CAREER: Enabling expert crowdsourcing via coordination, targeted contribution and education

职业：通过协调、有针对性的贡献和教育实现专家众包

• 批准号: 1351131
• 负责人: Michael Bernstein
• 金额: $ 55万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1351131&HistoricalAwards=false
• 关键词: CAREER; Enabling; expert; crowdsourcing; via

Crowdsourcing systems typically draw on the work of non-experts, as expert crowds are difficult to gather and coordinate. To extend the reach of crowdsourcing, this project investigates interactive systems, platforms and computational techniques to integrate experts as core participants of crowdsourcing systems. The project will develop and evaluate three related systems that improve the coordination, participation and education of expert crowds. First, the project will develop modular, composable workflows to guide paid expert crowds to accomplish complex tasks such as design and engineering. A second system seeks to attract a new form of expert participation by reaching out to experts in their spare moments. A final system will enable crowd workers to learn new skills by leveraging existing tasks as work-study opportunities. This research will produce three concrete types of results: 1) techniques and patterns for guiding expert crowds and their contributions, 2) scientific results and evaluations that depict the strengths and weaknesses of expert crowds, and 3) open, public platforms and systems to recruit, guide, and train members of expert crowds.Crowd work has the potential to employ millions of full-time workers and grant them the flexibility to guide their own careers. The proposed work advances a vision of how experts can engage in the future crowd-work economy, contribute to projects while improving their own skills, and be supported by practical knowledge and new sociotechnical systems. The project also includes a plan to use expert work-study techniques to provide realistic training in Stanford?s HCI curricula and develop a peer mentoring system to scale advising and informal learning.

众包系统通常利用非专家的工作，因为专家群体很难聚集和协调。为了扩大众包的范围，本项目研究了互动系统、平台和计算技术，以整合专家作为众包系统的核心参与者。该项目将开发和评价三个相关系统，以改善专家群体的协调、参与和教育。首先，该项目将开发模块化、可组合的工作流程，以指导付费专家群体完成设计和工程等复杂任务。第二个系统试图通过在业余时间接触专家来吸引新形式的专家参与。最终的系统将使人群工作者能够通过利用现有任务作为工作学习机会来学习新技能。这项研究将产生三种具体的结果：1）指导专家群体及其贡献的技术和模式，2）描述专家群体优势和劣势的科学结果和评估，3）开放的公共平台和系统，以招募，指导，群体工作有可能雇佣数百万全职工作者，并赋予他们指导自己职业的灵活性。拟议的工作提出了一个愿景，即专家如何参与未来的群体工作经济，在提高自身技能的同时为项目做出贡献，并得到实用知识和新的社会技术系统的支持。该项目还包括一个计划，使用专家工作学习技术，提供现实的培训，在斯坦福大学？的HCI课程，并开发一个同行指导系统，以规模的咨询和非正式学习。