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Comparing Traditional and Crowdsourcing Methods for Pretesting Survey Questions

Author

Listed:
  • Jennifer Edgar
  • Joe Murphy
  • Michael Keating

Abstract

Cognitive interviewing is a common method used to evaluate survey questions. This study compares traditional cognitive interviewing methods with crowdsourcing, or “tapping into the collective intelligence of the public to complete a task.†Crowdsourcing may provide researchers with access to a diverse pool of potential participants in a very timely and cost-efficient way. Exploratory work found that crowdsourcing participants, with self-administered data collection, may be a viable alternative, or addition, to traditional pretesting methods. Using three crowdsourcing designs (TryMyUI, Amazon Mechanical Turk, and Facebook), we compared the participant characteristics, costs, and quantity and quality of data with traditional laboratory-based cognitive interviews. Results suggest that crowdsourcing and self-administered protocols may be a viable way to collect survey pretesting information, as participants were able to complete the tasks and provide useful information; however, complex tasks may require the skills of an interviewer to administer unscripted probes.

Suggested Citation

  • Jennifer Edgar & Joe Murphy & Michael Keating, 2016. "Comparing Traditional and Crowdsourcing Methods for Pretesting Survey Questions," SAGE Open, , vol. 6(4), pages 21582440166, October.
    • Handle: RePEc:sae:sagope:v:6:y:2016:i:4:p:2158244016671770
    DOI: 10.1177/2158244016671770
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    Citations

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    Cited by:

    1. Lidon Moliner & Francisco Alegre, 2020. "Effects of peer tutoring on middle school students’ mathematics self-concepts," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-17, April.
    2. Murphy Joe & Biemer Paul & Berry Chip, 2018. "Transitioning a Survey to Self-Administration using Adaptive, Responsive, and Tailored (ART) Design Principles and Data Visualization," Journal of Official Statistics, Sciendo, vol. 34(3), pages 625-648, September.
    3. Holzberg Jessica & Ellis Renee & Kaplan Robin & Virgile Matt & Edgar Jennifer, 2019. "Can They and Will They? Exploring Proxy Response of Sexual Orientation and Gender Identity in the Current Population Survey," Journal of Official Statistics, Sciendo, vol. 35(4), pages 885-911, December.
    4. Trejo Yazmín García & Meyers Mikelyn & Martinez Mandi & O’Brien Angela & Goerman Patricia & Class Betsarí Otero, 2022. "Identifying Data Quality Challenges in Online Opt-In Panels Using Cognitive Interviews in English and Spanish," Journal of Official Statistics, Sciendo, vol. 38(3), pages 793-822, September.
    5. Cynthia Weiyi Cai & Jennifer Gippel & Yushu Zhu & Abhay Kumar Singh, 2019. "The power of crowds: Grand challenges in the Asia-Pacific region," Australian Journal of Management, Australian School of Business, vol. 44(4), pages 551-570, November.
    6. Regina Lenart-Gansiniec & Wojciech Czakon & Łukasz Sułkowski & Jasna Pocek, 2023. "Understanding crowdsourcing in science," Review of Managerial Science, Springer, vol. 17(8), pages 2797-2830, November.

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