Blackwell Reference Online

Extract

One of the key features of qualitative – non-numerical – data is that they are messy and usually voluminous. We wind up with huge piles of texts: transcripts, field notes, documents, questionnaires, pictures, audio, video, and so on, and have to sort our way through them. Add to this the need to find a rigorous approach to the analysis of these large quantities of data, and the researcher faces a daunting task. Researchers from different disciplines and different methodological perspectives will take different approaches to this task, but in most cases, computers can help. Whether we are looking for what we think are identifiable phenomena that we can cluster together into categories or themes, or some more emergent, holistic sense of the data, we need to be able to organize the data in some way. We need to be able to find our way through it, whether by chronology, narrative structure, topic, case type, theme, or by some other kind of relationship between one piece of text and another. We may need to be able to pull together all the pieces of text that have to do with a topic. We may need to be able to see each utterance in its original context to know what it means. Or we may need to be able to find support for a proposition or find the data that contradict it. When working with the often enormous piles of text generated in qualitative research, being careful, diligent, and thorough ... log in or subscribe to read full text