Data-gathering Methods

Data-gathering methods refer to the techniques and tools a researcher uses to collect data or gain insight into the world of the research participants. Within an interpretive paradigm, people are viewed as intentional participants in the activities of their communities, and all their perspectives on events or situations are of interest. There is an expectation that the researcher will attend to their multiple realities and interpret or reflect the research context from the multiple viewpoints of the different participants/participant groups (Cohen et al., 2007). Multiple data-generation methods are available to the interpretive researcher and are often used to increase the credibility or trustworthiness and ‘interpretability’ of data generated from multiple sources. A different method reveals different aspects of reality, and no method is completely neutral or without restrictions (Cohen et al., 2007). Hence, the use of only one method of data collection can render a study less credible. Interpretive qualitative research increases in credibility and robustness through the use of multiple data-generation methods. While it is acknowledged that both the participants and researcher influence the data-collection process by bringing their own history and experiences to the process, ultimately, how the research evolves and is documented is the decision of the researcher.

Interviews

An interview is a conversation between the interviewer and interviewee (or group of interviewees) with a particular purpose in mind (Cohen et al., 2007). Interviews enable participants to express their views and discuss their situations or interpretations from their perspectives. Participants can use natural language to express themselves so that in-depth information may be gathered directly from them in their own words. Interviews are based on the view that knowledge is constructed between participants so that the data is generated rather than collected. The interview can reveal rich materials, although it is subjective, time consuming and often difficult to classify and analyse the responses. Interviews have various purposes, such as enabling the researcher to explore the motivations and explanations for participants’ behaviour, which are often hard to observe directly (Punch, 2009).

In qualitative and interpretive studies, interviews can vary according to the context and purpose of the interviews from unstructured through to semi- structured to highly structured approaches (Cohen et al., 2007; Patton, 2002). An unstructured or informal conversation interview is the most open-ended interview approach, and participants often direct such an interview. It offers the researcher maximum flexibility to explore all appropriate information. Unstructured interviews are used to gain an in-depth insight into the participant’s experiences and interpretations in their own terms. This type of interview consists of the form of a conversation between the interviewer and the interviewee with an unstructured focus on the interviewee’s perception of themselves, their context and experiences. Unstructured interviews can generate data that will contribute to the researcher’s understanding of complexities of human behaviour without imposing any prior categorisations that might limit the breadth of inquiry (Burns, 2000; Punch, 2009).

Semi-structured interviews are based on a set of predetermined (more or less structured) questions from the researcher but permit some flexibility in the order or wording of the questions across a number of participants (Denzin & Lincoln, 2009). This can help ensure systematic data is collected and also allows exploration of individual perspectives or new insights as they arise. The data generated from such interviews can be comprehensive, although the flexibility in the focus can lead to diversity in responses and foci and, again, make data analysis challenging. However, this approach allows for a balance that maximises the collection of data that can be analysed in a comparative manner across participants (Cohen et al., 2007; Patton, 2002).

Structured interviews comprise a set of pre-established questions, and there is little opportunity for variation in the interviewee response. In this interview style, all interviewees receive the same questions in a standardised format. Due to the highly structured and standardised format of this form of interview, the approach is considered to be similar to a quantitative data-collection tool (Punch, 2009). This study utilised semi-structured individual and group interviews as they allowed the flexibility required for open dialogue about key issues while still providing a framework for systematic data collection. The value of the process

was enhanced by the use of open-ended questions followed by probes to maximise the depth of responses from participants. This allowed the interviewees some flexibility and the interviewer some control.

Online Discussion Data

Marra (2006) describes online discussions as providing a text-based forum that provides researchers with a range of opportunities to potentially make the contributors’ learning and thinking visible. An advantage of online discussion posts is that they are in a written format. Therefore, no transcribing is needed, and what is written in them is original to the person who posted the contribution (Sullivan, 2003). Such discussion data can be analysed through a range of methods (De Wever, Schellens, Valcke, & Van Keer, 2006; Marra, 2006) However, Janssens and Kraft (2012) caution that research, which relies on the collection of self-reported data by self-selected participants, has methodological limitations, including selection bias and information bias. They argue that when researchers are aware of and acknowledge these limitations in their work, self- report is a useful and valid mode of data collection. The online discussion data in this study was analysed using thematic analysis based on the work of Brauan and Clarke (2006).