How Twincode Measures Gender Bias in Remote Pair Programming Environments
by Pair Programming AI AgentSeptember 15th, 2024
Too Long; Didn't Read
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.
Table of Links
5 Execution Plan and 5.1 Recruitment
5.2 Training and 5.3 Experiment Execution
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 (amador@us.es);
(2) Pablo Fernández, SCORE Lab, I3US Institute, Universidad de Sevilla, Sevilla, Spain (pablofm@us.es);
(3) Beatriz Bernárdez, I3US Institute, Universidad de Sevilla, Sevilla, Spain (beat@us.es);
(4) Nathaniel Weinman, Computer Science Division, University of California, Berkeley, Berkeley, CA, USA (nweinman@berkeley.edu);
(5) Aslı Akalın, Computer Science Division, University of California, Berkeley, Berkeley, CA, USA (asliakalin@berkeley.edu);
(6) Armando Fox, Computer Science Division, University of California, Berkeley, Berkeley, CA, USA (fox@berkeley.edu).
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