Survey on Agile Practices and Technology Adoption

This dataset contains survey responses collected from Agile practitioners across various roles, including Scrum Masters, Developers, Product Owners, and Agile Coaches, from organizations with diverse Agile practices. The survey aimed to identify the common challenges in backlog refinement, such as time constraints, prioritization issues, and ambiguous user stories. It also explored perceptions of Generative AI's role in streamlining Agile workflows, enhancing productivity, and reducing cognitive load. The dataset forms the basis of the study, *"Enhancing Agile Backlog Refinement with Generative AI: An Empirical Study,"* which proposes actionable frameworks for safely integrating AI into backlog refinement practices while preserving Agile principles.

本数据集汇聚了来自不同角色（包括敏捷大师、开发者、产品负责人和敏捷教练）的敏捷实践者的调查反馈，这些角色分布于采用多样化敏捷实践的组织中。该调查旨在揭示在待办事项精炼过程中普遍存在的挑战，例如时间限制、优先级问题以及模糊的用户故事。此外，调查还探讨了对于生成式 AI 在简化敏捷工作流程、提升生产力和降低认知负荷中所扮演角色的看法。该数据集构成了研究《利用生成式 AI 提升敏捷待办事项精炼：一项实证研究》的基础，该研究提出了在保持敏捷原则的同时，安全地将 AI 集成到待办事项精炼实践中的可操作框架。