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Cintron, Dakota W.; Montrosse-Moorhead, Bianca – American Journal of Evaluation, 2022
Despite the rising popularity of big data, there is speculation that evaluators have been slow adopters of these new statistical approaches. Several possible reasons have been offered for why this is the case: ethical concerns, institutional capacity, and evaluator capacity and values. In this method note, we address one of these barriers and aim…
Descriptors: Evaluation Research, Evaluation Problems, Evaluation Methods, Models
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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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Pattyn, Valérie; Molenveld, Astrid; Befani, Barbara – American Journal of Evaluation, 2019
Qualitative comparative analysis (QCA) is gaining ground in evaluation circles, but the number of applications is still limited. In this article, we consider the challenges that can emerge during a QCA evaluation by drawing on our experience of conducting one in the field of development cooperation. For each stage of the evaluation process, we…
Descriptors: Qualitative Research, Comparative Analysis, Evaluation Methods, Program Evaluation
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Durand, Roger; Decker, Phillip J.; Kirkman, Dorothy M. – American Journal of Evaluation, 2014
Despite our best efforts as evaluators, program implementation failures abound. A wide variety of valuable methodologies have been adopted to explain and evaluate the "why" of these failures. Yet, typically these methodologies have been employed concurrently (e.g., project monitoring) or to the post-hoc assessment of program activities.…
Descriptors: Evaluation Methods, Program Implementation, Failure, Program Effectiveness
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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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Pituch, Keenan A.; Whittaker, Tiffany A.; Chang, Wanchen – American Journal of Evaluation, 2016
Use of multivariate analysis (e.g., multivariate analysis of variance) is common when normally distributed outcomes are collected in intervention research. However, when mixed responses--a set of normal and binary outcomes--are collected, standard multivariate analyses are no longer suitable. While mixed responses are often obtained in…
Descriptors: Intervention, Multivariate Analysis, Mixed Methods Research, Models
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Gee, Kevin A. – American Journal of Evaluation, 2014
The growth in the availability of longitudinal data--data collected over time on the same individuals--as part of program evaluations has opened up exciting possibilities for evaluators to ask more nuanced questions about how individuals' outcomes change over time. However, in order to leverage longitudinal data to glean these important insights,…
Descriptors: Longitudinal Studies, Data Analysis, Statistical Studies, Program Evaluation
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Kitto, Richard J.; Barnett, John – American Journal of Evaluation, 2007
Despite the best of intentions, qualitative researchers can be faced, in some circumstances, with having to make meaning from thin, or less than optimal, data. Using a real study as context, the authors describe the ways that they made sense of their thin data on teachers' perceptions of a large-scale evaluation instrument. They propose a…
Descriptors: Sequential Approach, Qualitative Research, Data Interpretation, Electronic Mail
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Sutherland, Stephanie – American Journal of Evaluation, 2004
In this article, I outline how, with the appropriate mix of external requirements and internal motivation, structure and capacity, a school can promote and maintain a culture of evaluative practices, specifically data use, for continuous improvement. I draw upon qualitative data conducted in a study of an Edison Project school. The findings from…
Descriptors: School Restructuring, Experimental Schools, Educational Change, Educational Improvement