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Taking the Next Course: Barriers and Facilitators Reported by Computer Science Majors

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Conference

2023 ASEE Annual Conference & Exposition

Location

Baltimore , Maryland

Publication Date

June 25, 2023

Start Date

June 25, 2023

End Date

June 28, 2023

Conference Session

Computer Science Education and AI research

Tagged Division

Educational Research and Methods Division (ERM)

Tagged Topic

Diversity

Page Count

15

DOI

10.18260/1-2--44398

Permanent URL

https://peer.asee.org/44398

Download Count

113

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Paper Authors

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Amari N. Lewis University of California San Diego

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Dr. Amari N. Lewis is a Postdoctoral scholar in the Department of Computer Science and Engineering at the University of California San Diego. Her research currently explores Computer Science and Engineering education. She earned her Bachelor's of science in Computer Science from Winston-Salem State University and earned her Master's of Science and Doctorate from the University of California, Irvine.

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Mia Minnes University of California, San Diego

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Mia Minnes is an Associate Teaching Professor and the Vice-Chair for Undergraduate Education in the Computer Science and Engineering Department at UC San Diego. In addition to research related to Automata Theory and Computability education, she works on projects that support professionalization pathways for students, including industry internships, TA development, and ethics and communication. Her research and teaching have work has been supported by grants and awards from UC San Diego, NSF, and industry partners.

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Kristen Vaccaro University of California San Diego

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Kristen Vaccaro is an Assistant Professor of Computer Science & Engineering at the University of California San Diego, where she is also a member of the Design Lab. Her research focuses on designing the user experience of machine learning systems, particularly in social computing contexts.

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Joe Gibbs Politz University of California San Diego

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Joe Gibbs Politz is an Associate Teaching Professor of Computer Science & Engineering at University of California San Diego. His research interests and experience include programming languages and systems as well as education for computer science and adjacent fields. He teaches broadly across the computer science curriculum with a focus on introductory programming and programming languages, and develops tools for teaching computing in both collegiate and secondary school settings. When not programming or teaching, he goes to the dog beach.

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Abstract

This research paper studies barriers to students continuing in undergraduate computing programs. On the journey to a computing profession, every course has the potential to be an off-ramp away from students’ goals. Every student who leaves a computing degree has a last class they took before not continuing, and a reason they didn’t continue. Based on qualitative analysis of open-ended questions in surveys of students in eight undergraduate computer science and engineering (CSE) courses, we identify common barriers students anticipate, and learn what encourages them to persist onto the next CSE course. For example, even for students within the major, a commonly reported barrier was the perceived inability to enroll in their next computing course due to unclear enrollment systems and requirements. We disaggregate the data by three demographic categories—race/ethnicity, gender, and admissions-type—to understand potential disparate impacts of CSE majors at our large, research- intensive university. Solutions to the reported barriers faced by students may include student-focused interventions, policy and programmatic changes at the department level, and broader institutional or external support. Keywords: 5.b.vii. Computer science, 10.f. Retention, 3. Diversity

Lewis, A. N., & Minnes, M., & Vaccaro, K., & Politz, J. G. (2023, June), Taking the Next Course: Barriers and Facilitators Reported by Computer Science Majors Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--44398

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