TY  - GEN
AB  - The recent rise in the performance and availability of large language models (LLMs) has fueled the adoption of generative artificial intelligence (AI) to support software engineering. Technologies such as Copilot and ChatGPT have become ubiquitous in software engineering, both in academic and professional settings. Nevertheless, the effects of such technologies on how engineers collaborate to build software are relatively unknown, raising questions regarding the impact they have on computer-supported collaborative work (CSCW). To explore these effects, we conducted a within-subjects empirical case study with 24 undergraduate software engineering students. Students were divided into seven groups, completing four brainstorming tasks related to a software engineering project for a course on frontend development. For each group, two of the tasks were supported by LLM-powered bots, while the other two tasks did not include bots. Our findings show that when the brainstorming process was supported by bots, students proposed significantly fewer ideas and reported significantly less sense of authorship and sense of responsibility with respect to the ideas selected. These results motivate the need for frameworks to guide how software engineers collaborate with AI-powered technologies.
AD  - EPFL, Lausanne, Switzerland
AD  - EPFL, Lausanne, Switzerland
AD  - School of Engineering and Architecture (HEIA-FR), HES-SO University of Applied Sciences and Arts Western Switzerland
AD  - EPFL, Lausanne, Switzerland
AU  - Farah, Juan Carlos
AU  - La Scala, Jérémy
AU  - Ingram, Sandy
AU  - Gillet, Denis
DA  - 2025-04
ID  - 15226
JF  - Proceedings of the 6th International Workshop on Bots in Software Engineering (BotSE), 27 April 2025, Ottawa, Canada
KW  - software engineering
KW  - bots
KW  - large language models
KW  - education
KW  - brainstorming
KW  - CSCW
L1  - https://arodes.hes-so.ch/record/15226/files/Farah_2025_supporting_brainstorming_activities_bots_software_engineering_education_POSTPRINT.pdf
L2  - https://arodes.hes-so.ch/record/15226/files/Farah_2025_supporting_brainstorming_activities_bots_software_engineering_education_POSTPRINT.pdf
L4  - https://arodes.hes-so.ch/record/15226/files/Farah_2025_supporting_brainstorming_activities_bots_software_engineering_education_POSTPRINT.pdf
LA  - eng
LK  - https://arodes.hes-so.ch/record/15226/files/Farah_2025_supporting_brainstorming_activities_bots_software_engineering_education_POSTPRINT.pdf
LK  - http://botse.org/
N2  - The recent rise in the performance and availability of large language models (LLMs) has fueled the adoption of generative artificial intelligence (AI) to support software engineering. Technologies such as Copilot and ChatGPT have become ubiquitous in software engineering, both in academic and professional settings. Nevertheless, the effects of such technologies on how engineers collaborate to build software are relatively unknown, raising questions regarding the impact they have on computer-supported collaborative work (CSCW). To explore these effects, we conducted a within-subjects empirical case study with 24 undergraduate software engineering students. Students were divided into seven groups, completing four brainstorming tasks related to a software engineering project for a course on frontend development. For each group, two of the tasks were supported by LLM-powered bots, while the other two tasks did not include bots. Our findings show that when the brainstorming process was supported by bots, students proposed significantly fewer ideas and reported significantly less sense of authorship and sense of responsibility with respect to the ideas selected. These results motivate the need for frameworks to guide how software engineers collaborate with AI-powered technologies.
PY  - 2025-04
T1  - Supporting brainstorming activities with bots in software engineering education
TI  - Supporting brainstorming activities with bots in software engineering education
UR  - https://arodes.hes-so.ch/record/15226/files/Farah_2025_supporting_brainstorming_activities_bots_software_engineering_education_POSTPRINT.pdf
UR  - http://botse.org/
VL  - 2025
Y1  - 2025-04
ER  -