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Member rate £492.50
Non-Member rate £985.00
£70 off Early Bird for Members until 31/10/2024
Save £45 Loyalty discount applied automatically*
Save 5% on each additional course booked
*If you attended our Methods School in the last calendar year, you qualify for £45 off your course fee.
Date: Monday 24 March – Friday 28 March 2025
Time: 13:30 – 16:30 CET
info@mariehelenepare.com
This course offers you an interactive online learning environment using advanced pedagogical tools, and is specifically designed for PhD students, postdoctoral researchers, and professionals. 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:
3 ECTS credits awarded for engaging fully in class activities.
1 additional ECTS credit awarded for completing a post-course assignment.
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 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.
The course includes a rich and diverse mix of online teaching techniques that includes elevator pitch, talk-to-text technique, study groups, debates and pre-recordings. The daily three-hour live session in Zoom are intertwined with hands-on exercises and group work, during which you will work on your own research and have the opportunity to troubleshoot any issue you may have with regard to the analysis of your data, or data analysis generally.
The instructor will also conduct live Q&A sessions for one-to-one consultations.
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 practise extensively what you will have learned to become an advanced NVivo user and be fit for this course. Likewise the course Qualitative Data Analysis provides introductory knowledge to the foundational concepts and processes of qualitative analysis. This introductory course must be combined with real experience in analysing qualitative data to follow 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.
As a participant in this course, you will engage in a variety of learning activities designed to deepen your understanding and mastery of the subject matter. While the cornerstone of your learning experience will be the daily live teaching sessions, which total three hours each day across the five days of the course, your learning commitment extends beyond these sessions.
Upon payment and registration for the course, you will gain access to our Learning Management System (LMS) approximately two weeks before the course start date. Here, you will have access to course materials such as pre-course readings. The time commitment required to familiarise yourself with the content and complete any pre-course tasks is estimated to be approximately 20 hours per week leading up to the start date.
During the course week, you are expected to dedicate approximately two-three hours per day to prepare and work on assignments.
Each course offers the opportunity to be awarded three ECTS credits. Should you wish to earn a 4th credit, you will need to complete a post-course assignment, which will involve approximately 25 hours of work.
This comprehensive approach ensures that you not only attend the live sessions but also engage deeply with the course material, participate actively, and complete assessments to solidify your learning.
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.