The STARS Alliance: Viable Strategies for Broadening Participation in Computing

  • Authors:
  • Teresa Dahlberg;Tiffany Barnes;Kim Buch;Audrey Rorrer

  • Affiliations:
  • University of North Carolina at Charlotte;University of North Carolina at Charlotte;University of North Carolina at Charlotte;University of North Carolina at Charlotte

  • Venue:
  • ACM Transactions on Computing Education (TOCE)
  • Year:
  • 2011

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Abstract

The Students and Technology in Academia, Research, and Service (STARS) Alliance is a nationally-connected system of regional partnerships among higher education, K-12 schools, industry and the community with a mission to broaden the participation of women, under-represented minorities and persons with disabilities in computing (BPC). Each regional partnership is led by a STARS member college or university with partners such as local chapters of the Girl Scouts, the Black Data Processors Association, public libraries, Citizen Schools, and companies that employ computing graduates. STARS goals include retaining and graduating undergraduates and recruiting and bridging undergraduates into graduate programs. The alliance works toward these goals through activities that advance the central values of Technical Excellence, Leadership, Community, and Service and Civic Engagement. In particular, all STARS college and university members implement the STARS Leadership Corps (SLC), an innovative model for enveloping a diverse set of BPC practices within a common framework for implementation within multiple organizations, common assessment, and sustainability through curricula integration. Herein, we describe the SLC model and its implementation in the STARS schools, including details of an SLC service-learning course that has been adopted by eight STARS schools. We report the results of our three-year study of the SLC in the 20 STARS schools. Our study found a positive effect of participation in the SLC on important student success variables, including self-efficacy, perceived social relevance of computing, grade point average, and commitment to remain in computing. Results indicate that the SLC model is effective for students under-represented in computing, as well as for those not from under-represented groups.