Measuring and Reducing the Cognitive Load for the End Users of Complex Systems
| Autor: | James Xue, James Oakes, Mark Johnson, Scott J Turner |
|---|---|
| Přispěvatelé: | Bi, Y, Bhatia, Rahul, Kapoor, Supriya |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Computer science
Process (engineering) End user business.industry Interface (computing) Distributed computing Complex system 020207 software engineering Cloud computing 02 engineering and technology computer.software_genre Oracle Expert system 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing business computer Cognitive load |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9783030295158 IntelliSys (1) |
| Popis: | With the proliferation of complex computer systems, end users face a never-ending increase in the number of tasks, methods, inputs, passwords, usernames (and so on) when using online and standalone computer-based 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 interfaces of 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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