Nomadic input on mobile devices: the influence of touch input technique and walking speed on performance and offset modeling

In everyday life people use their mobile phones on-the-go with different walking speeds and with different touch input techniques. Unfortunately, much of the published research in mobile interaction does not quantify the influence of these variables. In this paper, we analyze the influence of walking speed, gait pattern and input techniques on commonly used performance parameters like error rate, accuracy and tapping speed, and we compare the results to the static condition. We examine the influence of these factors on the machine learned offset model used to correct user input and we make design recommendations. The results show that all performance parameters degraded when the subject started to move, for all input techniques. Index finger pointing techniques demonstrated overall better performance compared to thumb-pointing techniques. The influence of gait phase on tap event likelihood and accuracy was demonstrated for all input techniques and all walking speeds. Finally, it was shown that the offset model built on static data did not perform as well as models inferred from dynamic data, which indicates the speed-specific nature of the models. Also, models identified using specific input techniques did not perform well when tested in other conditions, demonstrating the limited validity of offset models to a particular input technique. The model was therefore calibrated using data recorded with the appropriate input technique, at 75% of preferred walking speed, which is the speed to which users spontaneously slow down when they use a mobile device and which presents a tradeoff between accuracy and usability. This led to an increase in accuracy compared to models built on static data. The error rate was reduced between 0.05% and 5.3% for landscape-based methods and between 5.3% and 11.9% for portrait-based methods

The Open University Library in your pocket

The Open University library is working to support mobile learners through provision of mobile access to information management skills tutorials, the library website, and the library helpdesk. In 2007, we joined hands with the Athabasca University library team to develop the first mobile-friendly version of our library website. Since then, we have been actively researching and developing around other mobile library services, and more recently have consulted users to identify their requirements and what services they–d prefer to access through mobile phones. Recommendations from this user consultation (and from other sources, including regular users' feedback and by tracking user behavior through Google Analytics) include revamping the mobile version of the Library website to offer only the most used services on the home page, implementing SMS (Short Messaging Service) such as loan reminders or library reference service, and developing a consolidated search to offer results from various sources including the library catalogue and e-journals collection

Icanlearn: A Mobile Application For Creating Flashcards And Social Stories\u3csup\u3etm\u3c/sup\u3e For Children With Autistm

The number of children being diagnosed with Autism Spectrum Disorder (ASD) is on the rise, presenting new challenges for their parents and teachers to overcome. At the same time, mobile computing has been seeping its way into every aspect of our lives in the form of smartphones and tablet computers. It seems only natural to harness the unique medium these devices provide and use it in treatment and intervention for children with autism. This thesis discusses and evaluates iCanLearn, an iOS flashcard app with enough versatility to construct Social StoriesTM. iCanLearn provides an engaging, individualized learning experience to children with autism on a single device, but the most powerful way to use iCanLearn is by connecting two or more devices together in a teacher-learner relationship. The evaluation results are presented at the end of the thesis

TechNews digests: Jan - Mar 2010

TechNews is a technology, news and analysis service aimed at anyone in the education sector keen to stay informed about technology developments, trends and issues. TechNews focuses on emerging technologies and other technology news. TechNews service : digests september 2004 till May 2010 Analysis pieces and News combined publish every 2 to 3 month

The effect of age and font size on reading text on handheld computers

Though there have been many studies of computer based text reading, only a few have considered the small screens of handheld computers. This paper presents an investigation into the effect of varying font size between 2 and 16 point on reading text on a handheld computer. By using both older and younger participants the possible effects of age were examined. Reading speed and accuracy were measured and subjective views of participants recorded. Objective results showed that there was little difference in reading performance above 6 point, but subjective comments from participants showed a preference for sizes in the middle range. We therefore suggest, for reading tasks, that designers of interfaces for mobile computers provide fonts in the range of 8-12 point to maximize readability for the widest range of users

Mobile Usability in Educational Contexts: What have we learnt?

The successful development of mobile learning is dependent on human factors in the use of new mobile and wireless technologies. The majority of mobile learning activity continues to take place on devices that were not designed with educational applications in mind, and usability issues are often reported. The paper reflects on progress in approaches to usability and on recent developments, with particular reference to usability findings reported in studies of mobile learning. The requirements of education are considered as well as the needs of students participating in distance education; discipline-specific perspectives and accessibility issues are also addressed. Usability findings from empirical studies of mobile learning published in the literature are drawn together in the paper, along with an account of issues that emerged in two mobile learning projects based at The Open University, UK, in 2001 and 2005. The main conclusions are: that usability issues are often reported in cases where PDAs have been used; that the future is in scenario-based design which should also take into account the evolution of uses over time and the unpredictability of how devices might be used; and that usability issues should be tracked over a longer period, from initial use through to a state of relative experience with the technology