Dissemination in STEM Education R&D:
Perspectives on Knowledge Use
Communication Approaches Informed by Dissemination Research:
ü Communication should address the incentives and the customary practices in knowledge use that characterize the particular group to be reached.
ü Handing research reports to members of practice or policy communities is not an effective means of communication.
ü Teachers are not the ones who make adoption decisions for innovative curricula or assessments. A sustained partnership with school and district decisionmakers may help R&D projects make inroads in the face of the weak incentives for implementing new knowledge.
ü Recognizing that R&D results will not be effectively communicated to practice or policy through traditional research publications (whether on paper or online), investigators need to understand the knowledge-using behaviors of the community that might potentially use their results. They will benefit from enlisting the help of linkers who interact regularly with practitioners or policymakers. Linkers can translate…and can effectively place knowledge in context for potential users.
Nontraditional Applications of Dissemination Research: What Sustained Interaction Could Mean:
ü If one finding emerges with clarity from decades of research on dissemination, it is that sustained interaction across communities bolsters the use of knowledge resources in the target community.
ü Although thinking about dissemination may be difficult and even counterintuitive in the early stages of an R&D project, in fact much groundwork can be laid from the beginning of a project.
ü If teachers see attributes that leave them reluctant to join the project or to continue participating—something that often happens in projects like those of DR K–12—their perceptions constitute data relevant to the prospects for later adoption of the project’s results on a wider scale. Rather than gathering cursory feedback and lamenting the challenges of retaining pilot subjects, investigators could instead embrace these challenges as a source of learning and engage in structured data collection to inform themselves about future implementation constraints and possibilities.
ü Adaptation could be seen as a potentially productive part of the scale-up process, offering opportunities to capture further data to inform further cycles of development.