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

Published online by Cambridge University Press:  06 October 2014

Amber E. Boydstun
Affiliation:
University of California, Davis
Jessica T. Feezell
Affiliation:
University of New Mexico
Rebecca A. Glazier
Affiliation:
University of Arkansas, Little Rock
Timothy P. Jurka
Affiliation:
University of California, Davis
Matthew T. Pietryka
Affiliation:
Florida State University

Abstract

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.

Type
Features
Copyright
Copyright © American Political Science Association 2014 

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