人类-人工智能编程角色优化：开发一种以个性驱动的自我决定框架
Human-AI Programming Role Optimization: Developing a Personality-Driven Self-Determination Framework
AI总结：
本研究提出基于人格特质的自我决定理论框架，通过设计科学方法优化人类与AI协作角色，提升团队动态和动机水平。
摘要：
随着人工智能改变软件开发，一个关键问题浮现：开发者和人工智能系统如何最有效地协作？本论文通过自我决定理论和人格心理学优化人类-人工智能编程角色，引入了角色优化动机对齐（ROMA）框架。通过为期五轮的设计科学研究，本研究建立了人格特质、编程角色偏好和协作成果之间的实证验证联系，参与了200名实验参与者和46名访谈受访者。关键发现表明，以人格驱动的角色优化显著提高了自我决定和团队动态，使专业人员的平均动机增加23%，本科生则增加高达65%。五种不同的个性原型出现：探索者（高开放性/低宜人性）、协调者（高外向性/宜人性）、工匠（高神经质/低外向性）、建筑师（高尽责性）和适应者（平衡型）。每种都表现出对编程角色（共 pilot、共导航者、代理）的不同偏好，角色分配模式对满意度至关重要。本论文贡献：（1）一个实证验证的框架，将人格特质与角色偏好和自我决定结果联系起来；（2）一种映射到人格轮廓的AI协作模式分类法，同时保持人类自主性；（3）一个ISO/IEC 29110扩展，使Very Small Entities能够在现有标准内实施基于个性的角色优化。
英文摘要：
As artificial intelligence transforms software development, a critical question emerges: how can developers and AI systems collaborate most effectively? This dissertation optimizes human-AI programming roles through self-determination theory and personality psychology, introducing the Role Optimization Motivation Alignment (ROMA) framework. Through Design Science Research spanning five cycles, this work establishes empirically-validated connections between personality traits, programming role preferences, and collaborative outcomes, engaging 200 experimental participants and 46 interview respondents. Key findings demonstrate that personality-driven role optimization significantly enhances self-determination and team dynamics, yielding 23% average motivation increases among professionals and up to 65% among undergraduates. Five distinct personality archetypes emerge: The Explorer (high Openness/low Agreeableness), The Orchestrator (high Extraversion/Agreeableness), The Craftsperson (high Neuroticism/low Extraversion), The Architect (high Conscientiousness), and The Adapter (balanced profile). Each exhibits distinct preferences for programming roles (Co-Pilot, Co-Navigator, Agent), with assignment modes proving crucial for satisfaction. The dissertation contributes: (1) an empirically-validated framework linking personality traits to role preferences and self-determination outcomes; (2) a taxonomy of AI collaboration modalities mapped to personality profiles while preserving human agency; and (3) an ISO/IEC 29110 extension enabling Very Small Entities to implement personality-driven role optimization within established standards. Keywords: artificial intelligence, human-computer interaction, behavioral software engineering, self-determination theory, personality psychology, phenomenology, intrinsic motivation, pair programming, design science research, ISO/IEC 29110
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
