A Systematic Mixed Methodological Review of the Quantitative and Qualitative Methods Used in Mixed-Methods Published Research and IES Funded K – 12 Educational Statistical Analysis
Buros Center for Testing and University of Nebraska-Lincoln
Educational research involving mixed methods (MM) provides valuable context that may be missing from quantitative research. Although MM is encouraged by the Institute of Educational Sciences (IES), their guidelines do not reference its use. While most IES-funded research tends to be quantitative, if either quantitative or qualitative methods used within MM research lack rigor, then it is less likely to receive funding by IES and raises concerns regarding the quality of MM in the field of education. Guided by established complexity continua, this MM systematic review analyzes the methodological rigor of existing MM published and IES-funded research within education. The findings indicate that MM educational research reports the use of qualitative data more often than IES-funded studies do, while IES-funded studies implement more statistically complex quantitative methods. Future study should focus on identifying differences in MM designs, use of joint displays, and expertise in collaborative MM teams.
The purpose of this repository is to be transparent in showing the statistical tests and results for our exploration of the research methods and designs used between the Institute of Educational Sciences (IES) and non-IES funded mixed methods educational research. The data used derived from qualitative coding of articles published by journals and proposals advertised by IES via their website between 2014-2019. To better understand the screening of the sample of articles used, check out the PRISMA Chart document. Coding of relevant articles focused on the methodology and study designs rather than specific outcomes. Using MaxQDA, articles and IES studies were analyzed by the two authors who independently coded half of the articles and the IES proposals. The code list utilized was divided into five components: research method, IES research purpose, quantitative method, qualitative method, and mixed methods integration type. The codes for the quantitative and qualitative methods were organized using Onwuegbuzie (2016) a priori coding scheme which places method complexity along continuums. Using the RStudio environment (RStudio Team, 2021), statistical analyses were conducted via R Markdown to identify differences betweeen IES and non-IES funded studies in terms of reporting of methods and code complexities across these continuums. These were visualized through a set of bar charts that were divided into quantitative method, qualitative method, and research design by study purpose. You will also find a complete bibliography of published mixed methods educational research articles used for this systematic review.