A model-based framework for classifying and diagnosing usability problems
Ham, Dong-Han ORCID: https://orcid.org/0000-0003-2908-057X
(2014)
A model-based framework for classifying and diagnosing usability problems.
Cognition, Technology and Work, 16
(3)
.
pp. 373-388.
ISSN 1435-5558
[Article]
(doi:10.1007/s10111-013-0267-6)
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Abstract
A great deal of study has been devoted to the problem of how to identify and categorize usability problems; however, there is still a lack of studies dealing with the problem of how to diagnose the causes of usability problems and how to feed them back into design process. The value of classifying usability problems can be enhanced when they are interpreted in connection with design process and activities. Thus, it is necessary to develop a systematic way of diagnosing usability problems in terms of design aspects and applying diagnosis results to improve design process and activities. With this issue in mind, this paper proposes a conceptual framework that supports a systematic classification and diagnosis of usability problems. This paper firstly reviews seven approaches to classifying usability problems. Then, we point out the needs of adopting a model-based approach to classifying and diagnosing usability problems and of developing a comprehensive framework guiding the use of model-based approaches. We then propose a conceptual framework that specifies how a model-based classification and diagnosis of usability problems should be conducted and suggests the combined use of three different types of models, each of which addresses context of use, design knowledge and design activities. Last, we explain how a sound classification scheme of usability problems can be systematically developed, and how the classification of usability problems can be connected to design process and activities on the basis of the framework.
Item Type: | Article |
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Keywords (uncontrolled): | Usability Problems, Usability Problem Classification, Usability, Usability Evaluation, User Interface Design |
Research Areas: | A. > School of Science and Technology > Computer Science |
Item ID: | 19289 |
Notes on copyright: | This is a post-peer-review, pre-copyedit version of an article published in Cognition, Technology & Work. This is an author accepted manuscript. The final publication is available at Springer via http://dx.doi.org/10.1007/s10111-013-0267-6 |
Useful Links: | |
Depositing User: | Dong-Han Ham |
Date Deposited: | 15 Apr 2016 09:31 |
Last Modified: | 04 Mar 2023 09:25 |
URI: | https://eprints.mdx.ac.uk/id/eprint/19289 |
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