Predictive Cognitive Modelling of Applications

Sabine Prezenski, Dominik Bruechner, Nele Russwinkel

Abstract

This paper argues that important usability aspects of mobile applications can be automatically evaluated using computational cognitive models based on the cognitive architecture ACT-R. A tool incorporating cognitive models for specific tasks, users, applications and usability aspects is proposed. Explanations provided by the tool for usability flaws are based on simulations of cognitive mechanisms. A use-case of the tool is introduced, which is based on an ACT-R model that simulates how users search and select a specific target in a hierarchical android application and predicts efficiency and learnability for average users. The model has been empirically validated in four studies with two different applications. To fully automate the usability evaluation of the use-case, two basic requirements need to be fulfilled. First, the application and the cognitive model have to be connected. A tool called ACT-Droid acts as an interface between the Android application and the cognitive model. Second, the models knowledge of the world, which is application specific, has to be provided automatically by using an automated user interface analysation approach. Therefore, the open-source tool AppCrawler was extended to allow the extraction of the required information.

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Paper Citation


in Harvard Style

Prezenski S., Bruechner D. and Russwinkel N. (2017). Predictive Cognitive Modelling of Applications . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: HUCAPP, (VISIGRAPP 2017) ISBN 978-989-758-229-5, pages 165-171. DOI: 10.5220/0006273301650171


in Bibtex Style

@conference{hucapp17,
author={Sabine Prezenski and Dominik Bruechner and Nele Russwinkel},
title={Predictive Cognitive Modelling of Applications},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: HUCAPP, (VISIGRAPP 2017)},
year={2017},
pages={165-171},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006273301650171},
isbn={978-989-758-229-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: HUCAPP, (VISIGRAPP 2017)
TI - Predictive Cognitive Modelling of Applications
SN - 978-989-758-229-5
AU - Prezenski S.
AU - Bruechner D.
AU - Russwinkel N.
PY - 2017
SP - 165
EP - 171
DO - 10.5220/0006273301650171