Introduction to NVivo
NEW COURSE
Learn how to use NVivo at this training course introducing participants to the principles and practice of using ‘NVivo 11 Pro for Windows’ to support analysis of qualitative data in different formats.
This one-day course is delivered face-to-face in Oxford by the Health Experiences Research Group in the University of Oxford's computing centre. Through a series of practical sessions, the course provides hands-on experience across a range of data types (text-based data, images, video, social media) and in using different techniques (coding, classifications, queries, framework matrices). The course is particularly suited to those already working on projects with a qualitative dimension, doctoral students who are looking for appropriate software to support qualitative data analysis, and those with previous experience in using different qualitative analysis software packages.
While it is aimed at the needs of health professionals, researchers, academics and postgraduate students, the skills developed here apply to many settings - so everyone is welcome, regardless of their research or professional background. Some understanding of qualitative analysis methodology is required, as the course will only focus on using the ‘NVivo 11 Pro for Windows’ software, and will not cover methodological principles.
The course does not cover NVivo for Mac or other NVivo 11 versions, though some of the functionality translates across platforms and software versions.
CONTENT
The course will include:
- practical sessions offering participants the opportunity to practise their skills in using the ‘NVivo 11 Pro for Windows’ software to support analysis of qualitative data in different formats,
- hands-on exercises on importing research materials, developing coding frameworks, coding a sample data set, producing coding reports and codebooks, using memos and annotations, importing classifications, running queries, producing framework matrices and working with reference libraries,
- discussion of advantages and limitations in using qualitative analysis software,
- discussion about the role of software in participants’ own projects.
LEARNING OUTCOMES
By the end of the course participants will
- have an understanding of the role of software packages in qualitative analysis,
- be familiar with data management and analysis functionalities provided by ‘NVivo 11 Pro for Windows’,
- have gained practical experience in using ‘NVivo 11 Pro for Windows’ to support analysis of qualitative data in different formats,
- be able to recognise advantages and limitations of using qualitative analysis software.
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Booking
Next Course:
November 2019
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Course details:
Course fee: TBC
Duration: 1 day
Total places: 15
Venue: Oxford University Computer Services
Contact:
hergcourses@phc.ox.ac.uk
Testimonials:
"Very well taught and enjoyable. The balance was right between demonstrating the work and practical sessions. The course went at the right pace and the facilitators were very approachable and helpful. I will recommend this course to other colleagues.”
“Excellent, clear support from trainers. Non-judgemental and constructive.”
“Great course. Friendly, knowledgeable trainers and good, comprehensive handouts. Feel much more confident now about NVivo.”
NVivo course attendees - 2017
Course tutors
The course is run by the Health Experiences Research Group (HERG), based in the Nuffield Department of Primary Care Health Sciences, University of Oxford. HERG has been running successful qualitative research methods courses for over ten years drawing on the wide range of expertise within the group which includes the disciplinary areas of medical sociology, anthropology and public policy.
The Research Group conducts qualitative research focusing on the personal experiences of health conditions. The research findings, together with supporting video, audio and text extracts from the qualitative interviews, are published at www.healthtalk.org. This unique Oxford database of over 2000 qualitative interviews provides interesting, informative and contemporary teaching materials to support the course content.