Document Type
Abstract
Publication Date
2020
Publisher
Association for Computing Machinery
Source Publication
SIGCSE '20: Proceedings of the 51st ACM Technical Symposium on Computer Science Education
Source ISSN
978-1-4503-6793-6
Abstract
COSMIC is an NSF S-STEM graduate curriculum initiative/conversion program that strives to provide an accelerated pathway to a Master of Science (MS) degree for individuals who do not have an undergraduate degree in computing, but who wish to cross over into the computing field. The structure of our conversion program, the context that motivated it, and insights from conversion students' instructors are presented. Program successes with students from under-represented populations and the limitations that are also experienced are discussed. Our conversion program is based on a highly focused summer bridge course, combined with a customized curriculum pathway that enables people without undergraduate computing degrees to merge quickly and efficiently into a professional MS in computing degree program. The program is similar in concept to post-baccalaureate conversion programs in New Zealand (e.g., the Master of Software Development at the Victoria University of Wellington) and the extensive conversion choices in the UK. Undergraduate and graduate student enrollment statistics from past and current (2018) CRA Taulbee Surveys strongly suggest the computing profession has a moral obligation to seek out and encourage individuals from under-represented populations to become a significant part of the computing professional community. We encourage other institutions to join in the effort to recruit and provide pathways for post-baccalaureate individuals from under-represented populations to become a significant part of the computing community.
Recommended Citation
Krenz, Gary S. and Kaczmarek, Thomas, "COSMIC: US-based Conversion Master's Degree in Computing" (2020). Mathematical and Statistical Science Faculty Research and Publications. 40.
https://epublications.marquette.edu/math_fac/40
ADA Accessible poster
krenz_14119abstract.pdf (193 kB)
Abstract
krenz_14119abstractacc.docx (30 kB)
ADA Accessible abstract
Comments
Published version. SIGCSE '20: Proceedings of the 51st ACM Technical Symposium on Computer Science Education, 2020: 1277. DOI. © 2020 Copyright held by the owner/authors. Used with permission.