five

Metadata record for the doctoral dissertation “Mood-Focused Design: An Integrative Exploration”

收藏
4TU.ResearchData2025-10-30 更新2026-04-23 收录
下载链接:
https://data.4tu.nl/datasets/a11987f2-7027-496c-9399-660c8d062257/1
下载链接
链接失效反馈
官方服务:
资源简介:
This is a metadata-only record for Zhuochao Peng's doctoral dissertation, <em>Mood-Focused Design: An Integrative Exploration</em>.<br>The dissertation seeks to develop a comprehensive understanding of mood-focused design through integrating perspectives from design researchers, design practitioners, and the author and collaborators as researcher-designers. Its main contributions include (1) articulating conceptual archetypes of mood-focused design, (2) revealing pragmatic orientations when incorporating mood in real-world projects, and (3) providing situated examples and considerations for engaging with mood in everyday contexts.<br>Three qualitative datasets were collected and generated during the doctoral research:(1) Design professional interviews: 20 transcripts from interviews with experience-driven design practitioners in the Netherlands and Finland.(2) Employee focus groups: 52 diary entries from 26 employees in the Netherlands, along with 6 transcripts from focus group discussions on experiences of the “Sunday Blues.”(3) User evaluation studies: 45 transcripts from interviews with potential users engaging with mood-regulation interventions.<br>No research data are available for public access. The data are of a sensitive nature, and participants did not provide written consent for their data to be published or shared publicly.

本条目仅为彭卓超博士学位论文《情绪聚焦设计:整合性探索》(Mood-Focused Design: An Integrative Exploration)的元数据记录。 本论文旨在整合设计研究学者、设计从业者以及作为研究-设计者的作者与合作者的视角,全面深化对情绪聚焦设计的认知。其主要研究贡献包括:(1)阐明情绪聚焦设计的概念原型;(2)揭示在实际项目中融入情绪考量时的实践导向;(3)提供在日常情境中应对情绪的情境化案例与实践要点。 本博士研究期间共收集并生成三类定性数据集:(1)设计从业者访谈:包含对荷兰与芬兰的经验驱动型设计从业者的访谈转录稿共20份;(2)员工焦点小组:包含荷兰26名员工的52篇工作日志,以及针对“周日忧郁情绪”体验的焦点小组讨论转录稿6份;(3)用户评估研究:包含对参与情绪调节干预方案的潜在用户的访谈转录稿共45份。 本研究数据集暂不对外开放。该数据集涉及敏感内容,且参与人员未签署数据公开出版或共享的书面同意书。
创建时间:
2025-10-30
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作