Stimulating learning through policy experimentation: A multi-case analysis of how design influences policy learning outcomes in experiments for climate adaptation

Belinda McFadgen*, Dave Huitema

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

18 Citations (Scopus)

Abstract

Learning from policy experimentation is a promising way to approach the "wicked problem" of climate adaptation, which is characterised by knowledge gaps and contested understandings of future risk. However, although the role of learning in shaping public policy is well understood, and experiments are expected to facilitate learning, little is known about how experiments produce learning, what types of learning, and how they can be designed to enhance learning effects. Using quantitative researchmethods,we explore howdesign choices influence the learning experiences of 173 participants in 18 policy experiments conducted in the Netherlands between 1997 and 2016. The experiments are divided into three "ideal types" that are expected to produce different levels and types of learning. The findings show that policy experiments produce cognitive and relational learning effects, but less normative learning, and experiment design influenced three of six measured dimensions of learning, especially the cognitive learning dimensions. This reveals a trade-off between designing for knowledge development and designing for normative or relational changes; choices that experiment designers should make in the context of their adaptation problem. Our findings also show the role leadership plays in building trust.

Original languageEnglish
Article number648
JournalWater (Switzerland)
Volume9
Issue number9
DOIs
Publication statusPublished - 30 Aug 2017
Externally publishedYes

Keywords

  • Climate adaptation
  • Policy experiments
  • Policy learning
  • Science-policy interface

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