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Expertise Development With Different Types of Automation: A Function of Different Cognitive Abilities

Human Factors: The Journal of the Human Factors and Ergonomics Society

Published online on

Abstract

Objective:

I explored whether different cognitive abilities (information-processing ability, working-memory capacity) are needed for expertise development when different types of automation (information vs. decision automation) are employed.

Background:

It is well documented that expertise development and the employment of automation lead to improved performance. Here, it is argued that a learner’s ability to reason about an activity may be hindered by the employment of information automation. Additional feedback needs to be processed, thus increasing the load on working memory and decelerating expertise development. By contrast, the employment of decision automation may stimulate reasoning, increase the initial load on information-processing ability, and accelerate expertise development. Authors of past research have not investigated the interrelations between automation assistance, individual differences, and expertise development.

Method:

Sixty-one naive learners controlled simulated air traffic with two types of automation: information automation and decision automation. Their performance was captured across 16 trials. Well-established tests were used to assess information-processing ability and working-memory capacity.

Results:

As expected, learners’ performance benefited from expertise development and decision automation. Furthermore, individual differences moderated the effect of the type of automation on expertise development: The employment of only information automation increased the load on working memory during later expertise development. The employment of decision automation initially increased the need to process information.

Conclusion:

These findings highlight the importance of considering individual differences and expertise development when investigating human–automation interaction.

Application:

The results are relevant for selecting automation configurations for expertise development.