Individual performance markers and working memory predict supervisory control proficiency and effective use of adaptive automation
by Haneen Saqer; Raja Parasuraman
International Journal of Human Factors and Ergonomics (IJHFE), Vol. 3, No. 1, 2014

Abstract: Adapting automation to transient operator states and changes in the environment has been shown to be more effective than static automation. Adaptive automation design that incorporates individual human operator differences can further enhance human-automation interaction. In this study participants performed a simulated air defence task under low and high task load and three levels of automation (manual, low and high). Automated aids autonomously engaged targets and communicated actions via a text messaging system. Baseline performance measures not only predicted future performance but also predicted use of automation. Operators with high skill proficiency exhibited greater disuse of automation compared to their lower skill counterparts. Contrary to previous findings, working memory spans did not predict overall performance, but did predict appropriate use of automation in non-context matched scenarios. When automation was not matched to level of task load, operators with higher spans were better able to coordinate with automation than lower span individuals.

Online publication date: Fri, 06-Jun-2014

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