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Campbell, Rebecca; Goodman-Williams, Rachael; Feeney, Hannah; Fehler-Cabral, Giannina – American Journal of Evaluation, 2020
The purpose of this study was to develop triangulation coding methods for a large-scale action research and evaluation project and to examine how practitioners and policy makers interpreted both convergent and divergent data. We created a color-coded system that evaluated the extent of triangulation across methodologies (qualitative and…
Descriptors: Mixed Methods Research, Action Research, Data Interpretation, Coding
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Hilton, Lara G.; Azzam, Tarek – American Journal of Evaluation, 2019
Evaluations that include stakeholders aim to understand their perspectives and to ensure that their views are represented. This article offers a new approach to gaining stakeholder perspectives through crowdsourcing. We recruited a sample of individuals with chronic low back pain through a crowdsourcing site. This sample coded textual data…
Descriptors: Qualitative Research, Stakeholders, Data Collection, Chronic Illness
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Jacobson, Miriam R.; Whyte, Cristina E.; Azzam, Tarek – American Journal of Evaluation, 2018
Evaluators can work with brief units of text-based data, such as open-ended survey responses, text messages, and social media postings. Online crowdsourcing is a promising method for quantifying large amounts of text-based data by engaging hundreds of people to categorize the data. To further develop and test this method, individuals were…
Descriptors: Mixed Methods Research, Evaluation Methods, Comparative Analysis, Feedback (Response)
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Namey, Emily; Guest, Greg; McKenna, Kevin; Chen, Mario – American Journal of Evaluation, 2016
Evaluators often use qualitative research methods, yet there is little evidence on the comparative cost-effectiveness of the two most commonly employed qualitative methods--in-depth interviews (IDIs) and focus groups (FGs). We performed an inductive thematic analysis of data from 40 IDIs and 40 FGs on the health-seeking behaviors of African…
Descriptors: Cost Effectiveness, Comparative Analysis, Interviews, Focus Groups
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Neal, Jennifer Watling; Neal, Zachary P.; VanDyke, Erika; Kornbluh, Mariah – American Journal of Evaluation, 2015
Qualitative data offer advantages to evaluators, including rich information about stakeholders' perspectives and experiences. However, qualitative data analysis is labor-intensive and slow, conflicting with evaluators' needs to provide punctual feedback to their clients. In this method note, we contribute to the literature on rapid evaluation and…
Descriptors: Qualitative Research, Data Analysis, Evaluation, Evaluation Methods
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Labin, Susan N.; Duffy, Jennifer L.; Meyers, Duncan C.; Wandersman, Abraham; Lesesne, Catherine A. – American Journal of Evaluation, 2012
The continuously growing demand for program results has produced an increased need for evaluation capacity building (ECB). The "Integrative ECB Model" was developed to integrate concepts from existing ECB theory literature and to structure a synthesis of the empirical ECB literature. The study used a broad-based research synthesis method with…
Descriptors: Synthesis, Literature Reviews, Data Analysis, Coding
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Jackson, Suzanne F.; Kolla, Gillian – American Journal of Evaluation, 2012
In attempting to use a realistic evaluation approach to explore the role of Community Parents in early parenting programs in Toronto, a novel technique was developed to analyze the links between contexts (C), mechanisms (M) and outcomes (O) directly from experienced practitioner interviews. Rather than coding the interviews into themes in terms of…
Descriptors: Foreign Countries, Semi Structured Interviews, Qualitative Research, Comparative Analysis
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Thomas, David R. – American Journal of Evaluation, 2006
A general inductive approach for analysis of qualitative evaluation data is described. The purposes for using an inductive approach are to (a) condense raw textual data into a brief, summary format; (b) establish clear links between the evaluation or research objectives and the summary findings derived from the raw data; and (c) develop a…
Descriptors: Logical Thinking, Qualitative Research, Data Analysis, Evaluation Methods