DevCoach: Supporting Students Learning the Software Development Life Cycle with a Generative AI powered Multi-Agent System

The software development life cycle (SDLC) is vital for ensuring the quality of software systems. However, learning SDLC concepts presents unique challenges, such as the need for effective collaboration, real-time interaction, and access to diverse skill sets represented in software development teams. To address these problems, we present DevCoach, a generative AI powered multi-agent system designed to support students learning the SDLC. DevCoach allows students to interact with generative AI agents simulating the different roles in the software development team, engaging in tasks across different phases of SDLC. Through a user study (n = 20), we evaluate the system's effectiveness in enhancing learning, impact on SDLC deliverables, and support for Community of Inquiry (CoI) elements necessary for effective and supportive learning environments. Our results reveal that students using DevCoach achieved significantly higher learning gains and improved task completion rates across all SDLC phases. The system also supports CoI elements, particularly perceived social presence. Participants also lauded the immediate context-aware feedback, interactive learning environment, and diverse expertise provided by the roles within the multi-agent team. These findings demonstrate the potential of generative AI to enhance software engineering education by making it more effective, engaging, and interactive, providing students with collaborative and practical learning experiences.

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Published
2025-06-23
DOI
https://doi.org/10.1145/3696630.3727255
Primary Topic
Software Engineering Techniques and Practices
Type
article
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article

DevCoach: Supporting Students Learning the Software Development Life Cycle with a Generative AI powered Multi-Agent System

Chris Brown, Tianjia Wang, Matthew Trimble
Software Engineering Techniques and Practices
article

DevCoach: Supporting Students Learning the Software Development Life Cycle with a Generative AI powered Multi-Agent System

Chris Brown, Tianjia Wang, Matthew Trimble
article en

Abstract

The software development life cycle (SDLC) is vital for ensuring the quality of software systems. However, learning SDLC concepts presents unique challenges, such as the need for effective collaboration, real-time interaction, and access to diverse skill sets represented in software development teams. To address these problems, we present DevCoach, a generative AI powered multi-agent system designed to support students learning the SDLC. DevCoach allows students to interact with generative AI agents simulating the different roles in the software development team, engaging in tasks across different phases of SDLC. Through a user study (n = 20), we evaluate the system's effectiveness in enhancing learning, impact on SDLC deliverables, and support for Community of Inquiry (CoI) elements necessary for effective and supportive learning environments. Our results reveal that students using DevCoach achieved significantly higher learning gains and improved task completion rates across all SDLC phases. The system also supports CoI elements, particularly perceived social presence. Participants also lauded the immediate context-aware feedback, interactive learning environment, and diverse expertise provided by the roles within the multi-agent team. These findings demonstrate the potential of generative AI to enhance software engineering education by making it more effective, engaging, and interactive, providing students with collaborative and practical learning experiences.

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Software Engineering Techniques and Practices
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DevCoach: Supporting Students Learning the Software Development Life Cycle with a Generative AI powered Multi-Agent System — Chris Brown, Tianjia Wang, et al. · (2025) | TGRS Research Map | TGRS