Online Archive of University of Virginia Scholarship
Software Developing: Automating with Low-Code Solutions; Responding to the Threat They Created: Software Engineers and Automated Software Development138 views
Author
Shin, Andrew, School of Engineering and Applied Science, University of Virginia
Advisors
Norton, Peter, EN-Engineering and Society, University of Virginia
Vrugtman, Rosanne, EN-Comp Science Dept, University of Virginia
Abstract
How can computer science programs better prepare their students for careers transformed by cheap, abundant and powerful artificial intelligence? With a successful answer to this problem, universities can better prepare their graduates and elevate their own programs’ stature.
How can an informative automation course better prepare undergraduate students for rapidly evolving careers in STEM? University curricula typically do not offer students opportunities to learn about the social implications of artificial intelligence or how to use AI in assignments, preferring to discourage its usage by default. An introductory course can prepare students in all fields to use AI effectively and responsibly. Such a course was developed and prototyped through curriculum analysis and student interviews. Future researchers can improve the proposed course and offer it to university departments for experimental implementation.
In the US since 2020, how have entry-level software engineers adapted as AI tools evolve and modify software development? As AI tools proliferate, software engineers need a strong foundation in critical reasoning and ethics to manage their implications. Curricula in higher education must offer students this foundation. Being prepared for the adoption of artificial intelligence is paramount to determine the role AI will have within our future.
Shin, Andrew. Software Developing: Automating with Low-Code Solutions; Responding to the Threat They Created: Software Engineers and Automated Software Development. University of Virginia, School of Engineering and Applied Science, BS (Bachelor of Science), 2024-05-09, https://doi.org/10.18130/x8kn-h873.
