Philip Guo (Phil Guo, Philip J. Guo, Philip Jia Guo, pgbovine)

End-User Programmers Repurposing End-User Programming Tools to Foster Diversity in Adult End-User Programming Education

research paper summary
End-User Programmers Repurposing End-User Programming Tools to Foster Diversity in Adult End-User Programming Education. Sean Kross and Philip J. Guo. IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 2019.
Efforts to improve diversity in computing have mostly focused on K-12 and university student populations, so there is a lack of research on how to provide these benefits to adults who are not in school. To address this knowledge gap, we present a case study of how a nine-member team of end-user programmers designed an educational program to bring job-relevant computing skills to adult populations that have traditionally not been reached by existing efforts. This team conceived, implemented, and delivered Cloud Based Data Science (CBDS), a data science course designed for adults in their local community in historically marginalized groups that are underrepresented in computing fields. Notably, nobody on the course development team was a full-time educator or software engineer. To reduce the amount of time and cost required to launch their program, they repurposed end-user programming skills and tools from their professions, such as data-analytic programming and reproducible scientific research workflows. This case study demonstrates how the spirit of end-user programming can be a vehicle to drive social change through grassroots efforts.
@inproceedings{KrossVLHCC2019,
  author={Kross, Sean and Guo, Philip J.},
  title={End-User Programmers Repurposing End-User Programming Tools to Foster Diversity in Adult End-User Programming Education},
  booktitle = {Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)},
  series = {VL/HCC '19},
  year={2019},
  month={Oct}
}

(summary written by Sean Kross)

Short version: Philip Guo and I wrote a paper about how a team of data scientists built their own software tools for making, maintaining, and iterating on an educational program they designed to help adults from historically marginalized populations to start their data science careers. [...]

read the rest of this summary on Sean's webpage

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