New Orleans, Louisiana
June 26, 2016
June 26, 2016
June 29, 2016
978-0-692-68565-5
2153-5965
Pathways to Success in STEM through Computer Science and Making
Minorities in Engineering
Diversity
11
10.18260/p.26110
https://peer.asee.org/26110
4097
Dr. Nicki Washington is an Associate Professor in the Department of Computer Science and Quantitative Methods at Winthrop University in Rock Hill, SC. Prior to this, she was an Associate Professor in the Department of Computer Science at Howard University in Washington, DC.
She received a B.S. in Computer Science from Johnson C. Smith University and a M.S. and Ph.D. in Computer Science from North Carolina State University.
Her research interests include the use of culturally-relevant pedagogy to increase the participation and performance of underrepresented students in computer science.
Dr. Sudipta Dasmohapatra is an associate professor in analytics at the Institute for Advanced Analytics at NC State University, Raleigh, NC. The Institute was pivotal in creating the nation’s first Masters in Advanced Analytics program. She also holds a joint appointment in the Department of Forest Biomaterials in the College of Natural Resources at the university. Dr. Dasmohapatra's research focuses on the application of analytical models for solutions to environmental problems. In addition to mentoring PhD and MS students, Dr. Dasmohapatra annually advises about 20 student teams working on industry sponsored advanced analytics projects.
As computer science continues to permeate every aspect of society, the number of students of color adequately prepared for, choosing to pursue, and successfully completing computer science (CS) undergraduate programs is still dismal. CS education research has focused heavily on understanding why students of color don’t pursue computer science and identifying better ways to instruct, retain, and engage them. While there are several tools that measure student interest in, knowledge of, and attitude towards CS, there are none that assess the direct impact of ethnic identity on their perceptions of the field and decisions to pursue it.
To this extent, the Computer Science Cultural Attitude and Identity Survey (CSAIS) was developed to measure five important constructs that influence the attitudes and identity of undergraduate students of color in computer science: confidence, interest, gender, professional, and identity. The tool currently targets freshmen and sophomores either entering the university as first-time college students or enrolling in their first CS course. It was validated using current and former computer science students of color. The results indicated that the tool, specifically the identity construct, is a valid and reliable measure of ethnic identity in relation to CS.
Washington, A. N., & Grays, S., & Dasmohapatra, S. (2016, June), The Computer Science Attitude and Identity Survey (CSAIS): A Novel Tool for Measuring the Impact of Ethnic Identity in Underrepresented Computer Science Students Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana. 10.18260/p.26110
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