Sprout: Crowd-Powered Task Design for Crowdsourcing

While crowdsourcing enables data collection at scale, ensuring high-quality data remains a challenge. In particular, effective task design underlies nearly every reported crowdsourcing success, yet remains difficult to accomplish. Task design is hard because it involves a costly iterative process: identifying the kind of work output one wants, conveying this information to workers, observing worker performance, understanding what remains ambiguous, revising the instructions, and repeating the process until the resulting output is satisfactory. To facilitate this process, we propose a novel meta-workflow that helps requesters optimize crowdsourcing task designs and SPROUT, our open-source tool, which implements this workflow. SPROUT improves task designs by (1) eliciting points of confusion from crowd workers, (2) enabling requesters to quickly understand these misconceptions and the overall space of questions, and (3) guiding requesters to improve the task design in response. We report the results of a user study with two labeling tasks demonstrating that requesters strongly prefer SPROUT and produce higher-rated instructions compared to current best practices for creating gated instructions (instructions plus a workflow for training and testing workers). We also offer a set of design recommendations for future tools that support crowdsourcing task design.