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Interviews – statswork
 

Qualitative data collection: Interview

 

Qualitative data collection: interview

Interviews are considered to be the main tool of the qualitative researcher for Data Collection (Denzin & Lincoln, 1998). According to Walsham (1995) interviews allow the best access to the interpretations that the participants have regarding the actions and events, which have or taking place and the views and aspirations of themselves and other participants. An added benefit is that it allows researchers to step back and examine the interpretations of their fellow participants in some detail, and this is an advantage that other methods may not allow.

Types of interview

According to Denzin and Lincoln (1998) there are three major types of interviews namely:

  • Structured interview
  • Semi-structured interviews
  • Unstructured interviews

Interviews can also be undertaken in various forms like personal interviews, face-to-face group interviewing, telephone surveys etc. An In-Depth Interview is a dialogue between interviewer and an interviewee. Its goal is to elicit rich, detailed material that can be used in analysis. Such interviews are best conducted face to face, although in some situations telephone interviewing can be successful.

Advantages of interviews:

Usually yield richest data, details, new insights, permit face-to-face contact with respondents, provide opportunity to explore topics in depth, affordability to experience the affective as well as cognitive aspects of responses, allow interviewer to explain or help clarify questions, increasing the likelihood of useful responses, and allow interviewer to be flexible in administering interview to particular individuals or circumstances.

Disadvantages of Interviews:

Expensive and time-consuming, need well-qualified, highly trained interviewers, interviewee may distort information through recall error, selective perceptions, desire to please interviewer, flexibility can result in inconsistencies across interviews, and volume of information too large; may be difficult to transcribe and reduce data (Yin, 2003; Creswell, 2007; Neuman, 2003).

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