This study investigated the development of automaticity during repetitive construction activities. Twenty- eight subjects were recruited to participate in a total of 22 trials of simulated roofing installations for one month in a laboratory. The performance metric considered in this research for feature-based diagnosis of automaticity development was the roofing task accuracy. The results revealed that the roofing task accuracy significantly improved with practice as the trial days progressed. Given that practitioners are interested in training workers to achieve automaticity to increase their productivity and multi-tasking skills, the results of this study provide measures to test training effectiveness and the extent to which workers have developed automaticity. Also, by better understanding the model of humans, this study’s results will help improve human-AI teaming as the AI will better understand the cognitive state of its human counterpart and can adapt to him/her more accurately.
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