A framework for estimating difficulty and exclusion from tasks during inclusive design

Measuring capability variations within the population isanimportant process that can be used to support decision making regarding the inclusivity of design for all users, thus allowing the level of exclusion tobe defined veryearly and throughout the design process. Our hands often represent a central feature of the human-task interaction, and therefore, variations in the capabilities of the hands has the potential to exclude people from all or part of the tasks they perform. Data is presented from the performance of 15 people in one of three age groups (18-40, 41-64 and 65+). Using a classification system for defining hand actions the prevalence of different grips in response to a range of physical task demands was mapped in a way that allowed capability to be measured against other variables such as task quality. This was found toenhance thegranularity with which exclusion could be both measured and predicted.

Evaluation of Setup Procedures on Mobile Devices Based on Users’ Initial Experience

Users’ initial perceptions of their competence are key motivational factors for further use. However, initial tasks on a mobile operating system (OS) require setup procedures, which are currently largely inconsistent, do not provide users with clear, visible and immediate feedback on their actions, and require significant adjustment time for first-time users. This paper reports on a study with ten users, carried out to better understand how both prior experience and initial interaction with two touchscreen mobile interfaces (Apple iOS and Google Android) affected setup task performance and motivation. The results show that the reactions to setup on mobile interfaces appear to be partially dependent on which device was experienced first. Initial experience with lower-complexity devices improves performance on higher-complexity devices, but not vice versa. Based on these results, the paper proposes six guidelines for designers to design more intuitive and motivating user interfaces (UI) for setup procedures. The preliminary results indicate that these guidelines can contribute to the design of more inclusive mobile platforms and further work to validate these findings is proposed.

A framework for collecting inclusive design data for the UK population.

Successful inclusive product design requires knowledge about the capabilities, needs and aspirations of potential users and should cater for the different scenarios in which people will use products, systems and services. This should include: the individual at home; in the workplace; for businesses, and for products in these contexts. It needs to reflect the development of theory, tools and techniques as research moves on. And it must also to draw in wider psychological, social, and economic considerations in order to gain a more accurate understanding of users' interactions with products and technology. However, recent research suggests that although a number of national disability surveys have been carried out, no such knowledge currently exists as information to support the design of products, systems and services for heterogeneous users. This paper outlines the strategy behind specific inclusive design research that is aimed at creating the foundations for measuring inclusion in product designs. A key outcome of this future research will be specifying and operationalising capability, and psychological, social and economic context measures for inclusive design. This paper proposes a framework for capturing such information, describes an early pilot study, and makes recommendations for better practice.

Facets of prior experience and the effectiveness of inclusive design

Research in inclusive design has shown the importance of prior experience for the usability of interactive products. Prior experience, however, is an ill-defined and inconsistently used construct. A number of different definitions and operationalisations of experience exist, but the differing power of these operationalisations to predict the usability of products for older users has rarely been investigated systematically. This study seeks to fill that gap. It is argued that the construct of experience has at least three components. It is proposed that two of these components, exposure and competence, are directly relevant for the current discussion about prior experience in inclusive design and that they can predict to different degrees the usability of a product for older users. In an empirical study, these facets of expertise are each operationalised on three levels of specificity and their impact on usability is assessed. The results show that measures of competence predict usability variables more strongly than measures of exposure and that levels of medium and high specificity are the best predictors. The application of inclusive design principles to a redesigned version of a ticket vending machine-although not resulting in a difference of overall usability-changed the impact of prior experience on usability measures implying an enhanced inclusiveness of the redesign with regard to prior experience. The implications of these findings for the effectiveness of inclusive design for older users are discussed. © 2013 Springer-Verlag Berlin Heidelberg.

Age, technology prior experience and ease of use: Who's doing what?

Designers often assume that their users will have some digital technological prior experience. We examined these levels of prior experience by surveying frequency and ease of technology use with a range of technology products. 362 people participated as part of a UK nationwide larger survey of people's capabilities and characteristics to inform product design. We found that frequency and self-reported ease of use are indeed correlated for all of the products. Furthermore, both frequency and ease of use declined significantly with age for most of the products. In fact, 29% of the over 65s had never or rarely used any of the products, except for digital TV. We conclude that interfaces need to be designed carefully to avoid implicit assumptions about users' previous technology use.