Rock Leung

How Older Adults Learn to Use Mobile Devices: Survey and Field Investigations

Mobile computing devices, such as smart phones, offer benefits that may be especially valuable to older adults (age 65+). Yet, older adults have been shown to have difficulty learning to use these devices. In the research presented in this article, we sought to better understand how older adults learn to use mobile devices, their preferences and barriers, in order to find new ways to support them in their learning process. We conducted two complementary studies: a survey study with 131 respondents from three age groups (20--49, 50--64, 65+) and an in-depth field study with 6 older adults aged 50+. The results showed, among other things, that the preference for trial-and-error decreases with age, and while over half of older respondents and participants preferred using the instruction manual, many reported difficulties using it. We discuss implications for design and illustrate these implications with an example help system, Help Kiosk, designed to support older adults’ learning to use mobile devices.

Evaluation of haptically augmented touchscreen gui elements under cognitive load

Adding expressive haptic feedback to mobile devices has great potential to improve their usability, particularly in multitasking situations where ones visual attention is required. Piezoelectric actuators are emerging as one suitable technology for rendering expressive haptic feedback on mobile devices. We describe the design of redundant piezoelectric haptic augmentations of touchscreen GUI buttons, progress bars, and scroll bars, and their evaluation under varying cognitive load. Our haptically augmented progress bars and scroll bars led to significantly faster task completion, and favourable subjective reactions. We further discuss resulting insights into designing useful haptic feedback for touchscreens and highlight challenges, including means of enhancing usability, types of interactions where value is maximized, difficulty in disambiguating background from foreground signals, tradeoffs in haptic strength vs. resolution, and subtleties in evaluating these types of interactions.

Multi-Layered Interfaces to Improve Older Adults’ Initial Learnability of Mobile Applications

Mobile computing devices can offer older adults (ages 65+) support in their daily lives, but older adults often find such devices difficult to learn and use. One potential design approach to improve the learnability of mobile devices is a Multi-Layered (ML) interface, where novice users start with a reduced-functionality interface layer that only allows them to perform basic tasks, before progressing to a more complex interface layer when they are comfortable. We studied the effects of a ML interface on older adults’ performance in learning tasks on a mobile device. We conducted a controlled experiment with 16 older (ages 65--81) and 16 younger participants (age 21--36), who performed tasks on either a 2-layer or a nonlayered (control) address book application, implemented on a commercial smart phone. We found that the ML interface’s Reduced-Functionality layer, compared to the control’s Full-Functionality layer, better helped users to master a set of basic tasks and to retain that ability 30 minutes later. When users transitioned from the Reduced-Functionality to the Full-Functionality interface layer, their performance on the previously learned tasks was negatively affected, but no negative impact was found on learning new, advanced tasks. Overall, the ML interface provided greater benefit for older participants than for younger participants in terms of task completion time during initial learning, perceived complexity, and preference. We discuss how the ML interface approach is suitable for improving the learnability of mobile applications, particularly for older adults.

Age-related differences in the initial usability of mobile device icons

Mobile devices offer much potential to support older adults (age 65+). However, older adults have been relatively slow to adopt mobile devices. Although much ongoing HCI research has examined usability problems to address this issue, little work has looked at whether existing graphical icons are harder to use for this population compared with younger adults. We conducted a qualitative exploratory study and a follow-up experimental study to determine which icon characteristics help initial icon usability for older adults. We found that our older participants did have more problems using existing mobile device icons, but that particular icon characteristics – semantically close meaning (i.e. natural, close link between depicted objects and associated function), familiar, labelled and concrete (i.e. those depicting real-world objects) – improved icon usability for them. We discuss how these findings can help icon designers to create mobile device icons that are more suited to the abilities and technology experience of older adults.

Designing for bystanders: reflections on building a public digital forum

In this paper, we reflect on the design and deployment process of MAGICBoard, a public display deployed in a university setting that solicits the electronic votes and opinions of bystanders on trivial but amusing topics. We focus on the consequences of our design choices with respect to encouraging bystanders to interact with the public display. Bystanders are individuals around the large display who may never fully engage with the application itself, but are potential contributors to the system. Drawing on our recent experiences with MAGICBoard, we present a classification of bystanders, and then discuss three design themes relevant to the design of systems for bystander use: graduated proximal engagement, lowering barriers for interaction and supporting covert engagement.

Involving domain experts in assistive technology research

Teams engaging in assistive technology research should include expertise in the domain of disability itself, in addition to other areas of expertise that are more typical in human–computer interaction (HCI) research, such as computer science and psychology. However, unexpected problems can arise when HCI researchers do not adequately plan the involvement of domain experts in a research project. Although many research teams have included domain experts when designing assistive technologies, there has been little work published on how to best involve these experts in the research process. This paper is a first step towards filling that void. Based on the authors’ own experiences involving domain experts in research, as well as those documented in the literature, five types of domain experts and three broad roles that domain experts can play are identified, and five guidelines for their involvement are presented. This analysis will be useful to anyone in the assistive technology and universal accessibility communities, especially those who are in the early stages of conducting research in this area. It is intended to lay the foundation of best practices for involving domain experts in assistive technology research.

ALEX: mobile language assistant for low-literacy adults

Basic literacy skills are fundamental building blocks of education, yet for a very large number of adults tasks such as understanding and using everyday items is a challenge. While research, industry, and policy-making is looking at improving access to textual information for low-literacy adults, the literacy-based demands of todays society are continually increasing. Although many community-based organizations offer resources and support to adults with limited literacy skills, current programs have difficulties reaching and retaining those that would benefit most from them. To address these challenges, the National Research Council of Canada is proposing a technological solution to support literacy programs and to assist low-literacy adults in todays information-centric society: ALEX© - Adult Literacy support application for EXperiential learning. ALEX© has been created together with low-literacy adults, following guidelines for inclusive design of mobile assistive tools. It is a mobile language assistant that is designed to be used both in the classroom and in daily life, in order to help low-literacy adults become increasingly literate and independent.

ALEX © : a mobile adult literacy experiential learning application

An alarmingly high number of adults in the worlds most developed countries are linguistically functionally illiterate. The research presented in this paper describes ALEX ©, an ongoing attempt to successfully develop an innovative assistive, mobile, experiential language-learning application to support the daily literacy education and needs of such adults, anywhere, anytime. We introduce a set of guidelines we have collated to inform the design of mobile assistive technologies, introduce our application and describe the design activities to date that have led to the development of our current application. We present this overview in the hope that it is useful to others working in the fledgling domains of mobile assistive technology design and/or mobile experiential language-learning technologies.

Gamification of collaborative idea generation and convergence

Collaborative brainstorming does not always result in more ideas or higher quality ideas than working individually. We designed a system with game elements to incent participation in a collaborative creative idea generation processes of brainstorming followed by a convergence activity. We compared teams using the system with and without game elements to investigate the effect of the elements on collaborative work activities. Preliminary results suggest that game elements can help teams produce more ideas during brainstorming and engage in more discussion during a subsequent convergence activity, without negatively affecting idea quality.

Improving the learnability of mobile device applications for older adults

Mobile devices have the potential to support many older adults (age 65+) in their daily lives. However, older adults find it difficult to learn to use many existing mobile device applications and their interfaces. The goal of this dissertation research is to improve the learnability of mobile software user interfaces for older adults. To achieve this goal, we will investigate three complementary design approaches that have not been well explored for this population.