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Visual intelligences method to identify e-learning materials interactivity responsiveness

Bandara, I.; Ioras, F. and Maher, K. (2015). Visual intelligences method to identify e-learning materials interactivity responsiveness. In: ICERI 2015: 8th International Conference of Education, Research and Innovation (Gómez Chova, L.; López Martínez, A. and Candel Torres, I. eds.), IATED, pp. 109–116.

URL: https://library.iated.org/view/BANDARA2015VIS
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Abstract

New methods to deliver education at distance are rapidly emerging. One of the most promising method is E-Learning Systems (ELS). This is a pedagogical learning approach which is entirely web based and supports distributed learning. To support diverse teaching and learning paradigms, e-learning content has to be more than online text and PowerPoint material. It is imperious to create a dynamic interaction between e-learning content and users. Therefore, content as well as delivery, assessment and user feedback have to be supported in a highly personalised manner by ELS.

In this paper the authors present a real time vision-based method for measuring learner alertness to an enhanced adaptive ELS, which allowed ultimately to deploy a novel solution for improving its architecture based on real time eye blink measures to identify alertness and responsiveness to the E-learning materials. The proposed method uses eye blink detection in both diagnostic and interactive way. In diagnostic way the method show whether the learner's attention has been caught, thus providing evidence of the learner's focus of attention to the online materials. The interactive way enables the method to measure eye blink parameters to identify learner reaction time to online activities.

The resulting ELS architecture delivers personalised learning content which enhances learner responsiveness to content. Furthermore, various scenarios for different application domains are explored.

Item Type: Conference or Workshop Item
Copyright Holders: 2015 IATED
ISBN: 84-608-2657-0, 978-84-608-2657-6
ISSN: 2340-1095
Keywords: e-learning systems; eye blink parameters; alertness; reaction time; responsiveness
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
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Item ID: 59102
Depositing User: Indra Bandara
Date Deposited: 18 Feb 2019 15:23
Last Modified: 29 Mar 2019 11:33
URI: http://oro.open.ac.uk/id/eprint/59102
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