Introduction to QDA Miner and Wordstat for qualitative content analysis

Key information

Start date: 21 October 2021

Attendance dates:

October 2021: 21

Time commitment: 9:45am - 4pm

Venue:

Distance learning

Contact details:

Overview

QDA Miner and Wordstat are part of a suite of bespoke mixed methods analytic tools provided by Provalis Research. QDA Miner is a qualitative and mixed methods tool, providing powerful coding, annotating, retrieving and analyzing functions. WordStat is a text analysis tool providing sophisticated content analysis and text mining tools. Used together they provide sophisticated and flexible means to integrate qualitative and quantitative data and analyses, in ways unique in comparison to other options currently available. There is also a Lite version of QDA Miner, providing free access to the basic features of QDA Miner.

This one day course provides a general overview to the core functionality of QDA Miner with an introduction to the ways in which the use of WordStat can contribute to mixed methods analyses of textual data, including the building of dictionaries. It is suitable for those wanting to explore the possibilities of software which offers sophisticated content analysis and text mining functionality alongside a suite of qualitative analysis tools.

The course combines discussion, demonstration and hands-on work, including:

  • Contextual discussions – developmental, methodological and analytical principles
  • Software overview –interface, architecture, tools
  • Analytic planning – ensuring analytic strategies drive the appropriate use of software tools
  • Guided instruction – step-by-step teaching in the operation of NVivo and the use of tools for analytic tasks
  • Individual support – time for participants to discuss their projects with the tutor.

Please note: This course will use QDA Miner version 5 and WordStat version 8. The 30 day trial versions available from Provalis software are fine for the purposes of this course.

Learning outcomes

On successful completion of this course, you will be able to:

  • Understand the structure of QDA Miner and Wordstat and how they can be used throughout a research project
  • Navigate around the software and operate it to undertake analysis
  • Understand the importance of analytic planning in harnessing tools powerfully
  • Set-up a QDA Miner project to reflect initial research design and change structures as a research project progresses
  • Identify tools that can be used to fulfil specific analytic tasks
  • Know where to access relevant resources to support continued use.

Course content

  • Principles of using QDA Miner and Wordstat
  • Data preparation, import and organisation
  • Data exploration and familiarisation
  • Coding strategies – including appropriate uses of auto-coding
  • Use of writing and visualisation tools to reflect on data and processes
  • Querying and outputting.

Course leader

Placeholder image for staff profiles

Dr Christina Silver

Research Fellow

Reading list

You are required to read the QDA Miner and Wordstat review (PDF) before attending this course.

Entry requirements

This course assumes participants have a broad understanding of qualitative and/or mixed methods methodologies, but assumes no prior knowledge about QDA Miner or Wordstat.

Fees and funding

Price per person:

£130

Students

£155

Education and charitable sector applicants

£220

Government and commercial sector applicants

How to apply

Applications will be through our online store.

Apply now

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Further details of our terms and conditions will follow.

Disclaimer

This online prospectus has been prepared and published in advance of the commencement of the course. The University of Surrey has used its reasonable efforts to ensure that the information is accurate at the time of publishing, but changes (for example to course content or additional costs) may occur given the interval between publishing and commencement of the course. It is therefore very important to check this website for any updates before you apply for a course with us. Read more.