AI 中文总结
本研究提出并评估了用于监测非雇佣开发者效率的自适应纵向方法ADEMM，经27名开发者12个周期的混合方法研究验证，形成三项设计原则，可平衡监测的可比性、情境敏感性与实用性。
AI 中文摘要
背景：开发者效率受技术、组织、认知及沟通相关因素影响。然而，多数研究依赖一次性评估或固定工具，限制了对障碍随时间出现和变化的监测能力，尤其在咨询和专业教育场景中。目的：本研究提出并评估自适应开发者效率监测方法（Adaptive Developer Efficiency Monitoring Method，ADEMM），这是一种自适应纵向方法，用于监测监测组织未直接雇佣的开发者的效率。方法：遵循设计科学研究和行动设计研究，我们对27名软件开发者开展了为期12个调查周期的混合方法纵向研究。通过5个迭代周期设计并完善ADEMM，结合定期调查、18次半结构化访谈以及与问题所有者的联合评估。结果：本研究形成了ADEMM，该方法支持持续数据收集、混合方法整合以及监测工具的迭代重新设计。评估得出三项设计原则：基于可操作性与问题所有者确定优先级、结合封闭式与开放式数据收集、基于低方差和新兴定性信号调整条目。结论：ADEMM为开发者效率的自适应纵向监测提供了可迁移的方法，有助于在组织需支持开发者却不直接管控其工作环境的场景中，平衡可比性、情境敏感性与实用性。
英文摘要
Context: Developer efficiency is influenced by technical, organizational, cognitive, and communication-related factors. However, most studies rely on one-time assessments or fixed instruments, limiting the ability to monitor how barriers emerge and change over time, especially in consulting and professional education contexts. Objective: This study proposes and evaluates the Adaptive Developer Efficiency Monitoring Method (ADEMM), an adaptive longitudinal method for monitoring developer efficiency when the monitoring organization does not directly employ the developers. Method: Following Design Science Research and Action Design Research, we conducted a mixed-method longitudinal study with 27 software developers over twelve survey cycles. ADEMM was designed and refined through five iterative cycles, combining recurring surveys, 18 semi-structured interviews, and joint evaluation with a problem owner. Results: The study resulted in ADEMM, a method that supports continuous data collection, mixed-methods integration, and iterative redesign of monitoring instruments. The evaluation produced three design principles: prioritization with the problem owner based on actionability, combination of closed and open data collection, and adaptation of items based on low variance and emerging qualitative signals. Conclusions: ADEMM provides a transferable approach for adaptive longitudinal monitoring of developer efficiency. It helps balance comparability, contextual sensitivity, and practical utility in environments where organizations need to support developers without directly controlling their work contexts.
