![]() We start by autocoding questions from structured interviews, so the responses of each question are gathered in one node. I introduce techniques to autocode and code data inductively in NVivo. We analyse the outputs using word clouds, dendograms, and wordtrees. Module 1 concludes with lexical queries which search for frequency, occurrence, and context of keywords in textual data. We create externals that link an NVivo project to outside information, and memos where the analytic process is recorded. ![]() I explain how you can work directly on pictures or generate a log to associate comments with specific picture regions. I will explain how to work with still images. We turn our attention to the transcribing possibilities of NVivo, starting with transcribing media recordings in full or working only with sound and video sequences. ![]() We learn the key features that support a literature review so sources can be annotated and cross-referenced to highlight a line of arguments and connections across sources. We then move in NVivo and import and organise a range of qualitative data. I open with notions of qualitative research designs and their application in a NVivo project. We review how data can be organised in comparative and non-comparative designs, coding approaches developed, and types of analyses conducted.
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