Interviews are one the main ways of collecting qualitative data for your dissertation. Qualitative data adds color and depth to your information. Moreover, it provides an insight of the participants thought process, adds context, and an individual’s perspective to your dissertation findings, making it more critical.
Researchers often find it difficult to use interviews to provide them with statistical and numerical values (i.e. quantitative data). Hence, interviews are integral to provide researchers with data involving quotes and stories from contributors directly (i.e. qualitative data), thereby, making the data more reliable and valid.
After you are done with collecting your high quality data, your next step is to organize, conceptualize and analyze interview data. Unlike quantitative data, which can be easily analyzed systematically using formulas and computer softwares, analyzing qualitative data from interviews can be a long, tiring and chaotic process. It usually involves reading through numerous pages of text-based information and notes, and sometimes listening to hours of audio. Therefore, the analysis process usually begins as soon as the data becomes available.
Approaches For Data Analysis:
There are mainly two approaches used in PhD dissertation for data analysis; namely the inductive and deductive approach.
The inductive approach is further divided into thematic analysis and narrative analysis, both of which call for an unstructured approach to research.
Thematic Content Analysis:
The most common method used in qualitative data analysis is the thematic approach. Its main purpose is to find common patterns across a data set. There is no pre-set framework in this approach and the researcher naturally recognizes familiar themes to identify any emerging patterns.
This approach revolves around making sense of your respondents’ individual stories. Analyzing different stories to perceive each story, looking for meaning and context in them is the key to this approach. It finally features and includes those aspects of the respondents’ stories that the researcher thinks will be of interest to his readers. This approach is becoming increasingly popular.
This approach is somewhat a non-qualitative data analysis approach. This is used when the researcher is not looking for an in depth knowledge and understanding of the respondents’ views and feelings. This approach, unlike the inductive approach, has a pre-determined structure and framework which will lay the foundation for further analysis.
The researcher is basically testing his already existing theories in this approach, the themes and concepts are already decided on and just applied on the data and material available for the analysis. Consequently, this approach is less time consuming and less exhausting but lacks in depth information on any given topic.
If data analysis for qualitative data is done efficiently, it increases the accuracy of data for your dissertation. However, due to the involvement of so much text and detailed answers, there are high chances of some of the data being lost, which means loss of important facts as qualitative data is being directed from the source to your dissertation paper. It is because of this problem that transcribing an interview holds immense importance to reduce bias and maintain the integrity of your data.
Transcribe and Record Interviews:
Recording an interview is one of the most popular ways to overcome the issues of inaccuracies and data loss. Recording an interview is not only easier than taking first hand notes and relying on your memory to recall important aspects of the interview, but it also gives the respondents more margin to be at ease and answer questions without having the added pressure to wait for the interviewer to finish writing his notes before answering the next question. Hence, increasing the reliability of their answers consequently increase the worth of your dissertation.
Your recording technique may vary depending on whether the interview is taking place in person or over video or audio call. You may record just the audio or may even record video, as you please. Make sure your recording device is reliable so they can be easily transcribed. With advancements in technology, phone calls and Zoom sessions are becoming an increasingly popular way to conduct an interview, thus, increasing the ease with which they can be recorded and transcribed.
Transcription can be a tiring process if done manually. It may add unnecessary days to your dissertation. It may be difficult to pick out some accents and muffled voices, hence, using transcription software is highly recommended for the purpose.
Familiarize Yourself With The Data:
Since a lot of in depth responses are taken to analyze interview data, not only is recording and organizing your data a hassle but becoming acquainted with the data is also quite a task. Most of the data will be in narrative form, which means that the researcher will have to go through the data repeatedly, more than once, to recognize familiar themes and patterns. Thorough reading of the transcripts will help you hold on to important information.
At this point, you can also annotate your transcript to help analyze interview data further. Annotation involves labeling relevant words, phrases, sentences, and sections with codes. These codes assist in recognizing qualitative data types and patterns.
Conceptualize Your Data:
Once you have assigned codes to your data during annotation, you can group these codes further to create categories and sub categories, which is known as conceptualizing your data. At this point, it is up to you to merge certain codes and to get rid of others altogether, you may only keep the codes you think will be appropriate when analyzing your data. You can also get British dissertation help at this step.
Recognize Patterns And Connections:
After the researcher has applied codes to the data and further categorized them into categories and sub categories, the next step that he would do is to start identifying themes. They will look for patterns and answers that align with their research objectives.
To add to the validity and integrity of your PhD dissertation, it is imperative to conduct a thorough analysis to analyze interview data. At every point in your data collection, from conducting the interview to transcribing, organizing and interpreting your data, you should try your best to avoid all bias as a researcher. Only report true, actual insights of your respondents’ and not just the ones that you think go best with your hypothesis.
I think that all the above mentioned information will be enough to help you analyze interview data for a PhD dissertation. However, if you still feel stuck at any point when analyzing your data, remember to reach out to your mentor or professor and they would be happy to guide you.