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How Twincode Measures Gender Bias in Remote Pair Programming Environmentsby@pairprogramming

How Twincode Measures Gender Bias in Remote Pair Programming Environments

by Pair Programming TechnologySeptember 15th, 2024
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Twincode, a remote pair programming platform, supports the study of gender bias in collaborative coding by managing student registration, random pairing, exercise assignment, and automatic collection of interaction data.
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Abstract and 1 Introduction

1.1 The twincode platform

1.2 Related Work

2 Research Questions

3 Variables

3.1 Independent Variables

3.2 Dependent Variables

3.3 Confounding Variables

4 Participants

5 Execution Plan and 5.1 Recruitment

5.2 Training and 5.3 Experiment Execution

5.4 Data Analysis

Acknowledgments and References

1.1 The twincode platform

To support our study, we have developed the twincode remote pair programming platform, which manages the registration of students, the random allocation to gender-balanced groups, the random allocation into pairs, the random assignment of programming exercises to pairs, and the automatic collection of interaction metrics and dialog messages.


As shown in Figure 1, twincode offers a source code editor where the students concurrently develop the solution to a proposed exercise and can validate it against several test cases. It also offers a chat window, where they can collaborate to solve the exercise. Note that a gendered avatar is displayed for the student in the experimental group only (right), but not for the one in the control group (left).


Authors:

(1) Amador Durán, SCORE Lab, I3US Institute, Universidad de Sevilla, Sevilla, Spain ([email protected]);

(2) Pablo Fernández, SCORE Lab, I3US Institute, Universidad de Sevilla, Sevilla, Spain ([email protected]);

(3) Beatriz Bernárdez, I3US Institute, Universidad de Sevilla, Sevilla, Spain ([email protected]);

(4) Nathaniel Weinman, Computer Science Division, University of California, Berkeley, Berkeley, CA, USA ([email protected]);

(5) Aslı Akalın, Computer Science Division, University of California, Berkeley, Berkeley, CA, USA ([email protected]);

(6) Armando Fox, Computer Science Division, University of California, Berkeley, Berkeley, CA, USA ([email protected]).


This paper is available on arxiv under CC BY 4.0 DEED license.