Cornell University, USA
William M. K. Trochim is professor, Department of Policy Analysis and Management at Cornell University. He received his Ph.D. from the Department of Psychology at Northwestern University in the area of Methodology and Evaluation Research. His research is broadly in the area of applied social research methodology, with an emphasis on program planning and evaluation methods. Among experimentalists, he is known for his work in quasi-experimental alternatives to randomized experimental designs, especially the regression discontinuity and regression point displacement designs. In terms of research theory, he has extended the theory of validity through his articulation and investigation of the idea of pattern matching. In multivariate and applied contexts he is recognized for the development of a multivariate form of structured conceptual mapping, a general method for mapping the ideas of a group of people on any topic of interest that integrates traditional group processes (e.g., brainstorming, Delphi, focus groups, nominal group technique) with multivariate statistical methods (e.g., multidimensional scaling, hierarchical cluster analysis). He has written several books, including a widely used introductory research methods text, and articles that have appeared in the American Journal of Evaluation, New Directions for Program Evaluation, Evaluation and Program Planning, Evaluation Review, Journal of Clinical Epidemiology, Consulting and Clinical Psychology, Controlled Clinical Trials, Performance Improvement, and Medical Decision Making, among others. He is the developer of the Concept System® software and methodology and co-owner of a company, Concept Systems Incorporated, that provides the software, training and consulting services to support the method. He has also been an active member of the American Evaluation Association, serving multiple terms on its Board.
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The complexity of concept mapping for policy analysis
Volume: 7, Issue 1
Concept mapping is a participatory mixed methodology that enables diverse participant groups to develop shared conceptual frameworks that can be used in a variety of policy contexts to identify or encourage complexity, and the adaptive emergent properties associated with it. The method is consistent with an evolving paradigm of complex adaptive systems thinking and helps groups address complexity in several ways: it is inductive, allowing shared meaning to emerge; it is based on a simple set of rules (operations) that generate complex patterns and results; it engages diverse agents throughout the process through a range of participation channels (synchronous or asynchronous web, face-to-face, etc.); the visual products - the concept maps, pattern matches, action plots - provide high-level representations of evolving thinking; the results are generative, encouraging shared meaning and organizational learning while preserving individuality and diversity; the maps themselves provide a framework that enables autonomous agents to align action with broader organizational or systems vision. The concept mapping process involves free listing, unstructured sorting and rating of ideas, and a sequence of statistical analyses (multidimensional scaling, hierarchical cluster analysis) that produce maps and other results that the participants then interpret. An example is provided of a web-based project that mapped the practical challenges that need to be addressed to encourage and support effective systems thinking and modeling in public health work. It is suggested that using concept mapping especially in combination with other types of human simulation provides a valuable addition to our methodological tools for studying complex human systems.