The FIVE LEVEL QDA(R) Method

for harnessing CAQDAS packages powerfully

Developed by Nicholas Woolf and Christina Silver

A method for harnessing CAQDAS packages powerfully, independent of methodology, software package, or mode of learning. It is not a new method of data analysis but a way of making clear what CAQDAS experts unconsciously already do.

Five Level QDA is a trademark owned by Christina Teal and Nicholas H. Woolf, registered as European Community Trademark Registration Number 015596976, and United States Trademark Serial Number 87080134

QDA = Qualitative Data Analysis

CAQDAS = Computer Assisted Qualitative Data Analysis

                Faculty

QDA Faculty

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QDA Students

            Researchers

QDA Researchers

Harnessing CAQDAS Blog

Translation in Five-Level QDA: What's in a name? Actually, quite a lot

Translation in Five-Level QDA: What's in a name? Actually, quite a lot
By Nicholas Woolf on Jul 07, 2017 at 07:00 PM in Five-Level QDA in practice

“Translation” is the key concept in our Five-Level QDA method, so it’s important to know what it means. The word just showed up in the title of Susanne Friese’s blog post on the ATLAS.ti website – “Translating the process of open/initial coding in Grounded Theory” – and Susanne ended by inviting readers “to read more about this process of translation” in our textbooks on the Five-Level QDA method coming from Routledge in September. But as Susanne uses the word “translation” in a very different way from us we want to clear it up right away.

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Don't lose your analytic reflections: The value of writing spaces in CAQDAS packages

Don't lose your analytic reflections: The value of writing spaces in CAQDAS packages
By Christina Silver on Jun 17, 2017 at 09:30 AM in CAQDAS commentary

Writing spaces are one of the most valuable features of dedicated CAQDAS packages. But I often see projects that make little use of them. Here’s why they are so potentially powerful.

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Harnessing NVivo Classifications: it's all about units

Harnessing NVivo Classifications: it's all about units
By Christina Silver on May 29, 2017 at 06:01 AM in NVivo Learning, Five-Level QDA in practice

Kath McNiff’'s post on the NVivo Blog about classifying data in NVivo has prompted me to get writing about how I deal with this teaching challenge. For me, teaching students to choose between the available tools for classifying data and how to harness them appropriately revolves around units.

For years I've experimented with different ways of teaching how to harness the NVivo tools for classifying factual characteristics of data and respondents - for example the socio-demographics of participants or the metadata about documentary evidence. One of the great things about NVivo is that it offers several different ways of doing this, making it a very flexible tool.

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