. The descriptive analysis that which was generated by the SPSS as discussed by Pallant (2007) can help the researcher in describing the characteristics of the sample and to address specific research questions. For the purpose of analyzing the questionnaire, Frequencies was used to obtain the descriptive statistics for categorical items and Descriptives was used to obtain descriptive analysis for continuous variables of the questionnaire.

Creswell (2007, p. 148) provided a comprehensive conceptualization of the data analysis stage relevant to the interpretive tradition stating:

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Data analysis in qualitative research consists of preparing and organizing the data (i.e., text data as in transcripts, or image data as in photographs) for analysis, then reducing the data into themes through a process of coding and condensing the codes, and finally representing the data in figures, tables, or a discussion.

This definition provided by Creswell (2007) explains the main stages of interpreting the qualitative data obtained from semi-structured interviews which normally begins by preparing the data to make it easily accessible to the researcher and then formulating a pattern through which data can best be represented in an appropriate and explicit way. Some authors such as Agar (1980) suggested that researchers need to be familiar with the data by reading through the entire transcripts several times before breaking the data into parts or themes. This was useful for analyzing the voluminous generated data since it enables the researcher to be immersed within the data after which he/she can easily anticipate the analytic strategies and the initial categories used to represent the data.

The main elements referred to in Creswell’s explanation of the data analysis process revolve around two major concepts or sub-processes which are coding and interpretation. Creswell (2007) discussed how the interpretive researcher will ultimately be involved in a process of classifying or categorizing the emerging themes from the qualitative data. During this process, ‘Researchers develop a short list of tentative codes (e.g., 12 or so) that match text segments’ (Creswell, 2007, p. 152). It was further illustrated by Creswell how researchers may find it useful in this case to count the codes by determining ‘the frequency of occurrence’ of the codes within the passages. Although, this particular strategy can help the researchers to reduce the number of codes in the process of data analysis, it still appeared to be unreliable in this context. The process of data analysis is not meant to be linear or fixed but should be combined with the literature review. This linking scheme can help in refining the emerging codes by relating them to the main constructs which were elaborated in the literature review and will eventually help in addressing the main research questions.

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The interpretation stage takes place after the identification of the codes or themes during which the researcher ‘step back and form larger meanings of what is going on in the situations or sites’ (Creswell, 2007, p. 154). It is during this interpretation process that researchers provide their reflections on the topic in light of the views and perspectives. Walcott (1994, p. 36) depicted this interpretation process ‘at which the researcher transcends factual data and cautious analysis and begin to probe into what is to be made of them.’

In the context of this research, the qualitative data obtained from the recorded semi-structured interviews was transcribed and the researcher read through the generated data to establish a sense of familiarity with the entire transcripts. Analyzing the collected data by hand is impossible in the case of the current research due to the large amount of qualitative data. This is why the researcher opted for using the NVivo software programme to facilitate the process of data analysis (see Appendix 6). Using software programmes such as the NVivo has been encouraged by researchers because this programme ‘stores data, organizes your data, enables you to assign labels or codes to your data, and facilitates searching through the data and locating specific text or words’ (Coffey & Atkinson, 1996, p. 241).

The second level of analysis deals with processing the data by classifying it into themes and codes which can be analyzed on the basis of patterns and connections which emerge among these codes. Considering the methodological design of the research which makes use of the multiple case studies, Creswell (2007) stated the researcher is recommended to establish patterns and to search for corresponding relations between two or more categories which can be later illustrated in the form of a table. Yin (2014, p. 143) introduced a technique which can be useful for analyzing the data in the current research which he referred to as the cross-case synthesis. He suggested using a table to represent the data obtained from individual cases to provide a ‘uniform framework’. This particular illustrative design of the represented data will facilitate the task of looking for

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similarities and differences among the cases which can eventually help the researcher in developing naturalistic generalization.

It is important to refer to the data analysis strategies discussed earlier which can be representative of what some authors call coding in thematic analysis. In this form of thematic analysis, the researcher begins with developing a sense of familiarity with the data in order to establish codes. This exploratory nature is referred to as open coding and requires ‘looking in the data for codes’ (Ezzy, 2002, p. 87). This process of thematic analysis helps the researcher to identify themes and concepts derived from the data during which theory will be generated through the coding process. This is what distinguishes this form of data analysis from content analysis since thematic analysis is inductive in which the categorization scheme will highly rely on the themes and codes which are ‘induced from the data’ (Ezzy, 2002: 88). It is important when discussing the evidence of themes or categories to build up a convincing account for the readers. A number of writing strategies have been utilized in this research such as ‘conveying subthemes, or subcategories; citing specific quotes; using different sources of data to cite multiple items of evidence; and providing multiple perspectives from individuals in study to show the divergent views’ (Creswell & Plano Clark, 2011, p. 209).

A very important point to note on the qualitative data analysis is the efforts towards manual analysis and cross checking before the coding process which required extensive pre-analysis by hand. The initial analysis was started by reading through the transcripts many times and writing down the most important ideas in the transcripts which were found to be relevant to answer the research questions. After reaching a sense of familiarity with the most important ideas, the coding process was started and based on creating codes which were later assigned to respondents’ extracts from the transcribed interviews. The selection of the codes was based on their re-occurrence throughout the transcripts and their relevance to the main research questions. During the coding process, a number of themes and sub-themes began to emerge. To ensure the validity of the coding process, the emerging themes were written down along with sub-themes in a paper (see

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Appendix 9). Next, a manual analytical procedure was performed which contributed in building a logical chain of evidence and making a conceptual clarity at this particular stage. The following table 4.2 illustrates the process of coding and analyzing the interview transcripts.

Table 4.1. The Process of Analyzing and Coding Interview Transcripts

Procedures Assigning Codes to

interview Scripts

Codes Merging or Separating

themes into sub-themes

Making Conceptual Coherence Looking for Major

Themes EAP Curriculum Challenges

“It is top-down, Well, yes it affects because we are not involved in it, you just get disengaged from what is going on. You know it is very funny, I have been here three years and everyone starts coming in and they all say the same things like the things I said, and they think did anyone pay attention to this?’’ Centralized top- down leadership at CAS  Lack of teachers’ voice  Lack of communication  Resistance to change

Most EAP teachers think that the current centralized

leadership approach at CAS has given rise to many EAP curriculum challenges at the CAS collages. The current leadership approach does not involve teachers and therefore obstructs the establishment of a successful process of curriculum development. EAP Curriculum Challenges

‘’I think teachers should play a major role in curriculum development then comes the students who can to some degree speak about their specific needs in the classrooms.”

Curriculum Planning Related Challenges  Issues related to assessing the learners’ needs ↓  Students’ low proficiency level  Lack of students’ motivation EAP course objectives don’t seem to address the learners’ needs nor are aligned with their linguistic proficiency. This lack of

alignment between EAP course objectives and the actual students’ needs has led to students’ lack of motivation in EAP courses.

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EAP Curriculum Challenges

‘’a lot of these textbooks are not designed for IT and Engineering. Iam trying to bridge the gap between what the students are doing and what the students are interested in at their majors and what this course has to offer because I know that these textbooks somehow meet the course objectives.”

Issues Related to the Programme Content  Teachers’ dissatisfaction with the textbooks  Inconsistent use of supplementary materials

EAP teachers are dissatisfied with the current implemented textbooks because of their lack of relevance to the students’ major disciplines. This is why most of the EAP teachers tend to use supplementary materials to fill the gap with the current textbooks.