LLMs Integration in Software Engineering Team Projects: Roles, Impact, and a Pedagogical Design Space for AI Tools in Computing Education
Ahmed Kharrufa, Sami Alghamdi, Abeer Aziz, Christopher Bull·October 30, 2024
Summary
The study examines the integration of generative AI (GenAI) models in software engineering team projects, focusing on student perspectives. Through surveys and interviews, it assesses the impact of GenAI on coding, learning, and self-efficacy. Key findings highlight GenAI's role in teamwork, team dynamics, and learning, proposing a design space for AI-based programming tools. The research addresses a gap in understanding GenAI's implications in computing education, emphasizing the importance of transparency and considering AI's roles in the learning process.
Introduction
Background
Overview of generative AI (GenAI) models
Current state of AI in software engineering
Importance of understanding AI's role in computing education
Objective
To explore the integration of GenAI models in software engineering team projects from a student perspective
To assess the impact of GenAI on coding, learning, and self-efficacy
To propose a design space for AI-based programming tools
Method
Data Collection
Surveys targeting software engineering students
Interviews with students using GenAI in team projects
Data Preprocessing
Analysis of survey responses
Transcription and coding of interview data
Findings
Role of GenAI in Teamwork and Team Dynamics
Impact on collaboration and communication
Influence on team roles and responsibilities
Effect on Coding and Learning
Changes in coding practices
Learning outcomes and self-efficacy improvements
Implications for AI-based Programming Tools
Design considerations for AI integration
Recommendations for tool development
Discussion
Transparency in AI Use
Importance of clear communication about AI usage
Strategies for enhancing transparency in AI applications
AI's Role in the Learning Process
Balancing AI support with human learning
Considerations for AI's educational impact
Conclusion
Summary of Key Findings
Recap of the study's main insights
Implications for Education and Research
Recommendations for future studies
Practical applications for educators and AI developers
Future Directions
Opportunities for further exploration in AI integration
Potential areas for addressing gaps in current research
Basic info
papers
software engineering
artificial intelligence
Advanced features
Insights
How does the research propose a design space for AI-based programming tools and address the gap in understanding GenAI's implications in computing education?
How does the study assess the impact of GenAI on coding, learning, and self-efficacy?
What are the key findings regarding GenAI's role in teamwork, team dynamics, and learning?
What is the main focus of the study on generative AI (GenAI) models in software engineering team projects?