Considering the Source: Sampling and Data Collection in a Mixed Methods Study

Introduction

There has been much methodological literature written about mixed methods research (e.g., Fetters, Curry, & Creswell, 2013; Leech & Onwuegbuzie, 2009). The existing mixed methods literature primarily provides typologies and conceptual discussions with regard to mixed methods designs, sampling techniques, and data collection methods. This literature has been by instrumental in advancing the area of mixed methods research. Minimal detailed and practical explanation of how to navigate through the process of planning a mixed methods study is provided in the literature. Some of the literature describes the steps for designing a mixed methods study (e.g., Schoonenboom, 2018), but with little intense focus on specific steps of the process.

The overall purpose of this chapter is to provide novice researchers with step-by-step instructions for one aspect of designing a mixed methods study. The focus of this chapter is the selection of the data collection and sampling methods. This aspect of the mixed methods design process is second in importance to the development of the research questions. The data collected from the study participants becomes the information used to address the research questions following data analysis. The selection begins with identifying the optimal mixed methods data sources needed to address a set of research questions. After considering the possible data collection and sampling techniques, one can plan the methods to use when obtaining the mixed methods data. This chapter unpacks the nuances of decisions to be made and describes in detail how to navigate the logistics. The selection of data collection and sampling methods is described in a practical manner that is not overly technical to meet the needs of the target audience: novice researchers, such as graduate students working on theses or dissertations; junior faculty; and, practitioners in the field conducting research to address real problems in their professional settings.

This chapter has five major sections:

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  Background: the process for designing a mixed methods study is discussed along with an overview of each of the first four steps of the process;

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  Identifying Data Sources: a procedure is delineated to use when identifying the optimal data sources needed to address a set of research questions;

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  Selecting Data Collection Strategies: six data collection strategies are described along with how to weigh the advantages and disadvantages of each with regard to collecting the mixed methods data needed to address a set of research questions;

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  Developing a Sampling Plan: a procedure to use to develop a sampling plan is described as well as various probability, purposeful, and mixed methods sampling techniques; and,

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  Discussion: how to identify and describe the mixed methods design aligned with the data collection and sampling decisions is articulated.

Background

In this chapter, a study is defined to include formal research projects, evaluations, or any other process through which data are examined and used to address questions. The term data is defined to include both numerical values or scores, textual material, visual material (e.g., video, photography, artwork), and other pieces of material that can be collected about a unit of analysis. A unit of analysis is defined as the unit for which the data are describing. This could be an individual, a group, and organization, a physical location, etc… A mixed methods study is defined as one that includes both quantitative and qualitative methods. Quantitative methods use numerical data and statistical analyses usually to confirm theory. Qualitative methods use non-numerical data (e.g., textual, visual) to explore and develop theory. However, qualitative methods can be used to test theory and quantitative methods can be used to develop theory. In a mixed methods study, there are two strands: a qualitative strand and a quantitative strand. The qualitative strand is the collection and analysis of the qualitative data. Quantitative data are collected and analyzed in the quantitative strand (Schoonenboom, 2018).