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Monday 31 July – Friday 4 August 2023
Minimum 2 hours of live teaching per day
11:00 – 13:00 CEST
This course offers an interactive online learning environment using advanced pedagogical tools, and is specifically designed for advanced students, researchers, and professional analysts. The course is limited to a maximum of 16 participants, ensuring that the teaching team can address the unique needs of each individual.
This course teaches how to conduct four methods of qualitative analysis widely used in the social sciences using NVivo:
You will also learn how and when to combine different components of these methods in a single study, as well as the criteria to appraise the quality of qualitative data analysis.
By the end of this course, you will be able to:
4 credits - Engage fully in class activities and 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 provides you with advanced understanding and applied skills in qualitative content analysis (Schreier, 2012), thematic analysis (Boyatzis, 1998), cross-case analysis (Miles and Huberman, 1994) and grounded theory (Strauss and Corbin, 1998) using NVivo.
It fills a critical gap in scholarly literature and graduate training by providing step-by-step guidance in how to choose sampling, code data, conduct analysis and present findings of the four methods in a CAQDAS environment.
Day 1 – 4 are dedicated to the four methods, during which you will learn each method’s epistemological foundations and sampling requirements. Moving on to NVivo and implementing each method’s coding procedures, data transformation techniques and visualisation styles.
On Day 5, you will learn to integrate different components of the five methods into a single study, illustrating the promises, but also the potential pitfalls, of method integration.
The course ends with a workshop where you will critically review the criteria published in the literature to assess the quality of qualitative analysis. You will put forward recommendations for reporting this phase of qualitative research in theses or articles.
Outside live sessions, you will be able to discuss the course content, and troubleshoot any problems you might have with the Teaching Assistant.
The course combines pre-course assignments, such as readings and pre-recorded videos, as well as daily two-hour live lectures in Zoom, during which you will interact with the Instructor and fellow participants in real time.
To prevent Zoom fatigue, the course pedagogy includes small-group work, short, focused tasks and troubleshooting exercises using a range of online apps that support collective work and engagement with the course content.
This is an advanced method and software course. You must possess a solid foundation in qualitative analysis and be an advanced NVivo user – meaning that you can teach a crash NVivo course to colleagues. You should be able to create codes and relationships, work with cases and attributes, create sets, run queries, generate maps and set-up framework matrices independently.
Having experience in other qualitative software does not qualify you for the course.
The Introduction to NVivo course provides an introduction to NVivo. You will have to practice extensively what you will have learned to become an advanced NVivo user and be fit for this course. The course Qualitative Data Analysis will give you sufficient knowledge to engage in this course satisfactorily.
You must run the latest versions of NVivo (R1 or 14) to attend the course as earlier versions (10 or 12) have different interfaces and menus. If your institution does not provide you with an NVivo license, you can download the NVivo 14-day free trial. The trial is fully operational but can't be reinstalled on the same computer once expired.
Mac users must be warned that NVivo for Mac does not currently have all the functionalities of NVivo for Windows. If you are a Mac user and want to learn all the functionalities on this course, you must attend using a PC.
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.