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Research Spending & Results

Award Detail

Doing Business As Name:Hawaii Pacific University
  • Brenda A Jensen
  • (808) 544-0200
  • Sharon S Nelson-Barber
  • Kimberly A Scott
Award Date:09/10/2019
Estimated Total Award Amount: $ 299,833
Funds Obligated to Date: $ 349,793
  • FY 2019=$299,833
  • FY 2020=$49,960
Start Date:09/15/2019
End Date:08/31/2021
Transaction Type:Grant
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.070
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:CISE EAGER: Developing a Collective Impact Model with and for Native Hawaiian and Pacific Islander Girls to Persist in Computer Science
Federal Award ID Number:1947319
DUNS ID:072498132
Parent DUNS ID:072498132
Program:CISE Education and Workforce
Program Officer:
  • Fay Cobb Payton
  • (703) 292-7939

Awardee Location

Street:1164 Bishop Street, Suite 1500
Awardee Cong. District:01

Primary Place of Performance

Organization Name:Hawaii Pacific University
Cong. District:01

Abstract at Time of Award

While there are many computer science initiatives for girls of color (Native Hawaiian, Alaskan Native, African American, Latinx), they often share a constraint. Specifically, many of these programs use culturally responsive activities, which encourage community activism and have been shown to inspire girls to see themselves as entering computer-related fields, they often employ highly-general theoretical frameworks that are designed to apply to several cultural communities in a multitude of geographic regions. But in practice, cultures, needs, and assets differ in important ways across communities and regions, so activities that work for African American girls in the US Southeast might not also work for Native Hawaiians, for instance. Without empirically validated theories and frameworks focused on specific regions and cultures, program developers, researchers, and funding agencies cannot make informed decisions as to how computer science can be for all. Particularly for Native Hawaiian and other Indigenous communities, few solutions have been offered or framed in any substantive way. Instead, theories such as Indigenous Knowledge Systems and Culturally Responsive Computing remain detached from computer science endeavors. A collective impact model for programs focused on specific communities and cultures is needed, yet there is limited understanding of what this means for computer science, girls of color, and Native Hawaiian girls, in particular. This two-year project aims to explore what is needed to identify which elements can be used to bridge that gap. A research team that spans disciplines and geographic regions will apply two theories (Indigenous Knowledge Systems and Culturally Responsive Computing) and create a series of research opportunities to explore which features can constitute a collective impact model. Scholars from Hawai'i Pacific University, Arizona State University, and WestEd will use a particular methodology, Critical Indigenous Research Methodologies (CIRM). Along with a cultural liaison and advisory board, adolescent (13 to 18) Native Hawaiian, Alaskan Native, African American, and Latina girls will play critical roles as researchers. The approach uses systems mapping as a tool that allows the girls to assess the system, identifying interactions and connections that both promote and prevent existing and future opportunities for success in computer science and technology. The tool establishes an opportunity for intergenerational discussions, goals, and strategies to be developed based on these findings and enables real time adaptation, learning, and action to support collective impact. The potential for this project is significant. If successful, findings will advance theoretical and pedagogical development of curriculum and activities that intersect technology experiences with girls' of color cultural identities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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