We are Alexandra Hill and Diane Hirshberg, and we are part of the Center for Alaska Education Policy Research at the University of Alaska Anchorage. The evaluation part of our work ranges from tiny projects – just a few hours spent helping someone design their own internal evaluation – to rigorous and formal evaluations of large projects.
In Alaska, we often face the challenge of conducting evaluations with very small numbers of participants in small, remote communities. Even in Anchorage, our largest city, there are only 300,000 residents. We also work with very diverse populations, both in our urban and rural communities. Much of our evaluation work is on federal grants, which need to both meet federal requirements for rigor and power, and be culturally responsive across many settings.
Lesson Learned: Using mixed-methods approaches allows us to both 1) create a more culturally responsive evaluation; and 2) provide useful evaluation information despite small “sample” sizes. Quantitative analyses often have less statistical power in our small samples than in larger studies, but we don’t simply want to accept lower levels of statistical significance, or report ‘no effect’ when low statistical power is unavoidable.
Rather, we start with a logic model to ensure we’ve fully explored pathways through which the intervention being evaluated might work, and those through which it might not work as well. This allows us to structure our qualitative data collection to explore and examine the evidence for both sets of pathways. Then we can triangulate with quantitative results to provide our clients with a better sense of how their interventions are working.
At the same time, the qualitative side of our evaluation lets us lets us build in measures that are responsive to local cultures, include and respect local expertise, and (when we’re lucky) build bridges between western academic analyses and indigenous knowledge. Most important, it allows us to employ different and more appropriate ways of gathering and sharing information across indigenous and other diverse communities.
Rad Resource: For those of you at universities or other large institutions that can purchase access to it we recommend SAGE Research Methods. This online resource provides access to full text versions of most SAGE research publications, including handbooks of research, encyclopedias, dictionaries, journals, and ALL the Little Green Books and Little Blue Books.
Rad Resource: Another Sage-sponsored resource is Methodspace, an online network for researchers. Sign-up is free, and Methodspace posts selected journal articles, book chapters and other resources, as well as hosting online discussions and blogs about different research methods.
Rad Resource: For developing logic models, we recommend the W.K. Kellogg Foundation Logic Model Development Guide.
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