HNDS-I: Pushkin: Enabling large-scale citizen science data collection for the social, behavioral, and economic sciences

该项目开发了一个名为Pushkin的免费开源软件平台，该平台允许对人类进行行为和认知实验的研究人员进行大规模的在线实验。 这些实验可以吸引来自世界各地的数万名参与者，并使公民科学家能够进行自己的实验。 同时从数百个实验中收集数据的能力提高了心理学和行为科学知识积累的速度，鲁棒性和可靠性。普希金基础设施降低了访问行为研究结果和参与行为研究的障碍，增加了研究人员和参与者的多样性，并促进了对广泛学科和背景的理解，包括社会和教育计划和政策，产品设计，治疗以及人工智能的培训和开发。即使对于那些已经进行了大量在线实验的研究人员来说，普希金也很难使用。该项目为Pushkin添加了功能，使其更易于使用。 添加的功能可以提高软件的学习能力，并使编写和部署实验更快。附加功能生成所收集数据的文档，包括自动生成的统计摘要。 该软件将促进在数据共享中使用最佳做法，这反过来又将提高研究人员共享数据的意愿，并为大规模在线实验产生的丰富数据集做出贡献。 这些数据集的共享将支持新的理论和行为模型的发展，并扩大社会科学研究的影响。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This project develops a free and open-source software platform named Pushkin, which permits researchers who conduct behavioral and cognitive experiments with humans to run massive online experiments. These experiments can engage tens of thousands of participants from around the world and enable citizen scientists to run their own experiments. The ability to collect data from hundreds of experiments simultaneously increases the rate, robustness, and reliability of knowledge accumulation in psychology and the behavioral sciences. The Pushkin infrastructure lowers barriers to accessing the results from and participating in behavioral research, increases the diversity of both researchers and participants, and advances understanding across a wide range of disciplines and contexts, including social and educational programs and policies, product design, therapies, and training and development of artificial intelligence. Pushkin is difficult to use even for those researchers who already conduct massive online experiments. The project adds functionality to Pushkin to make it easier to use. Features are added that improve learning the software and that make it faster to write and deploy experiments. Additional functionality generates documentation of the collected data, including automatically generated statistical summaries. The software will facilitate the use of best practices in data sharing, which in turn will increase researchers’ willingness to share data and contribute to the rich datasets produced by massive online experiments. Sharing of these datasets will support the development of new theories and models of behavior and broaden the impact of social science research.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.