微型叙事:一种可扩展的方法,以唤起人们生活经验的故事
Amira Skeggs1, Ashish Mehta2, Valerie Yap1
1MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom.
概括
这项研究引入了一种新的人工智能驱动的方法,用于大规模收集个人故事. 微叙事方法使得任何人都可以轻松分享他们的经验,帮助人机交互研究.
科学领域:
- 人与计算机的交互 (HCI)
- 定性研究方法 定性研究方法
- 在社会科学中的AI.
背景情况:
- 与生活经验互动对于有效的HCI研究和设计至关重要.
- 现有的方法可能会对不同人群的参与构成障碍.
- 需要可扩展的方法来收集丰富的,以用户为中心的数据.
研究的目的:
- 引入和评估一种新的"微叙事"诱导方法.
- 授权个人表达生活经验,无论写作技巧如何.
- 为了使HCI研究的大规模,共同创建的数据收集.
主要方法:
- 使用LLM链接来构建叙事表达的AI驱动原型的开发.
- 在3个混合方法研究中部署了380多名参与者.
- 与学者和非营利组织领导人进行商,以探索应用.
主要成果:
- 定性和定量数据表明该方法的可接受性和潜力.
- 人工智能工具有效地支了叙事创作过程.
- 确定了大规模部署的伦理和保护考虑因素.
结论:
- 微叙事方法提供了一个有前途的方法,在HCI中进行包容性,大规模的数据收集.
- 由人工智能驱动的工具可以显著降低参与用户研究的障碍.
- 仔细考虑道德方面的影响对于广泛采用至关重要.
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