Crowdsourcing, cognitive load, and user interface design

Harnessing human computation through crowdsourcing offers a new approach to solving complex problems, especially those that are relatively easy for humans but difficult for computers. Micro-tasking platforms such as Amazon Mechanical Turk have attracted large, on-demand workforces of millions of workers as well as hundreds of thousands of job requesters. Achieving high quality results and minimizing the total task execution times are the two of the main goals of these crowdsourcing systems. Drawing on cognitive load theory and usability design principles, we study the effects of different user interface designs on performance and the latency of crowdsourcing systems. Our results indicate that complex and poorly designed user interfaces contributed to lower worker performance and increased task latency