Keep an eye on information processing: Eye tracking evidence for the influence of hypertext structures on navigational behaviour and textual complexity

In the following empirical study the influence of hypertext structures on the processing of information will be examined using eye tracking data. It will be tested whether the organizational structure of hypertexts influences navigational behaviour. Moreover we want to find out whether the information architecture has an effect on the number and duration of fixations and reading comprehension. A source text on the topic of speed reading consisting of 597 words was converted into an axial and a networked hypertext. The subjects in this test series were 22 students of English and American studies from Graz University, who were all on the level of C1 according to the common European Framework of Reference. To sample the position of the user’s eye on an average of every 20 ms the Eye Tracker Tobii 1750 was used. The data were analyzed using the software program Clearview. The eye tracking data depicting scan paths and hot spot images of areas of highest fixation count suggest that prototypical hypertext structures trigger prototypical gaze patterns, which means that the order in which links and nodes received their first fixation was stable. The average dwell time in the defined areas of interest was lower in the network structure while the axial structure produced fewer regressive eye movements and caused fewer orientation problems. The presentation format did not significantly affect comprehension

Chinese EFL learners' attitudes towards smartphone-based reading

Reading through mobile phones is increasingly popularized worldwide, particularly among young adults. However, few researchers investigate EFL learners' attitudes towards smartphone-based reading. The present research conducted a questionnaire survey to explore EFL learners' perceptions and beliefs by integrating the reading attitude model with the technology acceptance model UTAUT2. One hundred ninety-two participants responded to the questionnaire. The statistical data analysis, including t-tests and analysis of variance (ANOVA), indicated that Chinese EFL learners were generally positive in smartphone-based reading. Although they did not show keen feelings about it or form a habit of using the smartphone for EFL reading, they could perceive its usefulness and ease of use and positively believed in its future use in EFL reading. Additionally, gender differences did not impact EFL learners' overall attitudes. Still, participants' interest in English and experiences in mobile reading did suggest positive influences on their attitudes towards reading through the phone. Finally, the implications of the results and pedagogical practice of smartphone use in EFL reading are discussed

Reducing Power Consumption and Latency in Mobile Devices using a Push Event Stream Model, Kernel Display Server, and GUI Scheduler

The power consumed by mobile devices can be dramatically reduced by improving how mobile operating systems handle events and display management. Currently, mobile operating systems use a pull model that employs a polling loop to constantly ask the operating system if an event exists. This constant querying prevents the CPU from entering a deep sleep, which unnecessarily consumes power. We’ve improved this process by switching to a push model which we refer to as the event stream model (ESM). This model leverages modern device interrupt controllers which automatically notify an application when events occur, thus removing the need to constantly rouse the CPU in order to poll for events. Since the CPU rests while no events are occurring, power consumption is reduced. Furthermore, an application is immediately notified when an event occurs, as opposed to waiting for a polling loop to recognize when an event has occurred. This immediate notification reduces latency, which is the elapsed time between the occurrence of an event and the beginning of its processing by an application. We further improved the benefits of the ESM by moving the display server, a central piece of the graphical user interface (GUI), into the kernel. Existing display servers duplicate some of the kernel code. They contain important information about an application that can assist the kernel with scheduling, such as whether the application is visible and able to receive events. However, they do not share such information with the kernel. Our new kernel-level display server (KDS) interacts directly with the process scheduler to determine when applications are allowed to use the CPU. For example, when an application is idle and not visible on the screen, the KDS prevents that application from using the CPU, thus conserving power. These combined improvements have reduced power consumption by up to 31.2% and latency by up to 17.1 milliseconds in our experimental applications. This improvement in power consumption roughly increases battery life by one to four hours when the device is being actively used or fifty to three-hundred hours when the device is idle

Understanding and improving mobile reading via scalable and low cost sensing

In recent years, due to the increasing ubiquity of Internet and mobile devices, mobile reading on smart watches and smartphones is experiencing rapid growth. Despite the great potential, new challenges are brought. Compared to traditional reading, mobile reading faces major challenges such as encountering more frequent distractions and lacking portable and efficient technique to deeply understand and improve it. Fortunately, the development of the hardware and software of mobile devices provide an opportunity to track users’ behavior and physiological signals accurately in a low-cost and portable manner. In this thesis, I explored the usage of low-cost mobile sensors to solve the measurement challenges of reading. I used the low-cost mobile sensing techniques on mobile devices to understand and improve the degree and quality of reading. In this thesis, I first present SmartRSVP, a reading interface on smart watches that leverages eye-gaze contact tracking technique and heart rate sensing technique to facilitate reading under distractions. I then present Lepton, an intelligent reading system on smart phones that tracks eye-gaze periodical patterns and sensing the screen touching behavior to monitor readers’ cognitions and emotions during reading. Lastly, I present StrategicReading, which uses the implicitly captured eye gaze patterns, scrolling motions, and log histories to monitor users’ reading strategies and performance during multiple-sources online reading

Head-mounted displays and dynamic text presentation to aid reading in macular disease

The majority of individuals living with significant sight loss have residual vision which can be enhanced using low vision aids. Smart glasses and smartphone-based headsets, both increasing in prevalence, are proposed as a low vision aid platform. Three novel tests for measuring the visibility of displays to partially sighted users are described, along with a questionnaire for assessing subjective preference. Most individuals tested, save those with the weakest vision, were able to see and read from both a smart glasses screen and a smartphone screen mounted in a headset. The scheme for biomimetic scrolling, a text presentation strategy which translates natural eye movement into text movement, is described. It is found to enable the normally sighted to read at a rate five times that of continuous scrolling and is faster than rapid serial visual presentation for individuals with macular disease. With text presentation on the smart glasses optimised to the user, individuals with macular disease read on average 65% faster than when using their habitual optical aid. It is concluded that this aid demonstrates clear benefit over the commonly used devices and is thus recommended for further development towards widespread availability

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

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

The determinants of auditory distraction during reading: an eye-movement investigation.

Everyday reading rarely occurs in complete silence. Whether reading at the office, on the way to work, or in a cafeteria, people are often exposed to background sounds such as speech, noise or music that may distract them from their task. While a lot of research has focused on how background sounds affect readers’ comprehension, less is known about their influence on the ongoing reading process. The present research investigated the effect of continuous and discrete background sounds on eye-movements during reading in an attempt to find out what makes such sounds distracting and how they affect online reading behaviour. The present investigation started with a meta-analysis of previous findings, which revealed that background speech, noise, and music all have a modest but reliably detrimental effect on reading comprehension. The first two experiments showed that intelligible speech disrupts eye-movements during reading mostly due to its semantic properties, which interfere with extracting the meaning of the text. This disruption was found to occur after the initial lexical processing of words and it resulted in more regressions and more re-reading fixations. However, participant’s immediate comprehension of the text remained unaffected. Two further studies suggested that the increase in re-reading behaviour occurs in an attempt to maintain comprehension of the text under such distracting conditions because intelligible speech disrupted comprehension accuracy once participants could not selectively re-read the text. The final experiment showed that discrete deviant sounds also disrupt eye-movements during reading and lead to longer fixation durations when the sound is first heard. However, unlike intelligible speech, this type of distraction was likely due to saccadic inhibition of the oculomotor system. Taken together, the present results demonstrate that eye-movements during reading can reveal subtle auditory distraction effects that may not be detected in measures of comprehension accuracy and that they can give important theoretical insights into their cognitive and oculomotor origin. The findings are discussed in terms of theories of auditory distraction and computational models of eye-movement control during reading