Exploring a capability-demand interaction model for inclusive design evaluation

Designers are required to evaluate their designs against the needs and capabilities of their target user groups in order to achieve successful, inclusive products. This dissertation presents exploratory research into the specific problem of supporting analytical design evaluation for Inclusive Design. The analytical evaluation process involves evaluating products with user data rather than testing with actual users. The work focuses on the exploration of a capability-demand model of product interaction as the basis for analytical inclusive evaluation. This model suggests that by comparing the measured sensory, cognitive and motor capabilities of a user population to the corresponding product demands, the degree of fit between users and products can be assessed. The research problem was addressed by firstly examining theories of human function and performance together with existing sources of user capability data. It was found that user capability data was fragmented and lacking in terms of predicting design exclusion and difficulty at the population level. More fundamentally, however, it was found that the relationships between measured capability in populations with low functional capacity and real world task performance with products (such as errors, times and difficulty) were not well understood. Given that an understanding of these relationships are necessary to guide capability data collection and to drive valid and robust analytical evaluation methods, the research effort focused on exploring these relationships via empirical and analytical studies. The research process culminated in an experimental study with nineteen users of various functional capability profiles performing tasks with four consumer products (a clock radio, a mobile phone, a blender and a vacuum cleaner). Measures of user capability were related to corresponding product demands (on those capabilities) and task outcome measures. A complex picture emerged, where linear relationships did not generally account for significant variance in task outcome measures. Further, it appeared that multiple capabilities were possibly interacting in unknown ways to support real world interaction. These indicative results point to the further investigation of multivariate and non-linear models for describing capability-demand relationships, and also the replication of similar studies with larger sample sizes to confirm the relationships observed. The resulting overall recommendation, therefore, is that there is a need to direct research efforts in this critical but largely unexplored area of capability-demand model building for Inclusive Design evaluation

Visualizing recommendations to support exploration, transparency and controllability

Research on recommender systems has traditionally focused on the development of algorithms to improve accuracy of recommendations. So far, little research has been done to enable user interaction with such systems as a basis to support exploration and control by end users. In this paper, we present our research on the use of information visualization techniques to interact with recommender systems. We investigated how information visualization can improve user understanding of the typically black-box rationale behind recommendations in order to increase their perceived relevance and meaning and to support exploration and user involvement in the recommendation process. Our study has been performed using TalkExplorer, an interactive visualization tool developed for attendees of academic conferences. The results of user studies performed at two conferences allowed us to obtain interesting insights to enhance user interfaces that integrate recommendation technology. More specifically, effectiveness and probability of item selection both increase when users are able to explore and interrelate multiple entities - i.e. items bookmarked by users, recommendations and tags. Copyright © 2013 ACM

Facilitating insight into a simulation model using visualization and dynamic model previews

This paper shows how model simplification, by replacing iterative steps with unitary predictive equations, can enable dynamic interaction with a complex simulation process. Model previews extend the techniques of dynamic querying and query previews into the context of ad hoc simulation model exploration. A case study is presented within the domain of counter-current chromatography. The relatively novel method of insight evaluation was applied, given the exploratory nature of the task. The evaluation data show that the trade-off in accuracy is far outweighed by benefits of dynamic interaction. The number of insights gained using the enhanced interactive version of the computer model was more than six times higher than the number of insights gained using the basic version of the model. There was also a trend for dynamic interaction to facilitate insights of greater domain importance

InfoVis experience enhancement through mediated interaction

Information visualization is an experience in which both the aesthetic representations and interaction are part. Such an experience can be augmented through close consideration of its major components. Interaction is crucial to the experience, yet it has seldom been adequately explored in the field. We claim that direct mediated interaction can augment such an experience. This paper discusses the reasons behind such a claim and proposes a mediated interactive manipulation scheme based on the notion of directness. It also describes the ways in which such a claim will be validated. The Literature Knowledge Domain (LKD) is used as the concrete domain around which the discussions will be held

Usability testing for improving interactive geovisualization techniques

Usability describes a product’s fitness for use according to a set of predefined criteria. Whatever the aim of the product, it should facilitate users’ tasks or enhance their performance by providing appropriate analysis tools. In both cases, the main interest is to satisfy users in terms of providing relevant functionality which they find fit for purpose. “Testing usability means making sure that people can find and work with [a product’s] functions to meet their needs” (Dumas and Redish, 1999: 4). It is therefore concerned with establishing whether people can use a product to complete their tasks with ease and at the same time help them complete their jobs more effectively. This document describes the findings of a usability study carried out on DecisionSite Map Interaction Services (Map IS). DecisionSite, a product of Spotfire, Inc.,1 is an interactive system for the visual and dynamic exploration of data designed for supporting decisionmaking. The system was coupled to ArcExplorer (forming DecisionSite Map IS) to provide limited GIS functionality (simple user interface, basic tools, and data management) and support users of spatial data. Hence, this study set out to test the suitability of the coupling between the two software components (DecisionSite and ArcExplorer) for the purpose of exploring spatial data. The first section briefly discusses DecisionSite’s visualization functionality. The second section describes the test goals, its design, the participants and data used. The following section concentrates on the analysis of results, while the final section discusses future areas of research and possible development

Supporting Device Discovery and Spontaneous Interaction with Spatial References

The RELATE interaction model is designed to support spontaneous interaction of mobile users with devices and services in their environment. The model is based on spatial references that capture the spatial relationship of a user’s device with other co-located devices. Spatial references are obtained by relative position sensing and integrated in the mobile user interface to spatially visualize the arrangement of discovered devices, and to provide direct access for interaction across devices. In this paper we discuss two prototype systems demonstrating the utility of the model in collaborative and mobile settings, and present a study on usability of spatial list and map representations for device selection

Spatial Consistency and Contextual Cues for Incidental Learning in Browser Design

This paper introduces the Backward Highlighting technique for mitigating an identified flaw in directional column-faceted browsers like iTunes. Further, the technique significantly enhances the information that can be learned from the columns and encourages further interaction with facet items that were previously restricted from use. After giving a detailed overview of faceted browsing approaches, the Backward Highlighting technique is described along with possible implementations. Two of these possible implementations are compared to a control condition to statistically prove the value of Backward Highlighting. The analysis produces design recommendations for implementing the Backward Highlighting technique within faceted browsers that choose the directional column approach. The paper concludes with future work on how to further improve on the statistically proven advantages provided by the Backward Highlighting technique