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Exploring the feasibility of web form adaptation to users’ cultural dimension scores

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Abstract

With many daily tasks now performed on the Internet, productivity and efficiency in working with web pages have become transversal necessities for all users. Many of these tasks involve the inputting of user information, obligating the user to interact with a webform. Research has demonstrated that productivity depends largely on users’ personal characteristics, implying that it will vary from user to user. The webform development process must therefore, include modeling of its intended users to ensure the interface design is appropriate. Taking all potential users into account is difficult, however, primarily because their identity is unknown, and some may be effectively excluded by the final design. Such discrimination can be avoided by incorporating rules that allow webforms to adapt automatically to the individual user’s characteristics, the principal one being the person’s culture. In this paper we report two studies that validate this option. We begin by determining the relationships between a user’s cultural dimension scores and their behavior when faced with a webform. We then validate the notion that rules based on these relationships can be established for the automatic adaptation of a webform in order to reduce the time taken to complete it. We conclude that the automatic webform adaptation to the cultural dimensions of users improves their performance.

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Authors and Affiliations

  1. Facultad de Ingenieríay Ciencias Aplicadas, Universidad de Los Andes, Avenida San Carlos de Apoquindo 2200, Santiago, Chile

    Matías Recabarren

  2. Computer Science Department, School of Engineering, Pontificia Universidad Católica de Chile, Escuela de Ingeniería, DCC(143) Casilla 306, Santiago 22, Chile

    Miguel Nussbaum

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  1. Matías Recabarren
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  2. Miguel Nussbaum
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Correspondence to Matías Recabarren.

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Recabarren, M., Nussbaum, M. Exploring the feasibility of web form adaptation to users’ cultural dimension scores. User Model User-Adap Inter 20, 87–108 (2010). https://doi.org/10.1007/s11257-010-9071-7

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