Research often follows an either-or logic, using either a quantitative or qualitative approach. Yet, combining the two can lead to even more powerful insights than single-method studies.
In this course, we will explore different ways to design and conduct mixed-method studies. We will also consider how to tackle the challenges in preparing results from such studies for academic publications.
- The course is not tied to a particular discipline or theory; it is relevant for PhD students from all disciplines;
- The course discusses conceptual aspects of mixed-methods studies (different designs, approaches for analysis, etc.) and practical issues, based on concrete examples from students, literature and the lecturer's own research;
- The course does not require any in-depth knowledge about quantitative or qualitative paradigms, and will not deal with the details of quantitative or qualitative methods. The focus will be on explaining and exploring mixed-methods from design to publication;
- Active participation and the willingness to share and discuss your own studies are expected.
After completion of the course participants will:
- Understand the benefits and challenges of mixing methods;
- Be able to choose the adequate mixed-method design for their purposes;
- Be able to plan and implement data collection combining quantitative and qualitative approaches;
- Be able to prepare data analysis and integration across methods;
- Understand the specific challenges for publishing mixed-method studies.
Designing mixed-method studies
This lecture starts with a short introduction into quantitative and qualitative research and their respective strengths and weaknesses. The main part will be spend on discussing the various versions in which quantitative and qualitative approaches can be combined, the rationales for choosing specific designs, and the practical implications such choices have for important aspects of a research project, such as sampling procedures and the likely duration of a study.
Managing data collection
The second lecture will provide advice on how to plan for and execute the collection of data, when a combination of quantitative and qualitative approaches is intended.
Analysis, integration and writing up
Often the most difficult step in mixed-method studies is the effective analysis and integration of data following quantitative and qualitative logics. In this lecture, we will discuss the possibilities as well as the challenges when integrating and theorizing from mixed-method data. We will further look into the challenges of writing-up mixed method studies for publication in academic journals.
The last session will be an (optional) practical tutorial. It is meant to give the opportunity to ask specific questions on own research projects for students who intend to or are conducting mixed-method research.
- Creswell, J. W. (2013). Research design: Qualitative, quantitative, and mixed methods approaches. Sage Publications, Incorporated.
- Creswell, J. W., & Clark, V. L. P. (2007). Designing and conducting mixed methods research. Sage Publications, Incorporated.
- González Castro, F., Kellison, J.G., Boyd, S.J., & Kopak, A. (2010). A methodology for conducting integrative mixed methods research and data analyses. Journal of Mixed Method Research, 4(4), 342–360.
- Baranik, L.E., Hurst, C.S., & Eby, L.T. (2018). The stigma of being a refugee: A mixed-method study of refugees' experiences of vocational stress. Journal of Vocational Behavior, 105, 116-130.
- Singh, S. & Aggarwal, Y. (2018). Happiness at Work Scale: Construction and Psychometric Validation of a Measure Using Mixed Method Approach. Journal of Happiness Studies, 19(5), 1439–1463.
- Van Thielen, T., Decramer, A., Vanderstraeten, A., & Audenaert, M. (2018). When does performance management foster team effectiveness? A mixed-method field study on the influence of environmental extremity. Journal of Organizational Behavior, 39(6), 766-782.
Liesbet van Zoonen is professor of popular culture and dean of the Erasmus Graduate School of Social Sciences and Humanities (EGSH) at Erasmus University Rotterdam. Liesbet is also academic director of the Centre for Big Open and Linked Data (BOLD) Cities. She has written about (new) media, citizenship and identity. Her research currently focuses on data and cities.