UZH-Logo

Maintenance Infos

Culturally adaptive user interfaces


Reinecke, K. Culturally adaptive user interfaces. 2010, University of Zurich, Faculty of Economics.

Abstract

One of the largest impediments for the efficient use of software in different cultural contexts is the gap between the software designs - typically following western cultural cues - and the users, who handle it within their cultural frame. The problem has become even more relevant, as today the majority of revenue in the software industry comes from outside market dominating countries such as the USA. While research has shown that adapting user interfaces to cultural preferences can be a decisive factor for marketplace success, the endeavor is oftentimes foregone because of its time-consuming and costly procedure. Moreover, it is usually limited to producing one uniform user interface for each nation, thereby disregarding the intangible nature of cultural backgrounds. To overcome these problems, this thesis introduces a new approach called 'cultural adaptivity'. The main idea behind it is to develop intelligent user interfaces, which can automatically adapt to the user's culture. Rather than only adapting to one country, cultural adaptivity is able to anticipate different influences on the user's cultural background, such as previous countries of residence, differing nationalities of the parents, religion, or the education level. We hypothesized that realizing these influences in adequate adaptations of the interface improves the overall usability, and specifically, increases work efficiency and user satisfaction. In support of this thesis, we developed a cultural user model ontology, which includes various facets of users' cultural backgrounds. The facets were aligned with information on cultural differences in perception and user interface preferences, resulting in a comprehensive set of adaptation rules. We evaluated our approach with our culturally adaptive system MOCCA, which can adapt to the users' cultural backgrounds with more than 115'000 possible combinations of its user interface. Initially, the system relies on the above-mentioned adaptation rules to compose a suitable user interface layout. In addition, MOCCA is able to learn new, and refine existing, adaptation rules from users' manual modifications of the user interface based on a collaborative filtering mechanism, and from observing the user's interaction with the interface. The results of our evaluations showed that MOCCA is able to anticipate the majority of user preferences in an initial adaptation, and that users' performance and satisfaction significantly improved when using the culturally adapted version of MOCCA, compared to its 'standard' US interface.

One of the largest impediments for the efficient use of software in different cultural contexts is the gap between the software designs - typically following western cultural cues - and the users, who handle it within their cultural frame. The problem has become even more relevant, as today the majority of revenue in the software industry comes from outside market dominating countries such as the USA. While research has shown that adapting user interfaces to cultural preferences can be a decisive factor for marketplace success, the endeavor is oftentimes foregone because of its time-consuming and costly procedure. Moreover, it is usually limited to producing one uniform user interface for each nation, thereby disregarding the intangible nature of cultural backgrounds. To overcome these problems, this thesis introduces a new approach called 'cultural adaptivity'. The main idea behind it is to develop intelligent user interfaces, which can automatically adapt to the user's culture. Rather than only adapting to one country, cultural adaptivity is able to anticipate different influences on the user's cultural background, such as previous countries of residence, differing nationalities of the parents, religion, or the education level. We hypothesized that realizing these influences in adequate adaptations of the interface improves the overall usability, and specifically, increases work efficiency and user satisfaction. In support of this thesis, we developed a cultural user model ontology, which includes various facets of users' cultural backgrounds. The facets were aligned with information on cultural differences in perception and user interface preferences, resulting in a comprehensive set of adaptation rules. We evaluated our approach with our culturally adaptive system MOCCA, which can adapt to the users' cultural backgrounds with more than 115'000 possible combinations of its user interface. Initially, the system relies on the above-mentioned adaptation rules to compose a suitable user interface layout. In addition, MOCCA is able to learn new, and refine existing, adaptation rules from users' manual modifications of the user interface based on a collaborative filtering mechanism, and from observing the user's interaction with the interface. The results of our evaluations showed that MOCCA is able to anticipate the majority of user preferences in an initial adaptation, and that users' performance and satisfaction significantly improved when using the culturally adapted version of MOCCA, compared to its 'standard' US interface.

Downloads

1272 downloads since deposited on 07 Feb 2011
237 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Dissertation
Referees:Bernstein A, Jameson A
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Date:2010
Deposited On:07 Feb 2011 16:38
Last Modified:05 Apr 2016 14:44
Other Identification Number:1466
Permanent URL: http://doi.org/10.5167/uzh-44838

Download

[img]
Preview
Filetype: PDF
Size: 15MB

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.

Author Collaborations