Amazon 's Mechanical Turk ( M Turk ) Essay
Introduction The present study was an initial test for an online version of the road salting task. There was a potential concern that the advantage of numeric uncertainty was only restricted to population that had always been used as participants: young adults with some college education. Would other populations benefit from numeric uncertainty information as well? Additionally, all previous data had been collected in a laboratory setting with an experimenter monitoring task progress and preventing any outside distractions. Indeed, relative to traditional laboratory environment, many aspects of the online testing environment are not under the experimenter 's control. Participants could be distracted by simultaneously completing other online tasks or attending to other aspects of their environment. It is unsurprising that unsupervised subjects tend to be less attentive than subjects in a lab with an experimenter (Oppenheimer, Meyvis, & Davidenko, 2009). Would this affect road salting responses? The online testing environment used for this project was Amazon's Mechanical Turk (M–Turk). The M–Turk is a platform for thousands of response tasks covering a wide range of topics. Respondents complete tasks for small monetary rewards. Evidence suggests that M–Turk samples are reliable and reasonably representative of the general public and data quality does not seem affected by payment amount (Buhrmester, Kwang, & Gosling, 2011; Mason & Watts, 2009; Paolacci, Chandler, & Ipeirotis,
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