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Abstract

Cooperation is increasingly required to craft solutions to complex problems in our society, while the role of cultivated, academic expertise is being challenged as a model for solving social problems. Participatory or community-based approaches are often suggested as a solution to this dichotomy; however, few analytic methods are purposefully engineered to support this work. Affinity networks combine interviewing with data visualization to produce data analysis that can be easily fed back into collaboratives with community partners. This article provides a step by step introduction to producing affinity networks using Computer Assisted Qualitative Data Analysis Software, as well as suggestions for using them to advance community partnerships.

Keywords

Affinity Networks, Community-Based Research, Research-Practice Partnership, University-Community Partnership, NVivo, CAQDAS

Author Bio(s)

Catharine Biddle is an Assistant Professor of Educational Leadership at the University of Maine. Her research focuses on ways in which rural schools and communities respond to social and economic change in the 21st century. She is particularly interested in how schools can more effectively leverage partnerships with external organizations or groups to address issues of social inequality and how non-traditional leaders—such as youth, parents and other community members—may lead or serve as partners in these efforts. Correspondence regarding this article can be addressed directly to: catharine.biddle@maine.edu.

Ian M. Mette is an Assistant Professor in Educational Leadership at the University of Maine. His research and teaching interests include school reform, instructional supervision, and the merging of the two to drive meaningful improvement of educational systems. Specifically, his work targets how educators, researchers, and policy makers can better inform one another to drive school improvement and reform policy.

Publication Date

6-19-2019

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.

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