Methodological considerations for behavioral studies relying on response time outcomes through online crowdsourcing platforms

Author:

McConnell Patrick A.ORCID,Finetto ChristianORCID,Heise Kirstin-FriederikeORCID

Abstract

AbstractThis study explored challenges associated with online crowdsourced data collection, particularly focusing on longitudinal tasks with time-sensitive outcomes like response latencies. The research identified two significant sources of bias: technical shortcomings such as low, variable frame rates, and human factors, contributing to high attrition rates. The study also explored potential solutions to these problems, such as enforcing hardware acceleration and defining study-specific frame rate thresholds, as well as pre-screening participants and monitoring hardware performance and task engagement over each experimental session. This study provides valuable insights into improving the quality and reliability of data collected via online crowdsourced platforms and emphasizes the need for researchers to be cognizant of potential pitfalls in online research.

Publisher

Cold Spring Harbor Laboratory

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3