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Modeling Interruption and Resumption in a Smartphone Task: An ACT-R Approach

Modeling Interruption and Resumption in a Smartphone Task: An ACT-R Approach AbstractThis research aims to inspect human cognition when being interrupted while performing a smartphone task with varying levels of mental demand. Due to its benefits especially in the early stages of interface development, a cognitive modeling approach is used. It applies the cognitive architecture ACT-R to shed light on task-related cognitive processing. The inspected task setting involves a shopping scenario, manipulating interruption via product advertisements and mental demands by the respective number of people shopping is done for. Model predictions are validated through a corresponding experimental setting with 62 human participants. Comparing model and human data in a defined set of performance-related parameters displays mixed results that indicate an acceptable fit – at least in some cases. Potential explanations for the observed differences are discussed at the end. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png i-com de Gruyter

Modeling Interruption and Resumption in a Smartphone Task: An ACT-R Approach

i-com , Volume 14 (2): 8 – Aug 1, 2015

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Publisher
de Gruyter
Copyright
© 2015 Walter de Gruyter GmbH, Berlin/Boston
ISSN
2196-6826
eISSN
2196-6826
DOI
10.1515/icom-2015-0033
Publisher site
See Article on Publisher Site

Abstract

AbstractThis research aims to inspect human cognition when being interrupted while performing a smartphone task with varying levels of mental demand. Due to its benefits especially in the early stages of interface development, a cognitive modeling approach is used. It applies the cognitive architecture ACT-R to shed light on task-related cognitive processing. The inspected task setting involves a shopping scenario, manipulating interruption via product advertisements and mental demands by the respective number of people shopping is done for. Model predictions are validated through a corresponding experimental setting with 62 human participants. Comparing model and human data in a defined set of performance-related parameters displays mixed results that indicate an acceptable fit – at least in some cases. Potential explanations for the observed differences are discussed at the end.

Journal

i-comde Gruyter

Published: Aug 1, 2015

Keywords: ACT-R; Cognitive Modeling; Interruption; Mobile Interaction

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