On the ability of virtual agents to decrease cognitive load: an experimental study

Florian Brachten (), Felix Brünker, Nicholas R. J. Frick, Björn Ross and Stefan Stieglitz
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Florian Brachten: University of Duisburg-Essen
Felix Brünker: University of Duisburg-Essen
Nicholas R. J. Frick: University of Duisburg-Essen
Björn Ross: University of Duisburg-Essen
Stefan Stieglitz: University of Duisburg-Essen

Information Systems and e-Business Management, No 0, 21 pages

Abstract: Abstract When attempting to solve a problem, humans call upon cognitive resources. These resources are limited, and the degree of their utilisation is described as cognitive load. While the number of parameters to be taken into account and to be processed by modern-day knowledge workers increases, their cognitive resources do not. Research shows that too high a load can increase stress and failure rates and decrease the work satisfaction and performance of employees. It is thus in the interest of organisations to reduce the cognitive load of their employees and keep it at a moderate level. One way to achieve this may be the application of virtual assistants (VAs), software programs, that can be addressed via voice or text commands and respond to the users’ input. This study uses a laboratory experiment with N = 91 participants comparing two groups in their ability to solve a task. One group was able to make use of a VA while the other could not. Besides task performance, the cognitive load of the participants was measured. Results show that (a) cognitive load is negatively related to task performance, (b) the group using the VA performed better at the task and (c) the group using the VA had a lower cognitive load. These findings show that VAs are a viable way to support employees and can increase their performance. It adds to the growing field of IS research on VAs by expanding the field for the concept of cognitive load.

Keywords: Cognitive load; Virtual assistants; Chatbots; Conversational agents; Task performance; Perceived workload; NASA-TLX (search for similar items in EconPapers)
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DOI: 10.1007/s10257-020-00471-7

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