Th-22: Students' perspectives on entering a data science career after experiential learning with local community organizations


By Vimal Rao, Chelsey Legacy, & Andrew Zieffler (University of Minnesota)


Abstract

The NSF-funded DSC WAV project (HDF DSC-1923700) provides students experiential learning opportunities. It simultaneously supports community-based and non-profit organizations to harness the Data Science revolution at the local level. We interviewed the first cohort of students completing the project, and conducted preliminary analyses of notes and transcripts from interviews to answer the following question: What are students’ perspectives on entering a Data Science career after participating in the project? Adopting a Social Cognitive Career Theory framework, we identified three themes in students’ descriptions in which the WAV experience helped them to: (1) form outcome expectations by providing a realistic view of what Data Science work entails; (2) identify which aspects of Data Science work they are good at and which aspects they like (i.e., develop self-efficacy and interests); and (3) make specific career goals. These results suggest that experiential learning can greatly impact students’ Data Science career choices.


Recording

Th-22 - Students' perspectives on entering a data science career after experiential learning with local community organizations.pdf