Table of Links
2. Contexts, Methods, and Tasks
3.1. Quality and 3.2 Productivity
5. Discussion and Future Work
5.1. LLM, Your pAIr Programmer?
5.2. LLM, A Better pAIr Programmer?
5.3. LLM, Students’ pAIr Programmer?
6. Conclusion, Acknowledgments, and References
4.4 Collaboration
How well partners collaborate have been important factors that affect pair programming effectiveness [4, 79], and cooperative behavior and positive interdependence are key to pair programming success [67].
Collaboration can fail in various ways in a human-human pair. For example, the free-rider problem, where the entire workload is on one partner while the other remains a marginal player, can result in less satisfaction and learning [57, 87]. In human-AI pair programming, educators are worried that easily available code-generation tools may lead to cheating, and over-reliance on AI may hinder students learning [10]. However, no study has formally evaluated it.
For human-human pair programming, there is a suggested collaboration pattern of role-switching – two software developers periodically and regularly switch between writing code (driver) and suggesting code (navigator), aiming to ensure that both are engaged in the task and alleviate the physical and cognitive load borne by the driver [5, 65].
Some researchers Freudenberg et al. [24] argue that the success of pair programming should be attributed to communication rather than “the differences in behavior or focus between the driver and navigator,” as they found both driver and navigator worked on similar levels of abstraction. Nevertheless, instructors still recommend drivers and navigators to regularly alternate roles to ensure equitable learning experiences [83].
In human-AI interaction, given Copilot’s amazing capability to write code in different languages, some have argued that Copilot can take on the role of the “driver” in pair programming, allowing a solo programmer to take on the role of the “navigator” and focus on understanding the code at a higher level [35]. However, while it is possible for humans to offload some API lookup and syntax details to Copilot, humans still need to jump back into the driver’s seat frequently and fluidly switch between the thinking and writing activities [53]. It is ultimately the human programmer’s sole responsibility to understand code at the statement level [72].
Authors:
(1) Qianou Ma (Corresponding author), Carnegie Mellon University, Pittsburgh, USA ([email protected]);
(2) Tongshuang Wu, Carnegie Mellon University, Pittsburgh, USA ([email protected]);
(3) Kenneth Koedinger, Carnegie Mellon University, Pittsburgh, USA ([email protected]).
This paper is
