Online Archive of University of Virginia Scholarship
Computer Science Education: Synthesis of the Curricula of Data Structures and Algorithms; Analysis of Algorithmic Bias and its Interaction with Society233 views
Author
Chitre, Mark, School of Engineering and Applied Science, University of Virginia
Advisors
Wayland, Kent, EN-Engineering and Society, University of Virginia
Vrugtman, Rosanne, EN-Comp Science Dept, University of Virginia
Laugelli, Benjamin, EN-Engineering and Society, University of Virginia
Abstract
The topic of the technical work is the combination of two classes in the UVA curriculum that would enhance the learning experience for prospective students. The two classes are CS 2110 and CS 4102, essentially putting the general topics of data structures and algorithms together and creating a curriculum that synthesizes the information presented in that class. The STS topic addresses the idea of algorithmic bias in computer science and how algorithms can be trained to include unintentional biases. My technical and STS projects both address aspects of the socio-technical problem of how algorithms are taught and used and how they can have detrimental implications if done incorrectly. In what follows, I will demonstrate through both the technical project (changing how algorithms are taught) and the STS project (analyzing algorithmic bias through the lens of cases, socio-technical framework, journals) how the field of computer science can be improved in this specific aspect.
Chitre, Mark. Computer Science Education: Synthesis of the Curricula of Data Structures and Algorithms; Analysis of Algorithmic Bias and its Interaction with Society. University of Virginia, School of Engineering and Applied Science, BS (Bachelor of Science), 2022-05-12, https://doi.org/10.18130/61c6-nn41.
