457
Views
3
CrossRef citations to date
0
Altmetric
ARTICLES

COLLABORATIVE RESEARCH PARTNERSHIPS IN THE COMMUNITY

Digital Divas and Doing IT Better

, , , , , & show all
Pages 1081-1105 | Received 20 May 2011, Accepted 11 Jun 2012, Published online: 11 Jul 2012
 

Abstract

Working with community partners on research projects where the community members are part of the research team presents its own challenges. The challenges include the possible mismatch of expectations between academic team members and community members, as well as in defining the different roles people play, and managing the process. This paper reports the experiences and insights gained from working with community members involved in two research projects. The two projects were the Digital Divas project, involving the creation of a girls’ only information technology (IT) elective which has been implemented in a number of schools, and the Doing IT Better project that involved building IT capacity in the Victorian community service sector. Two community members from each of the projects are collaborators in this paper and provide the community perspective on this kind of research. Issues around concordances and discordances of academic research processes with a community's own ways of knowing, creating, managing and disseminating knowledge and information are discussed. The roles of community expertise, along with expectations regarding relationships and interactions are also explored.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 304.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.