UAZ Data and Community Science: Getting minoritized undergraduates into the field of Data Science for Public Interest
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Keywords
public interest technology,
Internship,
PIT,
community technology,
technology community,
internship,
workshop,
data & analytics , Educational Opportunities , MSI , HSI
Project
Authors
Picoral, Adriana
Date Submitted
7/1/23
Material Type
Student Support Materials
Secondary Material Type
Program Planning Resources
Institution
University of Arizona
Industry Partner
License
CC BY-NC-ND
Funding Source
Network Challenge Grant TAACCCT Round 3
Abstract
In Spring 2022 we put together the internship position ad to recruit applicants. We received more than 50 applications for the positions. Candidate materials were reviewed, and candidates were interviewed. Our final 4 interns came from various backgrounds: 1) local male hispanic sophomore student majoring in information, 2) a female senior student majoring in computer science, 3) an electrician’s apprentice transferring from the local community college to the University of Arizona as a computer science major, 3) a female sophomore student majoring in information technology. All 4 students were enrolled at the University of Arizona. In Spring 2023 we
were also able to meet with local organizations that had shareable data available for the summer internship projects. Two projects were set up for the internship, with specifications coming from the data stakeholders: 1) Water Pool Classifier, with data consisting of pictures taken of a waterpool with the goal of examining the water
levels in the region, and 2) Tucson Bird Count, with data consisting of bird observation reports from a crowd-sourced app. The 8-week internship started in June 2022, and interns met weekly with the Graduate mentor and myself (sometimes in the same meeting, at times in separate meetings, depending on the interns’ needs and
what stage of their project they were on). The full schedule of the internship can be found in our public GitHub repository. A pre-internship survey and post-internship interviews were used to collect data on the interns’ experiences. They reported needing to develop data analysis skills, machine learning techniques, and professional
development skills at the beginning of their internship. All participants reported feeling they had achieved their development goals at the end of their internship, and that the experience surpassed their expectations.
Industry (NAISC)
Public Interest Technology -- Data -- Algorithms
Occupation (SOC)
Computer and Mathematical Occupations -- Mathematical Technicians (15-2091)
Instructional Program (CIP)
Computer and Information Sciences and Support Services (11)
Credit Type
Credential Type
Associate Degree
Bachelors Degree
Bachelors Degree
Educational Level
Skill Level
Intermediate Level