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The trained and untrained users’ mental models compatibility with the icons of search modules in Iranian digital library applications

The trained and untrained users’ mental models compatibility with the icons of search modules in... PurposeThe purpose of this paper is to investigate the trained and untrained users’ mental models compatibility with search module icons in three Iranian digital library applications, namely, Nika, Azarakhsh, and Simorgh.Design/methodology/approachThe population of this survey consisted of two groups including trained and untrained users. The trained user group consisted of 174 samples, all of which were included in the study due to scarcity of the samples. The untrained user group consisted of 8,210 samples, from which 267 cases were selected through stratified sampling.FindingsResults showed that the trained users’ mental models were more compatible with the search module icons than those of the untrained users. The comparison of three software applications showed that the mental models of trained and untrained users had the highest compatibility with the search icons of Azarakhsh and the lowest compatibility with those of Nika. Concerning the untrained users’ status in terms of their fields of study, results showed that users majoring technical and engineering field and those in agriculture had, respectively, the highest and lowest mental models compatibility with the icons embedded in the user interface of the studied applications.Originality/valueSince the mental models may be incomplete or inaccurate, the study of the trained and untrained users’ mental models compatibility with the search module icons of user interface embedded in various library applications may help in assessing the software’ status and the designers’ level of success in conveying the content. This also may assist information literacy specialists to estimate the required amount of training for trained and untrained users. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Library Hi Tech Emerald Publishing

The trained and untrained users’ mental models compatibility with the icons of search modules in Iranian digital library applications

Rahrovani, Sanaz; Mirzabeigi, Mahdieh; Abbaspour, Javad
Library Hi Tech , Volume 35 (2): 13 – Jun 19, 2017
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References (38)

Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
0737-8831
DOI
10.1108/LHT-06-2016-0071
Publisher site
See Article on Publisher Site

Abstract

PurposeThe purpose of this paper is to investigate the trained and untrained users’ mental models compatibility with search module icons in three Iranian digital library applications, namely, Nika, Azarakhsh, and Simorgh.Design/methodology/approachThe population of this survey consisted of two groups including trained and untrained users. The trained user group consisted of 174 samples, all of which were included in the study due to scarcity of the samples. The untrained user group consisted of 8,210 samples, from which 267 cases were selected through stratified sampling.FindingsResults showed that the trained users’ mental models were more compatible with the search module icons than those of the untrained users. The comparison of three software applications showed that the mental models of trained and untrained users had the highest compatibility with the search icons of Azarakhsh and the lowest compatibility with those of Nika. Concerning the untrained users’ status in terms of their fields of study, results showed that users majoring technical and engineering field and those in agriculture had, respectively, the highest and lowest mental models compatibility with the icons embedded in the user interface of the studied applications.Originality/valueSince the mental models may be incomplete or inaccurate, the study of the trained and untrained users’ mental models compatibility with the search module icons of user interface embedded in various library applications may help in assessing the software’ status and the designers’ level of success in conveying the content. This also may assist information literacy specialists to estimate the required amount of training for trained and untrained users.

Journal

Library Hi Tech – Emerald Publishing

Published: Jun 19, 2017

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