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I asked for extra probing questions for many participants to gather more in-depth information or to clarify their responses. Marshall and Rossman (1989) find that interview allows for clarification and prompt follow-up omissions because of its interactive nature. Although the questions in the interview schedule provided a guide, I also asked other questions, depending on the participants’ responses, also participants could share any other ideas or information. The semi-structured interview was more a deal between the participants and me – we shared a common interest. During the full duration of the interviews, (which lasted between 45 to 75 minutes duration as shown in Table 3), depending on the information I gathered from interviewees. I collected both verbal and non-verbal data and was flexible in paraphrasing to support and to put at ease participants. Besides, I also took special care to use words that were clear and meaningful to the participants to ensure that they were clear about what was being inquired. I also allowed participants to take their time to think and reflect on the questions before answering. During the interview, although my focus was on being an excellent listener, I also took the time to observe the participants’ facial expressions and body language and took brief note of these.
I believed I could have argued any question in the interview if ever the participant was allowed sufficient time to reflect on the question and to give the answers that were required of them. I understood that the personality of the interviewer, the place of the interview, and the environment where the interview was carried out, were other reasons which could have influenced the participants. I expressed my gratitude to each participant after the interview for being part of the study. I reiterated and reassured participants about confidentiality and briefed them while I remained at their disposal for any more information they wished to know.
Immediately after each interview, I transcribed the recordings. I planned to distinguish the likenesses or differences of the transcripts, and then I listened anew to the audio recordings to substantiate their truthfulness. I observed and took all the precautions so that the recording machine worked at all times, during and after the interviews.
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describing, classifying, interpreting, and representing, and visualising. Moustakas (1994) finds analysis as some full-textual statements of the findings.
I started the data analysis with data management, and I converted the collected data into text units for analysis. For this purpose, I transcribed the sound recordings of the interviews from conversations, word-for-word, and I analysed the written transcripts using interpretive analysis.
I re-examined with the sound recordings to approve the quality of receiving high accuracy and consistency of the written translation. The data analysis of the study would lead to the research questions and ingredients of the general items.
The next step in the proceeding was for me to gain a general conscious awareness of the full information gathered during the interviews. I, therefore, read the transcripts of all participants as many times as needed before breaking them into parts to move into codes associated with the content and for arranging or classifying of the transcripts. I progressed through to scrutinised the transcripts, and I used a highlighter to mark essential phrases/sentences on the transcripts to make them more popular arguments, sentences or quotes that provided an interpretation of internship and employability.
I then uploaded the written transcripts of all participants into the Quality Data Analysis Software called “QDA Miner 4.0”. The chief role of QDA Miner was to attribute codes to the chosen text sections from the transcripts and to analyse these codes. The software placed the applicable codes associated with internship and employability in the “codes window” of the application workspace. I tagged the codes according to their respective groups. The software displayed the list of codes, recognised as the codebook and the nodes were in the form of a tree structure under which I could find associated codes. The code could be a word, a phrase, or a keyword/s. When coding for this study, I created fresh ideas and categories from the research questions and stored the coding at nodes. Nodes might be “free” in “trees.” QDA Miner allowed me to make nodes, coding them as a simple task. As I continued to work, the software made many nodes. Figure 4.1 shows an example of the tree structure as worked out by the QDA Miner software.
QDA Miner software allowed me to bring order and organisation to the data by looking for specific and identifiable codes. I worked with the “queries” command of the software to discover words in the text that showed all happenings of a unique word or phrase. I looked at the content of the source, coded by a particular collection of nodes, and a group of nodes by another group
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of nodes to form a theme. However, it is worth highlighting here that the software, in no way, contributed to the identification of themes from the codes. I had to identify the themes through a higher level of analysis. I perceived that data analysis was that of inspecting, cleaning, transforming, and creating data according to a model to identify information that could work, propose conclusions, and defending decision – making. I used the software to decide on the existence, presence, or fact of patterns having a base on coding when the condition of coding and their quality and accuracy were given by the software. I exported the analysis sheet from the QDA software to Excel Sheets where I could further analyse the data at level 2 analysis.
I moved into describing, classifying, and interpreting after having read and wrote the codes and nodes of all transcripts, and I managed the powerful arguments into bigger “units” or themes (analysis Level 2). The word “because” or other close synonyms used by participants in the interviews showed there were the possibilities to uncover themes. I classified these themes according to the views of professionals. Following this exercise, I recouped and assigned new categories of codes at a higher level. Further analysis resulted in developing the two most essential phenomena which I reported in the findings of the study in Chapter Five (Level 3). To use the results, I produced a literary work based on a text description of the “what” participants progressed through their experiences. I devised a clean word-for-word item of information typical of a class or group. Also, statements that represented in a particular field of an investigation of “how” internship experiences had happened were accepted. I further analysed the themes, memos, and fundamental ideas that I recorded. For each interview, I reviewed the re-reading transcripts, ideas, and themes critical to the research (level 1 and 2).
I moved into describing, classifying, and interpreting after having read and wrote the codes and nodes of all transcripts, and I managed the powerful arguments into bigger “units” or themes (analysis Level 2). The word “because” or other close synonyms used by participants in the interviews showed there were the possibilities to uncover themes. I classified these themes according to the views of professionals. Following this exercise, I recouped and assigned new categories of codes at a higher level. Further analysis resulted in developing the two most essential phenomena which I reported in the findings of the study in Chapter Five (Level 3). To
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Figure 4.1 The tree structure of the codebook for internship and employability.
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use the results, I produced a literary work based on a text description of the “what” participants progressed through their experiences. I devised a clean word-for-word item of information typical of a class or group. Also, statements that represented in a particular field of an investigation of “how” internship experiences had happened were accepted. I further analysed the themes, memos, and fundamental ideas that I recorded. For each interview, I reviewed the re-reading transcripts, ideas, and themes critical to the research (level 1 and 2). I described in Chapter Six, a higher thematic analysis of the topics (nodes) which contributed to the themes (the themes (level 3).
For this section, when I carried out the analysis of transcripts, viewing applicable ideas, combined with the experiences of participants in internship and employability voiced out by them in their interviews. Also, this allowed me making the collected information comprehensible by describing the consistent; I reported those facts (analysis levels 1 and 2). I used these sub- sections for the analysis of a text, and as a guide to the items of the theoretical framework, I dealt with at an earlier stage.