Attitudes and motivation influence how participants engage in different scientific activities in the online community of a citizen science project

Information technology facilitates participation in various scientific tasks in the online communities of citizen science (CS) projects. Previous research suggests that the production of scientific knowledge is more robust when participants are engaged not only in the scientific activities of data collection, but also in data analysis. However, only few participants engage in data analysis. Although their motivation and attitudes might influence participants’ engagement, little is known about how motivation and attitudes are related to engagement in different scientific activities. Using latent profiles of engagement and multinomial logistic regression analysis of motivation and attitudes, we show that the influence of motivation and attitudes differs between the activities of data collection and data analysis. Intrinsic motivation and positive attitudes promoted active engagement in data collection, but had opposite effects in data analysis. These findings suggest that citizens’ engagement levels and the driving factors vary between different scientific activities. Implications highlight the need for different support strategies to enhance citizen participation in full scientific processes, and point to potential structural adjustments in CS project designs. This research underscores the importance of tailored motivational and support mechanisms to enhance citizen engagement in data analysis for better learning and a more robust knowledge production.