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Install this application on your home screen for quick and easy access when you’re on the go.
Just tap then “Add to Home Screen”
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Install this application on your home screen for quick and easy access when you’re on the go.
Just tap then “Add to Home Screen”
Monday 7 ꟷ Friday 11 February 2022
2 hours of live teaching per day
08:30 ꟷ 10:30 CET
VIR: This is a virtual course
This course provides a highly interactive online teaching and learning environment, using state of the art online pedagogical tools. It is designed for a demanding audience (researchers, professional analysts, advanced students) and capped at a maximum of 16 participants so that the teaching team can cater to the specific needs of each individual.
This course teaches the basic and advanced features of NVivo for qualitative data analysis. You will learn to set up an NVivo project, organise a qualitative dataset, manage your literature review, autocode data and code data inductively, seek patterns and identify relationships across themes and cases, and present qualitative findings using visualisations.
The course uses the latest version of NVivo (version R1) for Mac and Windows. NVivo for Mac does not currently have all the features of NVivo for Windows. If you are a Mac user and want to learn all the features taught on this course, you must attend using a PC. Download the 14-day free trial of NVivo for Mac or Windows.
Marie-Hélène is a highly regarded methodologist who has NVivo Certified Platinum Trainer status. She has shared her expertise in qualitative data analysis with over 60 universities and research centres around the world, including Qatar and Iran. Since 2009, Marie-Hélène has been teaching introductory and advanced courses in qualitative data analysis at the ECPR Methods School. Her areas of methodological interest include qualitative evidence synthesis, decolonising epistemology, and participatory methodologies. Marie-Hélène is dedicated to advancing the field of qualitative data analysis and sharing her knowledge with others.
This course is designed for researchers who plan to use NVivo to manage, code, and analyse qualitative data in the context of academic research, public policy and not-for-profit applied research.
This is the course you need if you want to learn the added value of using qualitative software to manage large amounts of data efficiently, triangulate different data sources seamlessly, improve the auditability of your research and conduct your analysis in a rigorous and transparent manner.
The course is structured around four modules that follow the logical sequence of a qualitative journey. You will learn to import and organise a qualitative dataset in NVivo; manage your literature review; autocode structured data and code data inductively, work with cases and variables; seek patterns and identify relationship across themes and cases; present findings using visualisations, coordinate teamwork and report the analysis process in theses or articles. The course is entirely hands-on and uses sample data to learn NVivo’s functionalities.
This course does not teach how to use NVivo for specific analytical methods such as thematic analysis, content analysis, grounded theory, etc. For that, you need Advanced Qualitative Data Analysis in week three.
Outside class hours, you will be able to work on your own data, or articles of your literature review if you have not yet collected data. With the teaching assistant, you will also be able to troubleshoot any problems you might have with regard to your analysis in NVivo.
The course combines asynchronous pre-class assignments, such as readings and watching pre-recorded videos, as well as daily two-hour live sessions with Zoom. To prevent Zoom fatigue and boredom, the course pedagogy includes small-group work, short, focused tasks and troubleshooting exercises using a range of online apps that support collective work and participant engagement with the course content.
Although no previous knowledge of NVivo is required, you should have some familiarity with qualitative research.
This course is for both NVivo for Windows and Mac.