Effects of Cues in a Binary Categorization Task on Dual-Task Performance, Mental Workload, and Effort

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Abstract

Binary cues help operators perform binary categorization tasks, such as monitoring for system failures. They may also allow them to attend to other tasks they concurrently perform. If the time saved by using cues is allocated to other concurrent tasks, users’ overall effort may remain unchanged. In 2 experiments, participants performed a simulated quality control task, together with a tracking task. In half the experimental blocks cues were available, and participants could use them in their decisions about the quality of products (intact or faulty). In Experiment 1, the difficulty of tracking was constant, while in Experiment 2, tracking difficulty differed in the 2 halves of the experiment. In both experiments, participants reported on the NASA Task Load Index that cues improved their performance and reduced their frustration. Consequently, their overall score on mental workload (MWL) was lower with cues. They also reported, however, that cues did not reduce their effort. We conclude that cues and other forms of automation may support task performance and reduce overall MWL, but this will not necessarily mean that users will work less hard. Thus, effort and overall MWL should be evaluated separately, if one wants to obtain a full picture of the effects of automation.

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