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Research Spending & Results

Award Detail

Awardee:UNIVERSITY OF MAINE SYSTEM
Doing Business As Name:University of Maine
PD/PI:
  • Nicholas Giudice
  • (207) 581-2187
  • nicholas.giudice@maine.edu
Award Date:04/01/2021
Estimated Total Award Amount: $ 303,549
Funds Obligated to Date: $ 303,549
  • FY 2021=$303,549
Start Date:06/01/2021
End Date:05/31/2025
Transaction Type:Grant
Agency:NSF
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.076
Primary Program Source:045176 H-1B FUND, EHR, NSF
Award Title or Description:Collaborative Research: Creating and testing data science learning tools for secondary students with disabilities
Federal Award ID Number:2048394
DUNS ID:186875787
Parent DUNS ID:071750426
Program:ITEST-Inov Tech Exp Stu & Teac
Program Officer:
  • M. Alejandra Sorto
  • (703) 292-2934
  • msorto@nsf.gov

Awardee Location

Street:5717 Corbett Hall
City:ORONO
State:ME
ZIP:04469-5717
County:Orono
Country:US
Awardee Cong. District:02

Primary Place of Performance

Organization Name:University of Maine
Street:
City:Orono
State:ME
ZIP:04469-5717
County:Orono
Country:US
Cong. District:02

Abstract at Time of Award

The main goal of this collaborative project is to create and evaluate a universally accessible data science infrastructure for high-school-aged learners, with a focus on students with disabilities. Data science is critical in the development of industry-relevant computational thinking skills. Computing initiatives, including data science, are rapidly growing at the preschool-12th grade level because of the compelling career pathways that data science skills provide. A careful investigation into already-at-scale data science initiatives shows that such tools and curriculum are largely not accessible to individuals with disabilities, nor do they have a strong foundation of human factors evidence supporting their designs. These issues are crucial and must be resolved for workforce equity and a diverse science, technology, engineering, and mathematics (STEM) pipeline. This project will bring together investigators in computer science, mechanical engineering, education, social science, and cognitive neuroscience to rethink the tools that support the teaching and learning of data science at the high school level. The overarching goal will be to create and evaluate data science tools and curriculum that are not just in legal compliance for accessibility, but that carefully take into account the needs of learners, including those with disabilities. This project will involve numerous strategic partnerships including two schools for students with disabilities, the Disabilities, Opportunities, Internetworking, and Technology Center, and an engaged advisory board representing computing accessibility (AccessComputing), data science industry (RStudio), and data science governance (Association for Computing Machinery Data Science Task Force). The rigorous research plan will include iterative, user-focused development, empirical quantitative investigations, qualitative focus groups, and a culminating in-classroom field study, targeting an estimated total of 385 students, 105 teachers, and 30 industry professionals as participants across all studies. By creating, deploying, and rigorously evaluating the first data science tool and curriculum that is accessible to all, the project intends to help create equitable pathways for all students to enter the field of data science. This project is funded by the Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers. 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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