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A Statistical Analysis of Drop Rates in Introductory Computer Science by Gender and Partial Grade

Authors:

Jikai Long,

Brian HarringtonAuthors Info & Claims

WCCCE '19: Proceedings of the 24th Western Canadian Conference on Computing Education

Article No.: 13, Pages 1 - 2

https://doi.org/10.1145/3314994.3325081

Published: 03 May 2019 Publication History

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Abstract

University level introductory computer science courses have a notoriously high drop rate. Many students who aim to pursue CS education fail to complete their first semester. This trend holds across a wide variety of institutions, courses, and countries. In this study, we collect data from over 4000 students enrolled in an introductory course over a 5 year period in order to analyze potential factors that affect which students are more likely to drop the course. In particular, this work focuses on gender, international student status, and course performance up to the drop date.

The data for each student includes performance on assignments and term tests as well as weekly exercises which allow us to create a temporal view of students and analyze their partial grade at the time they stopped participating in the course. We find that there are slight differences in the probabilities of dropping for lower performing students by gender, the results are not statistically significant. Furthermore, we find virtually no difference in students who, up to the drop date, are receiving passing marks by either gender or international student status.

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Andrew Petersen, Michelle Craig, Jennifer Campbell, and Anya Tafliovich. 2016. Revisiting why students drop CS1. In Proceedings of the 16th Koli Calling International Conference on Computing Education Research. ACM, 71--80.

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Cited By

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Kovaleva YKasurinen JKindsiko EHapponen A(2024)State-of-the-Art Review on Current Approaches to Female Inclusiveness in Software Engineering and Computer Science in Higher EducationIEEE Access10.1109/ACCESS.2023.334676712(1360-1373)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2023.3346767
Devathasan KKepler JWarawa JPenney ATsui IBerg C(2023)PrairieLearn in CS1: An Experience ReportProceedings of the 25th Western Canadian Conference on Computing Education10.1145/3593342.3593344(1-2)Online publication date: 4-May-2023
https://dl.acm.org/doi/10.1145/3593342.3593344
Calver JCampbell JCraig MLam JMerkle LDoyle MSheard JSoh LDorn B(2022)The Impact of Optional Groups on StudentsProceedings of the 53rd ACM Technical Symposium on Computer Science Education - Volume 110.1145/3478431.3499286(829-835)Online publication date: 22-Feb-2022
https://dl.acm.org/doi/10.1145/3478431.3499286

Index Terms

A Statistical Analysis of Drop Rates in Introductory Computer Science by Gender and Partial Grade
1. Social and professional topics
  1. Professional topics
    1. Computing education
      1. Computing education programs
        Computer science education
        CS1

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WCCCE '19: Proceedings of the 24th Western Canadian Conference on Computing Education

May 2019

79 pages

ISBN:9781450367158

DOI:10.1145/3314994

Editor:
Ben Stephenson

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 the author(s) 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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UOC: University of Calgary

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Association for Computing Machinery

New York, NY, United States

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Published: 03 May 2019

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WCCCE '19: Western Canadian Conference on Computing Education

May 3 - 4, 2019

AB, Calgary, Canada

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WCCCE '19 Paper Acceptance Rate 15 of 29 submissions, 52%;

Overall Acceptance Rate 78 of 117 submissions, 67%

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Kovaleva YKasurinen JKindsiko EHapponen A(2024)State-of-the-Art Review on Current Approaches to Female Inclusiveness in Software Engineering and Computer Science in Higher EducationIEEE Access10.1109/ACCESS.2023.334676712(1360-1373)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2023.3346767
Devathasan KKepler JWarawa JPenney ATsui IBerg C(2023)PrairieLearn in CS1: An Experience ReportProceedings of the 25th Western Canadian Conference on Computing Education10.1145/3593342.3593344(1-2)Online publication date: 4-May-2023
https://dl.acm.org/doi/10.1145/3593342.3593344
Calver JCampbell JCraig MLam JMerkle LDoyle MSheard JSoh LDorn B(2022)The Impact of Optional Groups on StudentsProceedings of the 53rd ACM Technical Symposium on Computer Science Education - Volume 110.1145/3478431.3499286(829-835)Online publication date: 22-Feb-2022
https://dl.acm.org/doi/10.1145/3478431.3499286

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Recommendations

Drop, Fail, Pass, Continue: Persistence in CS1 and Beyond in Traditional and Inverted Delivery

Updating Introductory Computer Science with Creative Computation

Examining the Enrollment Growth: Non-CS Majors in CS1 Courses

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