During the past two decades mixed methods and multi method research (MMMR) has become an established empirical approach within a broad spectrum of social science disciplines. The integration of quantitative and qualitative methods is a growing research area and MMMR-Designs are increasingly acknowledged as a powerful strategy alongside traditional mono-method approaches. However, this positive development has been accompanied by several issues.Firstly, the popularization of MMMR has led to a considerable expansion of methodological concepts and terminologies.
The resulting plethora of conceptualizations remains yet to be integrated into a broadly applicable methodological framework. In its current state, the methodological literature on MMMR is - at least in some instances - prone to cause confusion rather than clarity, e.g. in the areas of validation criteria or data analysis strategies.Secondly, methodological dialog is sometimes hindered by disciplinary boundaries, since MMM-researchers tend to remain grouped into disciplines or research fields, e.g. in educational science, psychology, or comparative political science.
The proposed scientific network will take on these methodological issues by providing an infrastructure for problem-centered, interdisciplinary discussion. At the same time, it aims to intensify the exchange between the German-speaking and international methods-communities. The following topics will be emphasized:
- (1) How can the multiplicity of current MMMR-conceptualizations and terminologies be integrated more fully without compromising diversity?
- (2) What are different approaches towards causal analysis in MMMR and what are possible avenues towards a more productive dialog between them?
- (3) What are current issues and developments with regard to MMMR sampling and data collection?
- (4) What are current problems and potentials for innovation in MMMR data analysis?
- (5) What are promising avenues towards practical, comprehensive quality criteria and best-practice-guidelines for MMMR?
- (6) What are typical barriers for communicating MMMR-results and teaching MMMR-skills and what are possible ways to reduce them?