By Corinne Alfeld and Meredith Larson, NCER Program Officers
Since IES was founded more than a dozen years ago, it has built a reputation for funding rigorous research to measure the causal effects of education policies and programs. While this commitment remains solid, we also recognize the value of well-designed qualitative research that deepens understanding of program implementation and other educational processes and that generates new questions or hypotheses for study. In this blog post, we highlight the outcomes from a recent meeting we hosted focused on the use of mixed methods – that is, studies that combine qualitative and quantitative methods – and share some of the ways in which our grantees and other researchers incorporate mixed methods into their research.
On May 29, 2015, 10 researchers with experience designing and conducting mixed methods research met with staff from the two IES research centers in a technical working group (TWG) meeting. The TWG members shared their experiences carrying out mixed methods projects and discussed what types of technical assistance and resources we could provide to support the integration of high-quality mixed methods into education research. There was consensus among the TWG members that qualitative data is valuable, enriches quantitative data, and provides insight that cannot be gained from quantitative research alone. Participants described how mixed methods in currently used in education research, proposed potential NCER and NCSER guidance and training activities to support the use of high-quality mixed methods, and offered suggestions for researchers and the field. Below are just a few examples that were shared during the meeting:
- Dr. Carolyn Heinrich and colleagues used a longitudinal mixed method study design to evaluate the efficacy of supplemental education services provided to low-income students under No Child Left Behind. One of the critical findings of the study was that there was substantial variation across school districts in what activities were included in an hour of supplemental instruction, including (in some cases) many non-instructional activities. This was revealed as the team examined the interview data describing what activities lay behind the shared metric of an hour of instructional time. Having that level of information provided the team with critical insights as they examined the site-by-site variation in efficacy of supplemental education services. Dr. Heinrich emphasized the need for flexibility in research design because the factors affecting the impact of an intervention are not always apparent in the design phase. In addition, she reminded the group that while statistical models provide an average impact score, there is valuable information included in the range of observed impacts, and that that variability is often best understood with information collected using in-depth field research approaches.
- Dr. Mario Small used mixed methods research to examine social networks in childcare centers in New York City. Using observational methods, he discovered that variations in the level of networking among mothers depended on the individual child care center, not the neighborhood. He hypothesized that child care centers that had the strictest rules around pick-up and drop-off, as well as more opportunities for parent involvement (such as field trips), would have the strongest social networks. In such settings, parents tend to be at the child care center at the same time and, thus, have more interaction with each other. Dr. Small tested the hypotheses using analysis of survey and social network data and found that those who developed a social network through their child care center had higher well-being than those who did not. He concluded from this experience that without the initial observations, he would not have known that something small, like pick-up and drop-off policies, could have a big effect on behavior.
- Dr. Jill Hamm described a difficult lesson learned about mixed methods “after the fact” in her study, which was funded through our National Research Center on Rural Education Support. In planning to launch an intervention to be delivered to sixth-grade teachers to help adolescents adjust to middle school, she and her colleagues worked with their school partners to plan for possible challenges in implementation. However, because some of the qualitative data collected in these conversations were not part of the original research study – and, thus, not approved by her Institutional Review Board – the important information they gathered could not be officially reported in publications of the study’s findings. Dr. Hamm encouraged researchers to plan to use qualitative methods to complement quantitative findings at the proposal stage to maximize the information that can be collected and integrated during the course of the project.
- In a study conducted by Dr. Tom Weisner and his colleagues, researchers conducted interviews with families of children with disabilities to determine the level of “hassle” they faced on a daily basis and their perceptions of sustainability of their family’s routines. Findings from these interviews were just as good at predicting family well-being as parental reports of coping or stress on questionnaires. The findings from the analysis of both the qualitative and quantitative data collected for this study enhanced researchers’ understanding of the impact of a child’s disability on family life more than either method could have alone. Dr. Weisner observed that the ultimate rationale of mixed methods research should be to gather information that could not have been revealed without such an approach. Because “the world is not linear, additive, or decontextualized,” he suggested that the default option should always be to use mixed methods and that researchers should be required to provide a rationale for why they had not done so, where feasible.
Curious to learn more about what was discussed? Additional information is available in the meeting summary.
Comments? Questions? Please email us at IESResearch@ed.gov.