Data analysis

A crossroad in research science and the use of qualitative research is inductive and deductive data analysis. The most common for qualitative researchers is to utilise inductive data analysis in order to build a theory from data that they have collected. While inductive analysis works by working towards a theory based on the data, a deductive analysis works towards the data based on a theory, which then becomes commonly found in quantitative research. Creswell & Creswell still underlines that it is very useful to work back and forth between the data and theory

– while an analysis began using an inductive method, the researcher can reflect and look for more aspects and themes in their data using their established theory, thus working deductively (Creswell & Creswell, 2018, p. 181). During the analytical work in the study, an inductive analysis was utilised to create theory based on the data collected in the study. A completely deductive analysis could not be done as there were no prior theories on the subject that could be attempted falsified. However, a combination was used during and after the analysis to confirm or reassure that they theory that was being built remained rigid.

3.4.1 Transcription

The data analysis is based on the statements by the participants. To be able to analyse the interviews, they needed to be transcribed. This was done to obtain a more structured overview of the data material and to make analysis easier. A transcription was therefore deemed necessary for further analysis of the data. For transcribing, I used InqScribe, which is a free, online program that features both an audio player and a blank paper to write. It also allowed the audio file to be either slowed down or sped up for easier workflow, and using integrated hotkeys, pausing and rewinding was done easily. During the transcription, the participants were anonymised by being given a number instead of their name, including myself. This would not only follow the contractual guidelines of conserving the participants’ anonymity, but also voids me of having to write out their full name every time they say something on tape, which would be time consuming. The transcriptions are aimed to be very accurate and true to the recording of the interviews. This entails that everything was transcribed like it was said, and non-verbal words such as sighing and laughter was also included. While listening to the recordings, a high occurrence of mmhmm and yeah was noted. Not all of them were included, but they were reduced to only occur where they appeared to be relevant to the conversation or point being made. Examples of this are places where they would be confirming a view or thought from another participant, showing a sign of agreement to the statement being said.

After the transcription was finished, the entire transcript was moved over to a Word-document for easy storage, as the free version of InqScribe did not allow for saving the written text unless paid for. All the participants were offered a chance to read through the transcriptions, comment, or delete statements if they wanted to, but none of them seized said opportunity.

3.4.2 Analysis

During the transcription process, I noticed that participants kept returning to themes in their statements. When reading repeatedly through the transcripts, I therefore extracted statements linked to each of the themes identified – this served as the coding. Creswell & Creswell (2018, p. 196) presents Tesch’s (1990) eight steps in the coding process: (1) get a sense of the whole, (2) pick one document and ask yourself what it is about, (3) make a list of all topics, (4) compare the list to the data and abbreviate the topics as codes, (5) find the most descriptive wording for the topics and turn them into categories, (6) finalise decision on abbreviations, (7) assemble data material to corresponding category and perform preliminary analysis, (8) if necessary, recode existing data. Inspired by these steps for forming codes, four themes were established based on the data: expense, accessibility, attitude and usability. They will be elaborated in chapter 4.

Creswell & Creswell state that there generally are three categories of code: expected codes, surprising codes and codes of unusual or of conceptual interest. Expected codes are codes that readers would expect to find, based on for instance literature and common sense. Surprising codes are codes that could not be anticipated beforehand. Codes of unusual or of conceptual interest are those that are, in and of themselves, of conceptual interest to readers (Creswell & Creswell, 2018, p. 195). According to them, it is common to allow codes to emerge, but combination of predetermined and emerging codes can also be utilised instead of fitting the data into predetermined codes. Given the purpose of this study, a focus on emerging codes appears more fitting as an exploration entails little predetermination on what to find – though some expectations can be formed on preconceptions and personal experience. After repeatedly reading through transcripts of the interviews, and extracting statements that correlated to the themes that was identified, notable data from the interviews was compared. Because some participants focused more on a product or aspect than the others, the emphasis on the products is not always equal. An example of this is the case of Skoog, in which one pair of participants experienced difficulties in playing the video, resulting in them moving on to other products while the other pair discussed the product.

To counter this uneven presentation of the products, resulting in having lots of data material on Rocksmith, GarageBand and Soundation, I searched online for reviews and comments about Skoog and used those to base my discussion and reflection on. This allowed for either support or contrast of the statements made by two of the participants, who were the only ones to talk

about Skoog and its usability. In the contrasting of Skoog I used product reviews found on Amazon UK, the Apple Store and a random selection of reviews found on different sites.