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Using eye tracking to optimise the usability of content rich e-learning material / Optimising the usability of content rich e-learning material: an eye tracking experiment

This research was aimed at the optimisation of the usability of content-rich computer and mobile based e-learning material. The goal was to preserve the advantages of paper based material in designing optimised modules that were mobile and computer-based, but at the same time avoiding the pitfalls of converting traditional paper based learning material for use on screen. A mobile eye tracker was used to analyse how students studied similar course content on paper, and on mobile device. Screen based eye tracking was also used to analyse how participants studied corresponding content on a desktop screen. Eye movements which were recorded by an eye tracker revealed the sequences of fixations and saccades on the text that was read by each participant. By analysing and comparing the eye gaze patterns of students reading the same content on three different delivery platforms, the differences between these platforms were identified in terms of their delivery of content rich, text based study material. The results showed that more students read online content on a computer screen than on mobile devices. The inferential analysis revealed that the differences in reading duration, comprehension, linearity and fixation count on the three platforms were insignificant. There were significant differences in saccade length. This analysis was used to identify strong aspects of the respective platforms and consequently derive guidelines for using these aspects optimally to design content rich material for delivery on computer screen and mobile device. The limitations of each platform were revealed and guidelines for avoiding these were derived / Computing / M. Sc. (Computing)

Identiferoai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:unisa/oai:uir.unisa.ac.za:10500/13832
Date11 1900
CreatorsMpofu, Bongeka
ContributorsVan Dyk, Tobie, Gelderblom, Helene
Source SetsSouth African National ETD Portal
LanguageEnglish
Detected LanguageEnglish
TypeDissertation
Format1 online resource (xiii, 196 leaves) : color illustrations, color graphs, application/pdf

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