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Quantifying the Benefits of Prior Programming Experience in an Introductory Computer Science Course

Published: 21 February 2018 Publication History

Abstract

The superior performance of students with prior exposure to programming has long been evident to faculty that teach introductory courses. In this paper we replicate previous studies that quantify the difference between students with and without previous programming experience, and we provide further focus on gender differences. Our research is based on an initial CS1 course that we divided into a section with students having previous programming experience (P) and two sections for students without (N). Both sections of CS1 were taught with the same curriculum and assessments. We find that the advantages of prior experience are substantial, with P students outscoring N students by more than 6% on exams and 10% on programming quizzes. However, the performance gap between P and N students narrows considerably by the end of the following CS2 course, with no significant difference in overall scores. Analyzing results by gender, our data shows that 22% of N students in CS1 are female versus only 12% of P students. However, the female students with prior exposure outperform their male peers in all areas. Another finding of our research is the confirmation of a significant difference in confidence between female and male students.

References

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Sylvia Beyer, Kristina Rynes, Julie Perrault, Kelly Hay, and Susan Haller. 2003. Gender Differences in Computer Science Students. Proc. of the 34th SIGCSE Technical Symposium on Computer Science Education (SIGCSE '03). ACM, New York, NY, USA, 49--53.
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  1. Quantifying the Benefits of Prior Programming Experience in an Introductory Computer Science Course

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    cover image ACM Conferences
    SIGCSE '18: Proceedings of the 49th ACM Technical Symposium on Computer Science Education
    February 2018
    1174 pages
    ISBN:9781450351034
    DOI:10.1145/3159450
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 21 February 2018

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    Author Tags

    1. CS1
    2. CS2
    3. broadening participation
    4. previous experience

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    SIGCSE '18 Paper Acceptance Rate 161 of 459 submissions, 35%;
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    • (2024)Student Transitions Through an Entire Computing ProgramProceedings of the 26th Western Canadian Conference on Computing Education10.1145/3660650.3660661(1-7)Online publication date: 2-May-2024
    • (2024)Utilizing the Constrained K-Means Algorithm and Pre-Class GitHub Contribution Statistics for Forming Student TeamsProceedings of the 2024 on Innovation and Technology in Computer Science Education V. 110.1145/3649217.3653634(569-575)Online publication date: 3-Jul-2024
    • (2024)How Pre-class Programming Experience Influences Students' Contribution to Their Team Project: A Statistical StudyProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630870(255-261)Online publication date: 7-Mar-2024
    • (2024)Examining Intention to Major in Computer Science: Perceived Potential and ChallengesProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630843(1237-1243)Online publication date: 7-Mar-2024
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    • (2024)Applying CS0/CS1 Student Success Factors and Outcomes to Biggs' 3P Educational ModelProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630781(1168-1174)Online publication date: 7-Mar-2024
    • (2024)How self-beliefs, values, and belonging change and relate with performance during introductory computer scienceComputer Science Education10.1080/08993408.2024.2429058(1-37)Online publication date: 24-Nov-2024
    • (2024)Understanding resilience in programming: A scale adaptation and analysis of individual differencesEducation and Information Technologies10.1007/s10639-024-13086-zOnline publication date: 11-Oct-2024
    • (2023)Game-Based Learning for Students’ Computational Thinking: A Meta-AnalysisJournal of Educational Computing Research10.1177/0735633123117894861:7(1430-1463)Online publication date: 14-Jun-2023
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