Using online crowdsourcing platforms has become an option for researchers to rapidly recruit participants for completing tasks that require human ingenuity. However, a growing concern is that workers on online crowdsourcing platforms, such as Amazon Mechanical Turk (AMT), receive unfair compensation for tasks completed. In this article, we explored the effects of the income level of participant’s country and the rate of payment on perceived payment fairness, task quality, and subjective experience. We tested our hypothesis using 3-way ANOVA and chi-square test of independence. The results showed that lower compensation increased the number of participants whose data might be unusable for research. Participants in the lower compensation rate group reported better perceived performance compared to those who received higher compensation. We found that high income country participants report less perceived effort and frustration than lower-middle income country participants.
Trained human workers can predict the intentions of other workers from observed movement patterns when working collaboratively. The intentions prediction is crucial to identify their future actions. In human-machine teams, predictable movement patterns can enhance the interaction and improve team performance. In this article, we investigated the effects of different robot trajectory characteristics on the early prediction performance in human-machine teaming and on perceived robot’s human-likeness. The results showed that humans can predict the robot’s intention quicker and more accurately when the observed robot’s trajectory was generated with relatively lower energy expenditure. We found that the amount of jerk and acceleration in the robot’s joint-space affected perceived robot’s human-likeness.
The use of an online crowdsourcing platform makes it easier and quicker for researchers to recruit participants online. It also allows researchers to adopt another payment method traditionally used on crowdsourcing platforms: the piece-rate payment method. This paper investigated the effects of the participants’ location, the payment method, and the compensation rate on subjective experience, motivation, and perceived payment fairness. This paper extends last year’s paper, in which the participants’ location and the payment method were the focus of the investigation. Two additional studies have been conducted using piece-rate payment method. The data were analyzed using a 3-way ANOVA and a chi-square test of independence. The results showed that the piece-rate payment method was less likely to attract workers who were motivated to work for money than the quota payment method. There was no difference in perceived payment fairness between using a quota payment method and a piece-rate payment method.
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