Chair: Orit Shaer, Wellesley College, USA
Researching the User Experience for Connected TV - A Case Study
- Long Case Study
Contribution & Benefit: Case study presenting a variety of projects that highlight UX challenges and opportunities around internet-connected television. Can inspire developers to exploit this emerging platform to create novel experiences.
Abstract » This paper presents a Case Study of the BBC’s recent research and development work into the user experience of Internet-Connected Television. User expectations and aspirations around their TV experiences are changing radically as the platform increasingly supplements broadcast network connectivity with IP connectivity. Despite the relative youth of the platform, it is clear that Connected TV and its users support and seek user experiences which are quite distinctive from web browsing on personal computers, or earlier forms of interactive TV platforms. We describe a number of the BBC’s recent research projects developing knowledge and tools to support future user experiences for TV, ranging from typography to alternative input interfaces. In each case, we describe the motivation, the development approach and the empirical assessment of impact of the technology and experiences embodied by our prototypes.
Implicit Imitation in Social Tagging: Familiarity and Semantic Reconstruction
Contribution & Benefit: Presents a multinomial model and experiment formalizing cognitive processes in social imitation in tagging. Allows researchers to differentiate implicit and explicit imitation and to assess the impact of different design choices.
Abstract » Social Tagging is a recent widespread phenomenon on the Web where people assign labels (tags) to Web resources. It has been hypothesized to support collaborative sensemaking. In this paper, we examine some of the cognitive mechanisms assumed to underlie sensemaking, namely social imitation processes. We present a multinomial model that is applied to the generation of tags. In line with the semantic imitation model of Fu and colleagues, we assume that implicit processing can be understood as a semantic reconstruction of gist. Our model contrasts this process with a recall of tags from an explicit verbatim memory trace. We tested this model in an experimental study in which after the search task students had to generate tags themselves. We exposed their answers to a multinomial model derived from Fuzzy Trace Theory to obtain independent parameter estimates for the processes of explicit recall, semantic gist reconstruction and familiarity-based recall. As it turns out, a model that assumes all processes are at play explains the data well. Similar to results of our previous study, we find an influence of search intentions on the two processes. Our results have implications for interface and interaction design of social tagging systems, as well as for tag recommendation in these environments.ACM
Annotating BI Visualization Dashboards: Needs & Challenges
Contribution & Benefit: Presents the user-centered design of a visualization dashboard, which supports context aware and multi-chart annotations applied across visualizations and data dimension levels. Discusses challenges in annotating dynamic and hierarchical data.
Abstract » Annotations have been identified as an important aid in ACM
analysis record-keeping and recently data discovery. In this
paper we discuss the use of annotations on visualization
dashboards, with a special focus on business intelligence
(BI) analysis. In-depth interviews with experts lead to new
annotation needs for multi-chart visualization systems, on
which we based the design of a dashboard prototype that
supports data and context aware annotations. We focus
particularly on novel annotation aspects, such as multi-target annotations, annotation transparency across charts
and data dimension levels, as well as annotation properties
such as lifetime and validity. Moreover, our prototype is
built on a data layer shared among different data-sources
and BI applications, allowing cross application annotations.
We discuss challenges in supporting context aware
annotations in dashboards and other visualizations, such as
dealing with changing annotated data, and provide design
solutions. Finally we report reactions and recommendations from a different set of expert users.
Choosing to Interleave: Human Error and Information Access Cost
Contribution & Benefit: Empirical study demonstrating that the cost of accessing information can impact on multitasking performance. Choosing to interleave the programming of medical devices can result in more omission errors.
Abstract » People are prone to making more errors when multitasking. Thus in safety-critical environments, it is often considered safer to perform tasks sequentially. Here we explore how the cost of accessing information affects the way people choose to interleave. An empirical study based on a medical scenario was conducted. Participants had to program infusion pump devices using information from a prescription form. The physical and mental effort involved in accessing information was manipulated. This was achieved by varying the physical distance between the prescription form and the devices. We demonstrate that by increasing information access cost, individuals are less likely to omit a required task step. This is because they adopt a more memory-intensive strategy, which encourages interleaving at natural boundaries, i.e., after completing the programming of one of the pumps. Interleaving during programming can result in task steps being forgotten.ACM