The arc of scientific research points towards an ever-growing universe of new automated scientific-data collection instruments, increasing the amount and variety of data. Virtual citizen science projects are a popular method for addressing the deluge of data generated by such instruments and facilitate collaboration on large-scale scientific research between professional scientists and amateur volunteers. Learning and motivation are two critical areas of research dictating the success of virtual citizen projects. Since most citizen scientists are amateur volunteers with little knowledge about the technical infrastructure supporting their participation or the science subject matter, insights into how citizen scientists acquire procedural knowledge, technical competence, and learn the subject matter is essential.
In this talk, I present results from ongoing research studies documenting and assessing volunteer learning and motivation in virtual citizen science projects. In documenting human experiences, the studies I present will focus on how a volunteers’ engagements with a site’s socio-technical resources dictate how (1) people acquire procedural knowledge, (2) enhance participation, (3) compensate for lack of learning materials, and are motivated to contribute to projects. Beyond learning and motivation, I will discuss several projects under development, including ongoing efforts to facilitate human-machine collaboration and examinations of how citizen science artifacts impact scientific practice.