Rather Multifaceted than Disruptors: Exploring Gamification User Types of Crowdworkers

Abstract

Crowdsourcing allows individuals and organizations to outsource tasks to an anonymous group of individuals called crowdworkers, who are paid when completing the tasks. The quality of task results depends on factors like task complexity, task instruction quality, and crowdworker-related aspects, like their motivation towards the task. In this context, gamification, i.e., the use of game elements in non-ludic contexts, could foster the crowdworkers’ motivation besides monetary incentives. Nevertheless, identifying the audience’s gamification preferences is important to maintain their motivation in the long term. Although gamification has been used in crowdsourcing, to the best of our knowledge, it has not been based on crowdworkers’ preferences. The User Types HEXAD scale is suitable to identify those preferences and is designed explicitly for gamification. In our research, we investigated which HEXAD user types characterize crowdworkers. To aim this, we conducted a large-scale user study on two well-known crowdsourcing platforms, Amazon Mechanical Turk and Microworkers. Crowdworkers completed a demographic questionnaire, an image annotation task, and the HEXAD scale. The results show that crowdworkers are a multifaceted audience since all user types are exhibited. Therefore, we argue that one gamification approach might already satisfy a broad range for crowdworkers.

Keywords: Gamification, crowdsourcing, HEXAD user types, image annotation task

DOI: 10.54941/ahfe1002069