Colleague Crowdsourcing: A Method for Incentivizing National Student Engagement and Large-N Data Collection

Abstract

This paper details our participant recruitment efforts as part of a research project studying individual-level, real-time reactions to the 2012 presidential debates. As researchers interested in examining debate effects as conditioned by key variables such as party identification and race, we wanted a large and diverse sample of respondent data, well beyond what we would be able to achieve by drawing on student participants from any single campus. As educators, we wanted to take the opportunity of this study to engage students in the electoral process. Our solution: crowdsourcing the political science community. Using an incentive package including teaching materials and promised next-day preliminary results from our study, we encouraged colleagues across the country to register their classes, offering incentives in turn to their students for participating. Our crowdsourcing approach yielded a dataset large enough and diverse enough to support hypothesis testing across even rare combinations of variables, such as African American Republicans. What is more, of the nearly 5,000 students across the country who viewed the presidential debates as part of our study, there were surely many who otherwise would not have watched.