Knowledge Mobilization and Research Impact in Canadian Universities: A Developmental Evaluation of Network Learning

Abstract

In Canada and abroad, governments and research funders are increasing expectations that researchers engage in knowledge mobilization (KMb) efforts to advance the impacts of research. However, despite this growing pressure, researchers and universities are struggling to build their KMb capacity. This dissertation aims to contribute to the research and practice of KMb by investigating the experiences and perspectives university-embedded professional staff who operationalize KMb as well as their professional networks that build KMb capacity at scale. Developmental evaluation (DE) provides the overarching design of this study, and the participants were members of Research Impact Canada (RIC). A multi-manuscript format is used to organize this dissertation reflecting one study with three phases. The first paper corresponds to Phase I of the DE and presents survey findings from 16 RIC leaders, representing 14 networked universities, about the usefulness and use of network learning to build institutional KMb capacity. The second paper corresponds to Phase II of the DE and presents the findings from semi-structured interviews with 20 key informants from 17 RIC member institutions regarding network learning and how it could be structured to improve the disconnect between KMb theory and practice. The third paper combines the findings from Phases I and II of the DE and merges key insights with practitioner narratives from four experienced RIC members, focusing on how the lessons learned from RIC provide insight into how universities can foster active engagement in KMb. The final paper presents an overview of quantitative measurement tools for the impacts of co-production, which developed in response to an identified problem of practice for KMb professionals. Collectively, the findings from these papers elucidate the potential of network learning to build institutional KMb capacity, while acknowledging that such efforts require attention to (a) the diversity of individual and institutional practices; (b) tensions that can simultaneously spell network fragmentation or a generative learning environment; and (c) enduring questions for the field of KMb; and (d) how a necessary complement to KMb efforts will require engaging more openly and critically with psychometric and pragmatic considerations when designing, implementing, and reporting on research impact measurement tools.