Promoting evaluation capacity building in a complex adaptive system

Frances Lawrenz, Elizabeth Kunz Kollmann, Jean A. King, Marjorie Bequette, Scott Pattison, Amy Grack Nelson, Sarah Cohn, Christopher L.B. Cardiel, Stephanie Iacovelli, Gayra Ostgaard Eliou, Juli Goss, Lauren Causey, Anne Sinkey, Marta Beyer, Melanie Francisco

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


This study provides results from an NSF funded, four year, case study about evaluation capacity building in a complex adaptive system, the Nanoscale Informal Science Education Network (NISE Net). The results of the Complex Adaptive Systems as a Model for Network Evaluations (CASNET) project indicate that complex adaptive system concepts help to explain evaluation capacity building in a network. The NISE Network was found to be a complex learning system that was supportive of evaluation capacity building through feedback loops that provided for information sharing and interaction. Participants in the system had different levels of and sources of evaluation knowledge. To be successful at building capacity, the system needed to have a balance between both centralized and decentralized control, coherence, redundancy, and diversity. Embeddedness of individuals within the system also provided support and moved the capacity of the system forward. Finally, success depended on attention being paid to the control of resources. Implications of these findings are discussed.

Original languageEnglish (US)
Pages (from-to)53-60
Number of pages8
JournalEvaluation and Program Planning
StatePublished - Aug 2018

Bibliographical note

Funding Information:
This work was supported by the National Science Foundation [Grant Number 1228868 ]. Any opinions, findings, and conclusions or recommendations expressed in this report are those of the author(s) and do not necessarily reflect the views of the Foundation.

Publisher Copyright:
© 2018 Elsevier Ltd


  • Case studies
  • Complex adaptive systems
  • Evaluation capacity building
  • Networks


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