Abstract Number:
3699
Submission Type:
Contributed Abstract
Contributed Abstract Type:
Speed
Participants:
Zaher Kmail (1), Betty Love (2), Michelle Friend (2), Becky Brusky (2), Julie Dierberger (2)
Institutions:
(1) University of Washington-Tacoma, N/A, (2) University of Nebraska-Omaha, NE
Co-Author(s):
First Author:
Presenting Author:
Abstract Text:
In Fall 2020, the University of Nebraska at Omaha (UNO) successfully introduced a general education quantitative literacy course fusing workforce-critical data science skills with service learning. Seeking to build on UNO's existing success, the University of Washington Tacoma (UWT) is creating their own version of the course for Spring 2024, with researchers collaborating to revise, implement, and assess it in both environments. At UNO, the proposed model contributed to increased data literacy among participants from a broad variety of majors by helping them develop fundamental mathematical, quantitative, and data literacy competencies in ways that are accessible and engaging, while increasing the capacity of local non-profit organizations to use data to answer meaningful questions to further their missions. We predict similar outcomes for UWT and its community, where we expect to find an increase in positive perceptions of mathematics and data science, particularly for non-STEM affiliated students who typically have lower interest and self-efficacy in mathematics and are often from groups underrepresented in STEM. Analysis of data collected at both institutions will be presented.
Keywords:
service learning|data literacy|community engagement|high impact practices|underrepresentation in STEM|data visualization and presentation
Sponsors:
Section on Statistics and Data Science Education
Tracks:
Miscellaneous
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