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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 27 ꟷ Friday 31 July 2020
2 hours of live teaching per day
Courses will be either morning or afternoon to suit participants’ requirements
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 (the Instructor plus one highly qualified Teaching Assistant) can cater to the specific needs of each individual.
This course will teach you how to use NVivo for the management, coding, analysis and visualisation of qualitative data. It follows the qualitative data analysis process in sequence, and covers how to:
3 credits Engage fully with class activities
4 credits Complete a post-class assignment
Marie-Hélène teaches qualitative research methods at the Open University of Catalonia (UOC) and is a freelance methodologist in qualitative data analysis. She was educated in Quebec, Beirut and Oxford where she read social work. A clinician by training, she worked as a mental health officer in humanitarian missions for MSF, MDM and UNWRA in psychosocial aid programs for survivors of war trauma in East Africa and the Middle East. Her clinical work led her to research the harm that INGOs can do in the name of doing good when imposing Western paradigms in culturally and politically different contexts.
Marie-Hélène is an NVivo Certified Platinum Trainer and is a member of the NVivo Core Trainer Team who teaches the NVivo online courses. She is a sought-after methodologist who has taught qualitative data analysis in more than sixty universities and research centres worldwide, in countries including Qatar and Iran. Since 2009, Marie-Hélène has taught the introductory and advanced courses in qualitative data analysis at the ECPR Methods School and teaches similar courses at the IPSA-NUS Summer School in Singapore. Her methodological interests range from advances in qualitative data analysis, qualitative evidence synthesis, decolonising epistemology and participatory methodologies.
This course is designed for those who intend to use NVivo to manage, code, and analyse qualitative data and present qualitative findings in articles, reports or theses.
It is the course you need if you are looking for training in using qualitative software that supports the research process from beginning to end.
The course is structured around four modules that address the following topics:
The course is entirely hands-on and uses sample data to practise NVivo’s functionalities.
Please note This course does not teach qualitative data analysis in NVivo based on specific methods such as thematic analysis, content analysis, grounded theory, etc.
The course combines pre-course tasks, such as readings which will be provided beforehand and pre-recorded videos, as well as live lectures, during which the Instructor and participants will interact in real-time.
Apps that support online learning management systems (LMS) such as Google Docs, Slack and Asana, also feature in the course's pedagogy.
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.
Each course includes pre-course assignments, including readings and pre-recorded videos, as well as daily live lectures totalling at least three hours. The instructor will conduct live Q&A sessions and offer designated office hours for one-to-one consultations.
Please check your course format before registering.
Live classes will be held daily for three hours on a video meeting platform, allowing you to interact with both the instructor and other participants in real-time. To avoid online fatigue, the course employs a pedagogy that includes small-group work, short and focused tasks, as well as troubleshooting exercises that utilise a variety of online applications to facilitate collaboration and engagement with the course content.
In-person courses will consist of daily three-hour classroom sessions, featuring a range of interactive in-class activities including short lectures, peer feedback, group exercises, and presentations.
This course description may be subject to subsequent adaptations (e.g. taking into account new developments in the field, participant demands, group size, etc.). Registered participants will be informed at the time of change.
By registering for this course, you confirm that you possess the knowledge required to follow it. The instructor will not teach these prerequisite items. If in doubt, please contact us before registering.