The strength of this impulse is widely evident from the methodological design of undergraduate dissertations to multimillion pound research grant applications. David Silverman argues that the reliance on these techniques has limited the sociological imagination: “Qualitative researchers’ almost Pavlovian tendency to identify research design with interviews has blinkered them to the possible gains of other kinds of data” (Silverman 2007: 42).
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For qualitative researchers the tape-recorder became the prime professional instrument intrinsically connected to capturing human voices on tape in the context of interviews. Over the past 50 years the habitual nature of our research practice has obscured serious attention to the precise nature of the devices used by social scientists (Platt 2002, Lee 2004). This quote has been too true for too long: I’m kind of hoping that the sudden shifts the pandemic has caused in practice and process might lead to some developments and rethinking of analysis.
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I also think this really gives the lie to the idea that manual transcription is “the best way” to get in touch with audio.
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I’ve had a lot of help and encouragement – see acknowledgements below – but also NEED from students and groups who are wondering how to do transcription better. So this has been a real focus for me recently. The blog bit – background, next steps, context ResourcesĮxample project file NVivo R1 (Windows) hereĮxample media file and VTT file from the first video also available here. But not only corrections! You can also annotate the transcript, label speakers and even start coding at this stage. This process allows you to now use the powerful tools within NVivo to playback the audio / video (including slowing playback speed,adjusting volume and setting rewind intervals when you press play/pause + keyboard shortcuts for the play/pause functions) whilst you read the transcript and make corrections. You can also (currently) upload videos to Stream or use a wide range of other applications and system to create an automatic transcript of a media file. The introductory video was created with Teams, another was created in Zoom. Step One – Create a media file with subtitle file in VTT formatĭepending where you start there are a few ways this will work – all have the same end point: a media file and a VTT transcript.
Clean the subtitle file ready for import.
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Download the media file and the subtitle file.Create a media file with subtitle file in VTT format.Installation of the free VLC media player.Installed version of NVivo – the following is illustrated for R1.A recording from another system that outputs a subtitle file (that you will then convert to VTT).An audio or video recording through an institutionally licensed Zoom account (with subtitling enabled).A media file you can convert and upload to Microsoft Stream*.A recording within Microsoft Teams saved to Stream.
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The user discussion forum is also a useful place for learning how to use the program and to apply the software to specific research needs.The following are important prerequisites. Many tutorials can be found online and via the MaxqDA website. Flat coding prevents imposing a structure on data while hierarchical coding can help researchers find patterns in the document, assists with analysis and building models. Each coded segment in Nvivo called a "node", can have a set of custom properties that include instance-specific values can be either flat, or hierarchically arranged, each of which has certain advantages. This grounded approach will allow users to build an understanding of the underlying themes in the data. This is important for exchanging data on research teams whose members will be using both Windows and Mac computers.Ĭolleagues have often commented on how Nvivo is easy to use for content and thematic analysis.īy using Nvivo to define codes and tag documents with the codes as you move through the document.