Measuring and Reducing the Cognitive Load for the End Users

Oakes, J, Johnson, M, Xue, J & Turner, S 2019, Measuring and Reducing the Cognitive Load for the End Users of Complex Systems. in Y Bi, R Bhatia & S Kapoor (eds), Intelligent Systems and Applications: AISC 1037. 1 edn, vol. 1, Springer Nature Switzerland AG, Switzerland. https://doi.org/10.1007/978-3-030-29516-5_88, 

Abstract

With the proliferation of complex computer systems, end users face a never-ending increase in the numbernof tasks, methods, inputs, passwords, usernames (and so on) when using online and standalone computerbased systems and applications. This paper examines a method and approach to measure how complex a system is to use, and how to reduce the complexity of such systems by minimising the requirement for human inputs as much as possible, in order to reduce the cognitive load for that user, or group of users.

This paper addresses a study completed around using virtualised computer management systems interfacesof two well-known products AWS (Amazon Web Services), Oracle Cloud, and compares the complexity of the steps and interface for end users to a private cloud less well-known system called the IDE
(Intelligent Design Engine). By using a set of derived formula, we examine how this can be applied to systems that have qualitative data feedback from the experiment process, and how to convert this effectively into quantitative data. This data is then analysed numerically using a unique approach to provide additional and meaningful results based of the original end user data.

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