Evaluating Readability on Mobile Devices
Abstract: The thesis presents findings from five readability studies performed on mobile devices. The dynamic Rapid Serial Visual Presentation (RSVP) format has been enhanced with regard to linguistic adaptation and segmentation as well as eye movement modeling. The novel formats have been evaluated against other common presentation formats including Paging, Scrolling, and Leading in latin-square balanced repeated-measurement studies with 12-16 subjects. Apart from monitoring Reading speed, Comprehension, and Task load (NASA-TLX), Eye movement tracking has been used to learn more about how the text presentation affects reading.The Page format generally offered best readability. Reading on a mobile phone decreased reading speed by 10% compared to reading on a Personal Digital Assistant (PDA), an interesting finding given that the display area of the mobile phone was 50% smaller. Scrolling, the most commonly used presentation format on mobile devices today, proved inferior to both Paging and RSVP. Leading, the most widely known dynamic format, caused very unnatural eye movements for reading. This seems to have increased task load, but not affected reading speed to a similar extent. The RSVP format displaying one word at time was found to reduce eye movements significantly, but contrary to common claims, this resulted in decreased reading speed and increased task load. In the last study, Predictive Text Presentation (PTP) was introduced. The format is based on RSVP and combines linguistic chunking and adaptation with eye movement modeling to achieve a reading experience that can rival traditional text presentation.It is explained why readability on mobile devices is important, how it may be evaluated in an efficient and yet reliable manner, and PTP is pinpointed as the format with greatest potential for improvement. The methodology used in the evaluations and the shortcomings of the studies are discussed. Finally, a hyper-graeco-latin-square experimental design is proposed for future evaluations.
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