Document Type
Conference Proceeding
Department
Computer Science (HMC)
Publication Date
3-3-2023
Abstract
Despite an increasing number of successful interventions designed to broaden participation in computing research, there is still significant attrition among historically marginalized groups in the computing research pipeline. This experience report describes a first-of-its-kind Undergraduate Consortium (UC; https://aaai-uc.github.io/about) that addresses this challenge by empowering students with a culmination of their undergraduate research in a conference setting. The UC, conducted at the AAAI Conference on Artificial Intelligence (AAAI), aims to broaden participation in the AI research community by recruiting students, particularly those from historically marginalized groups, supporting them with mentorship, advising, and networking as an accelerator toward graduate school, AI research, and their scientific identity. This paper presents our program design, inspired by a rich set of evidence-based practices, and a preliminary evaluation of the first years that points to the UC achieving many of its desired outcomes. We conclude by discussing insights to improve our program and expand to other computing communities.
Rights Information
© 2023 James C Boerkoel and Mehmet Ergezer
Terms of Use & License Information
This work is licensed under a Creative Commons Attribution 4.0 License.
DOI
10.1145/3545945.3569841
Recommended Citation
James Boerkoel and Mehmet Ergezer. 2023. An Undergraduate Consortium for Addressing the Leaky Pipeline to Computing Research. In Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 (SIGCSE 2023). Association for Computing Machinery, New York, NY, USA, 687–693. https://doi.org/10.1145/3545945.3569841
Included in
Computer Sciences Commons, Higher Education Commons, Other Feminist, Gender, and Sexuality Studies Commons
Comments
Originally published in Proceedings of the 54th ACM Technical Symposium on Computer Science Education, Vol. 1, by the Association for Computing Machinery, 2023.