Problem
Research questions and friction points this paper is trying to address.
cognitive diversity
problem-solving styles
developer needs
conversational programming assistants
individual differences
No Two Developers Think Alike: How Problem-Solving Styles and Experience Shape Needs in Conversational Interaction with Copilot
🤖 AI Summary
This study investigates the diverse needs and challenges that arise from cognitive differences among developers when interacting with AI-powered programming assistants. Employing a mixed-methods approach, the research integrates think-aloud protocols and quantitative analyses from 27 professional developers and students to systematically uncover how cognitive diversity influences human-AI collaborative programming. The work identifies five distinct interaction patterns and ten core user requirements, and proposes a conceptual model that elucidates how problem-solving styles and prior experience shape interaction behaviors. This framework offers both theoretical grounding and practical guidance for the design, research, and deployment of programming assistants that account for individual cognitive differences.
📝 Abstract
Conversational LLM-based ``programming assistants'' provide a range of benefits to developers. However, recent studies demonstrate the variety in individual developers' needs regarding programming assistants, and challenges encountered by only specific groups of developers. In this study, we explore the role of cognitive diversity in shaping interactions with GitHub Copilot chat. Through a mixed-methods think aloud study with 27 professional developers and students, we characterize 5 distinct ``interaction modes'' and 10 underlying needs in developers' interactions, forming a conceptual model. We characterize links between these modes, needs, and developers' problem-solving styles and experience profiles, showing how cognitive diversity may shape developers' interactions. We provide insights and recommendations for researchers and practitioners on how to design, research, and employ programming assistants to better account for diverse developer needs.
Innovation
Methods, ideas, or system contributions that make the work stand out.
cognitive diversity
interaction modes
problem-solving styles
programming assistants
developer needs
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