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

  • Amber E. Boydstun (a1), Jessica T. Feezell (a2), Rebecca A. Glazier (a3), Timothy P. Jurka (a4) and Matthew T. Pietryka (a5)...

Scholars often rely on student samples from their own campuses to study political behavior, but some studies require larger and more diverse samples than any single campus can provide. In our case, we wanted to study the real-time effects of presidential debates on individual-level attitudes, and we sought a large sample with diversity across covariates such as ideology and race. To address this challenge, we recruited college students across the country through a process we call “colleague crowdsourcing.” As an incentive for colleagues to encourage their students to participate, we offered teaching resources and next-day data summaries. Crowdsourcing provided data from a larger and more diverse sample than would be possible using a standard, single-campus subject pool. Furthermore, this approach provided classroom resources for faculty and opportunities for active learning. We present colleague crowdsourcing as a possible model for future research and offer suggestions for application in varying contexts.

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PS: Political Science & Politics
  • ISSN: 1049-0965
  • EISSN: 1537-5935
  • URL: /core/journals/ps-political-science-and-politics
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