Motivation Methods for Crowdsourcing Accessibility Attributes

Michaela Riganov√° Supervisor: Jan Balata Master thesis 2020
A key to online crowdsourcing platforms is a sufficient amount of high-quality data collected by users. Therefore it is essential to define motivation methods which would attract a large crowd and make it perform at a high level. In this thesis, we report on the results of our research focused on designing the most effective motivation methods for an online non-profit crowdsourcing platform focused on collecting accessibility data. Following the User-Centered Design methodology and based on the comprehensive analysis of the literature available, we have identified five main motivational factors and incorporated them into low-fidelity and high-fidelity prototypes of the mobile application. The prototypes were evaluated with the target group, the low-fidelity prototype via usability testing (N = 5, mean age = 27.6) and the high-fidelity prototype via diary study (N = 5, mean age = 27.2). The results suggest the feasibility of the approach supported by enhancing causal importance and perceived self-efficacy of users, providing them training and feedback on contributions, supporting a feeling of cooperation and allowing them to share data collection with friends.