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Exploring the educational impact of diverse technologies in online virtual museums

Sylaiou Stella, Mania Aikaterini, Paliokas Ioannis G., Pujol-Tost Laia, Killintzis Vassilis, Liarokapis, Fotis

Πλήρης Εγγραφή


URI: http://purl.tuc.gr/dl/dias/3CADEEEA-F981-4A98-B08F-79ADA289F1F7
Έτος 2017
Τύπος Δημοσίευση σε Περιοδικό με Κριτές
Άδεια Χρήσης
Λεπτομέρειες
Βιβλιογραφική Αναφορά S. Sylaiou, K. Mania, I. Paliokas, L. Pujol-Tost, V. Killintzis and F. Liarokapis, "Exploring the educational impact of diverse technologies in online virtual museums," Int. J. of Arts Technol., vol. 10, no. 1, pp. 58-84, 2017. doi: 10.1504/IJART.2017.083907 https://doi.org/10.1504/IJART.2017.083907
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Περίληψη

This research explores the learning outcomes of online virtual museums employing diverse technologies such as images, videos, 3D reconstructions, etc. It presents the selection criteria (imageability, interactivity, navigability, personalisation, communication) of the five online virtual museums (VMs) involved in the analysis, each of which brings forward a prominent visualisation technology. Then, it describes the methodology of the evaluation process, in which a group of 164 (n = 164) participants, after exploration of the virtual museum websites, answered a self-administered questionnaire including 12 questions based on the concept of generic learning outcomes: a) knowledge and understanding; b) skills; c) change in attitude and values; d) enjoyment, inspiration and creativity; e) action, behaviour and progression. The results of a statistical analysis investigating the educational impact of each VM are analysed. The potential educational advantage of incorporating complex 3D reconstructions in a VM is questioned. A new methodology for analysing VMs is required. This paper contributes to the understanding of the educational impact of VMs in relation to their underlying technology and human computer interaction (HCI) features. Therefore, conclusions have a wider impact and can be generalised to be relevant even after design changes of the VMs selected for the evaluation.

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