research-article

A Comparative Analysis of GitHub Contributions Before and After An OSS Based Software Engineering Class

Authors:

Edward GehringerAuthors Info & Claims

ITiCSE 2024: Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 1

Pages 576 - 582

https://doi.org/10.1145/3649217.3653535

Published: 03 July 2024 Publication History

ITiCSE 2024: Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 1

A Comparative Analysis of GitHub Contributions Before and After An OSS Based Software Engineering Class

Pages 576 - 582

Abstract
References

Abstract

This study presents a comparative analysis of contributions to GitHub by students before and after participating in a Software Engineering class based on Open Source Software (OSS). The primary objective is to understand the influence of formal software engineering education on students' engagement in OSS projects, as reflected in their GitHub activities. The research addresses two key questions. Firstly, it examines how GitHub contributions change before and after the class. The corresponding hypothesis posits that students' average GitHub contributions will exhibit a distinct pattern post-class compared to pre-class. Additionally, the study explores the potential association between students' academic performance in the class and their level of GitHub contributions after the class. The strength and direction of the potential association are quantified using the Spearman correlation coefficient, considering the potential non-linear nature of the data. This analysis uses data from over 1000 students across more than 10 years, encompassing their GitHub contribution data over multiple timeframes and their grades in the class. The study employs a combination of statistical methods, including paired tests and correlation analysis, to explore these dynamics. While causality cannot be established due to the absence of a control group, the findings offer valuable insights into the correlation between academic engagement and practical contributions in the realm of OSS development. This research contributes to the understanding of how theoretical software engineering education might relate to practical application and engagement in real-world projects.

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Cited By

Cui JZhou FLiu CJia QSong YGehringer EMonga MLonati VBarendsen ESheard JPaterson J(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
https://dl.acm.org/doi/10.1145/3649217.3653634
Cui JZhang RJia QZhou FLi RGehringer E(2024)A Statistical Study of Female Students in a Software Engineering Class: Preparedness, Performance, and Contribution2024 IEEE Frontiers in Education Conference (FIE)10.1109/FIE61694.2024.10893315(1-9)Online publication date: 13-Oct-2024
https://doi.org/10.1109/FIE61694.2024.10893315
Cui JZhang RZhou FLi RSong YGehringer E(2024)How Much Effort Do You Need to Expend on a Technical Interview? A Study of LeetCode Problem Solving Statistics2024 36th International Conference on Software Engineering Education and Training (CSEE&T)10.1109/CSEET62301.2024.10663022(1-10)Online publication date: 29-Jul-2024
https://doi.org/10.1109/CSEET62301.2024.10663022

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cover image ACM Conferences

ITiCSE 2024: Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 1

July 2024

776 pages

ISBN:9798400706004

DOI:10.1145/3649217

General Chairs:
Mattia Monga
University of Milan, Italy
,
Violetta Lonati
University of Milan, Italy
,
Erik Barendsen
Radboud University, The Netherlands
,
Program Chairs:
Judithe Sheard
Monash University, Australia
,
James Paterson
Glasgow Caledonian University, Scotland

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Published: 03 July 2024

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ITiCSE 2024: Innovation and Technology in Computer Science Education

July 8 - 10, 2024

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Overall Acceptance Rate 552 of 1,613 submissions, 34%

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Cited By

Cui JZhou FLiu CJia QSong YGehringer EMonga MLonati VBarendsen ESheard JPaterson J(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
https://dl.acm.org/doi/10.1145/3649217.3653634
Cui JZhang RJia QZhou FLi RGehringer E(2024)A Statistical Study of Female Students in a Software Engineering Class: Preparedness, Performance, and Contribution2024 IEEE Frontiers in Education Conference (FIE)10.1109/FIE61694.2024.10893315(1-9)Online publication date: 13-Oct-2024
https://doi.org/10.1109/FIE61694.2024.10893315
Cui JZhang RZhou FLi RSong YGehringer E(2024)How Much Effort Do You Need to Expend on a Technical Interview? A Study of LeetCode Problem Solving Statistics2024 36th International Conference on Software Engineering Education and Training (CSEE&T)10.1109/CSEET62301.2024.10663022(1-10)Online publication date: 29-Jul-2024
https://doi.org/10.1109/CSEET62301.2024.10663022

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