9 February 2024
Mixed Methods Designs: Principles and Proceduresonline course
"Learn how to consolidate and enrich the mixed and multimethod skills of researchers, so that you may implement richer and more robust designs in your projects.
Need to know
You should have a basic knowledge in qualitative and quantitative methods, understanding the basic ontological, epistemological and methodological difference between qualitative and quantitative data collection methods.
No prior knowledge of Mixed Methods Designs, specifically, is required.
If you are unsure if you possess the prerequisite knowledge that is requested to be able to follow this course, please contact the instructor. The instructor will not teach these prerequisite items.
Mixed methods research combines the strengths of qualitative and quantitative research by integrating at least one data collection and/or data analysis method from each. This approach offers a comprehensive and nuanced understanding of complex phenomena that may not be captured by one method alone (Johnson, Onwuegbuzie, & Turner, 2007).
Multimethod research is a broader term that encompasses any use of multiple research methods, including two qualitative or two quantitative methods. The use of mixed and multimethod research designs (MMRDs) is increasingly popular, as researchers seek to better capture and analyse the complexity of their research questions. These designs are continuously evolving, and innovative techniques are being developed to further enhance their effectiveness.
Key Topics Covered
Topic 1: Introduction and overview
• Why go mixed’ (how to justify)?
• Definition, terminology
• Two main rationales for MMD
Topic 2: Epistemological underpinning and early uses
• Early uses of MMR
• Battle of methods or battle pf paradigms?
Topic 3: Basic MMR designs
• Sequential designs
• Concurrent designs
• Nested designs
Topic 4: Advanced MMR designs, sampling procedures
• Convergent findings
• Additional coverage
• Connected contributions
• Iterative designs, including FOMM
• Sampling procedures
Topic 5: Data quality, reporting, ethics
• Data quality criteria
• Reporting challenges
• Ethical issues
How the course will work online
The course consists of two main formats: an asynchronous format (receiving access to diverse resources prior the start of the ‘live’ sessions), and a synchronous format during the 5 days of daily 3 hour live sessions. You are able to manage your time in a flexible way during the first asynchronous phase, in order to navigate through the resources, preparing for the live sessions.
In the asynchronous part of the course, there are the following elements:
• Full-text preparatory readings;
• A Canvas forum to start interacting with me & with the other participants;
• Pre-recorded lectures for each of the five topics;
• A list of assignments to be delivered before each ‘live’ session.
Each daily session will be three hours and organized as follows (naturally with a bit of flexibility, if need be):
• Q&A session about the topic of the day: seminar-style discussions based on the specific MMD issue in pre-recorded lectures, and the preparatory readings for the day. Any point(s) that still need to be clarified beyond the Canvas forum discussion, if applicable;
• Working in breakout rooms (sub-groups of 4 participants): discussions based on the pre-session assignment prepared by each participant, with the instructor ‘hopping’ from room to room;
• Plenary ‘lessons learned’ session: Participants highlight some main points & lessons learned, before the live session commences.
For each daily breakout room session, one participant will be responsible for taking short minutes. There will also be a short list of recommended prior readings that will be sent to you ahead of the course starting.
Bojana Lobe is an Assistant Professor at the Faculty of Social Sciences, University of Ljubljana, where she teaches various methods courses, including Social Science Data Collection and Digital Technologies.
Researchers, professional analysts, and advanced students
"The pedagogical approach of the course is designed so that you make concrete progress on your main research project, via three main channels: (1) receiving access to multiple resources and tricks of the trade; (2) discussing in small groups, with other participants that face similar challenges; and (3) receiving small group and individual feedback and guidance by the instructor.
The overarching goal is to consolidate and enrich the mixed and multimethod skills of researchers, so that you may implement richer and more robust designs in your respective current projects and in further applications. This will include four possible ways: building such a design, justifying it, implementing it, and writing it up in the form of an RD section in a short or longer format. A particular emphasis is laid on mixed modes of data collection."
"You can earn up to four credits for attending this course.
3 ECTS credits – Attend 100% of live sessions and engage fully with class activities.
4 ECTS credits – Attend 100% of live sessions, engage fully with class activities and complete a post-class assignment."
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