Rationale awareness for quality assurance in iterative human computation processes
This research addresses the challenge of enhancing quality in iterative crowdsourcing processes, which is an incremental step in optimizing human computation for tasks requiring collaborative input.
The study investigated how making human workers aware of previous workers' rationales affects performance in iterative human computation tasks, such as brainstorming and rating, finding that rationale awareness can improve outcomes, though specific numerical results were not provided in the abstract.
Human computation refers to the outsourcing of computation tasks to human workers. It offers a new direction for solving a variety of problems and calls for innovative ways of managing human computation processes. The majority of human computation tasks take a parallel approach, whereas the potential of an iterative approach, i.e., having workers iteratively build on each other's work, has not been sufficiently explored. This study investigates whether and how human workers' awareness of previous workers' rationales affects the performance of the iterative approach in a brainstorming task and a rating task. Rather than viewing this work as a conclusive piece, the author believes that this research endeavor is just the beginning of a new research focus that examines and supports meta-cognitive processes in crowdsourcing activities.