Exploring the effects of non-monetary reimbursement for participants in HCI research

Sarah Wiseman, Anna L. Cox, Sandy J. J. Gould, Duncan P. Brumby
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引用次数: 2

Abstract

When running experiments within the field of Human Computer Interaction (HCI) it is common practice to ask participants to come to a specified lab location, and reimburse them monetarily for their time and travel costs. This, however, is not the only means by which to encourage participation in scientific study. Citizen science projects, which encourage the public to become involved in scientific research, have had great success in getting people to act as sensors to collect data or to volunteer their idling computer or brain power to classify large data sets across a broad range of fields including biology, cosmology and physical and environmental science. This is often done without the expectation of payment. Additionally, data collection need not be done on behalf of an external researcher; the Quantified Self (QS) movement allows people to reflect on data they have collected about themselves. This too, then, is a form of non-reimbursed data collection. Here we investigate whether citizen HCI scientists and those interested in personal data produce reliable results compared to participants in more traditional lab-based studies. Through six studies, we explore how participation rates and data quality are affected by recruiting participants without monetary reimbursement: either by providing participants with data about themselves as reward (a QS approach), or by simply requesting help with no extrinsic reward (as in citizen science projects). We show that people are indeed willing to take part in online HCI research in the absence of extrinsic monetary reward, and that the data generated by participants who take part for selfless reasons, rather than for monetary reward, can be as high quality as data gathered in the lab and in addition may be of higher quality than data generated by participants given monetary reimbursement online. This suggests that large HCI experiments could be run online in the future, without having to incur the equally large reimbursement costs alongside the possibility of running experiments in environments outside of the lab.
探索非货币补偿对HCI研究参与者的影响
在人机交互(HCI)领域进行实验时,通常的做法是要求参与者到指定的实验室地点,并补偿他们的时间和旅行费用。然而,这并不是鼓励学生参与科学研究的唯一手段。鼓励公众参与科学研究的公民科学项目已经取得了巨大的成功,它让人们充当传感器来收集数据,或者自愿将他们空闲的计算机或脑力用于对包括生物学、宇宙学、物理和环境科学在内的广泛领域的大型数据集进行分类。这通常是在不期望付款的情况下完成的。此外,数据收集不需要代表外部研究人员进行;量化自我(QS)运动允许人们反思他们收集的关于自己的数据。因此,这也是一种无偿收集数据的方式。在这里,我们调查公民HCI科学家和那些对个人数据感兴趣的人是否与更传统的基于实验室的研究参与者相比产生可靠的结果。通过六项研究,我们探索了在没有金钱补偿的情况下招募参与者是如何影响参与率和数据质量的:要么通过向参与者提供关于他们自己的数据作为奖励(QS方法),要么通过简单地请求帮助而没有外部奖励(如公民科学项目)。我们的研究表明,人们确实愿意在没有外在金钱奖励的情况下参与在线HCI研究,而那些出于无私原因而不是金钱奖励的参与者所产生的数据,可以与实验室收集的数据一样高质量,而且可能比在线获得金钱补偿的参与者所产生的数据质量更高。这表明,大型HCI实验将来可以在线运行,而不必承担同样大的报销费用,同时也可以在实验室外的环境中运行实验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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