Systemic Evaluation, Impact Evaluation and Logic Models

Datos Bibliográficos

ID12347349
AutoresRalph Renger (0000-0002-0224-1444, Mel and Enid Zuckerman College of Public Health at the University of Arizona, Tucson, Arizona, autor de correspondencia), Shandiin Wood (Mel and Enid Zuckerman College of Public Health at the University of Arizona, Tucson, Arizona), Simon Williamson (0000-0002-8951-6446, Senior Evaluation Advisor in the Strategy, Advisory and Evaluation Group with the New Zealand Ministry of Foreign Affairs and Trade, Wellington), Stefanie Krapp (M&E Officer with the Monitoring and Evaluation Unit at Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ), Eschborn, Germany)
Año2011
Volumen11
Número2
Páginas24-30
Fecha de publicación2011-09-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaEvaluation Journal of Australasia (JOURNAL)
Identificadores de la revistaISSN: 1035-719X • E-ISSN: 2515-9372
EditorialSAGE Publishing (PUBLISHER • US)
DOI10.1177/1035719x1101100204
OpenAlexW2118253723
IdiomaEN
Citas recibidas8
Referencias citadas16

Evaluators are yet to define systemic evaluation adequately. With respect to impact evaluation, systemic evaluators are critical of current methods such as simple logic models, or logframes, for capturing the contextual complexity in which programs operate. Despite a lack of clarity about what constitutes a systemic evaluation, many evaluators are suggesting it is a better alternative for capturing the true complexity of the context in which a program operates. However, capturing complexity is itself complex, resulting in amorphous and ambiguous approaches and results. This can create problems in relation to evaluation capacity building, usability of results, and evaluator credibility. This article demonstrates how methods such as simple logic models or logic models grounded in situational awareness can be an ally in bridging clients' understanding, so that systemic evaluation is not perceived to be new, but rather something that continues to build on past investments

Argumentation theory · Bridging (networking · CLARITY · Computer security · Context (archaeology · Credibility · Data science · Epistemology · Human–computer interaction · Informal logic · Knowledge management · Logic model · Management science · Simple (philosophy · Simplicity · Sociology · Usability · Community Health and Development · Computer Science · Engineering · Evaluation and Performance Assessment · Health Policy Implementation Science