Reading on small displays: reading performance and perceived ease of reading

Tikka, Piiastiina (2013) Reading on small displays: reading performance and perceived ease of reading. Doctoral thesis, Northumbria University.

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Abstract

The present thesis explores and discusses reading continuous text on small screens, namely on mobile devices, and aims at identifying a model capturing those factors that most influence the perceived experience of reading. The thesis also provides input for the user interface and content creation industries, offering them some direction as to what to focus on when producing interfaces intended for reading or text-based content that is likely to be read on a small display.

The thesis starts with an overview of the special characteristics of reading on small screens and identifies, through existing literature, issues that may affect fluency and ease of reading on mobile devices. The thesis then
presents six experiments and studies on reading performance and perceived experience when reading on small screens. The mixed-methods research presented in the thesis showed that reading performance and subjective perception of reading fluency and ease do not always correspond, and perceived experience can have a strong influence over an end-user’s choice of whether to access text based content on a small display device or not. The research shows that it is important to measure interface quality not only in terms of functionality, but also for the user experience offered – and, ideally, to measure experience through more than one variable.

The thesis offers a factor model (mobile reading acceptance model) of those factors that collectively influence subjective experience when reading via small screens. The key factors in the model are visibility of text, overview of contents, navigation within the contents and interaction with the interface/device. Further contributions include methods for cost-efficient user experience testing: a modified critical incident technique and using an optical character recognition to gauge legibility user experience
at early design iterations.

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