Using a Complex Adaptive Systems Perspective to Illuminate the Concept of Evaluation Capacity Building in a Network

While evaluation capacity building (ECB) may hold promise for fostering evaluation, little is known about how it is operationalized within a network. This article presents initial findings from a National Science Foundation–funded research project (Complex Adaptive Systems as a Model for Network Evaluations) that used concepts from complex adaptive systems theory to develop case studies of ECB within the Nanoscale Informal Science Education Network. The project used a multiple case study approach to explore ECB within four Network workgroups. Cross-case themes documented characteristics of the system and ECB within it. Evaluation capacity was evident in several ways, including people's comfort with evaluation, evaluation-related skills, evaluation processes used, and the value placed on evaluation. Ultimately, the study identified several complex adaptive system features that fostered Network ECB: massive entanglement and neighbor interactions, information flow/feedback loops, stability and flexibility/adaptability, redundancy and diversity of evaluative skills and knowledge, and both centralized and distributed control