Search

A variety of views of User Experience (UX) have emerged ranging from contextual interpretations of experience to experimental studies. This paper focuses on User Engagement (UE), a restricted explanation of UX that concentrates on judgement of product quality during interaction. It presents a model to explain how users’ judge quality according to criteria such as aesthetics, usability and engagement.

So why do we get worried about complex systems and what can we do about it? Complexity worries us because the world is unpredictable, large scale, multi component and densely interconnected. We perceived interactions as complex since we have difficulty in generalising over multiple events especially when events are poorly ordered. However interactional complexity is tractable by mathematical modeling as (misnamed) chaos theory has shown. Interactional complexity is being modeled with increasing accuracy by computational theories and simulations of physical and biological systems, viz. the IPCC world climate model. The second form is semantic complexity which implicates the difficulties we have in understanding intent of people. Here sadly there is no short term tractable solution. The Dagstuhl process of discussion leading to incremental (maybe radical) advances in understanding is one answer.

This document gives a motivation for this perspective seminar within the Science of Design initiative, as well as an outline of the participants, agenda, sessions, and presentations. Furthermore, the outcomes of the five working group sessions are summarized: multiple concepts of design, evolution and management of requirements, stakeholder issues, intertwining requirements and design, and requirements, architecture and complexity.

This paper describes the influence of human factors in the requirements engineering process of socio-technical systems design. In particular, we examine agents' workloads and the partitioning of system requirements into automated functions, collaborative task support or manual procedures. We assess workload in terms of communication and the task load that each agent is able to handle. We illustrate the application of the approach in complex socio-technical systems such as the command and control rooms of military vessels. A case study is presented that demonstrates the use of a tool, HUCRE (Human-Centred Requirements Engineering) that assesses workloads of agents and assists the diagnosis of potential system failure. A preliminary evaluation of the HUCRE method and tool is reported, demonstrating that requirements engineers can address human factors issues using the support tool.

This paper presents a visualisation approach of socio‐technical system design evaluation based on human reliability. Bayesian Belief networks are used to assess human error and system failure (Sutcliffe et al. 1999) based on a variety of high‐level operational scenarios. The System Reliability Analyser tool automates the process by iteratively manipulating the BBN model, presenting the analyst with a three‐level visualisation of the results to diagnose the locus of reliability problems. A case study is presented on the evaluation of two alternative designs of the command and control room of an offshore patrol vessel.

This paper describes a validation approach of a socio-technical design support system using data mining techniques. Bayesian Belief Networks (BBN) are used to assess human error and system failure [13] based on a variety of high-level operational scenarios. The System Reliability Analyser (SRA) tool automates the process by iteratively manipulating the BBN model. Data mining techniques are employed in order to identify whether the initial assumptions embedded in the system reliability model are met by results from scenario-based testing.

This study investigates the usefulness of a scenario advisor tool which was designed to be used in the military domain where human or machine errors cause safety-critical problems. The tool provides traceability between scenario models and requirements and helps to generate new scenarios and scenario variations. Through two series of evaluation sessions, we found that the tool is useful to generate scenarios

Tool support is described for analyzing requirements and creating conceptual models from scenarios. A schema of scenario-based knowledge is proposed that extends the i* ontology with concepts to represent the system environment and natural language semantics to categorize arguments. Modelling tools are introduced to support the process of transforming scenarios into models and requirements. We illustrate use of the tools by analysis of the London Ambulance case study. The advisor guides the analyst with contextual appropriate advice on functional allocation of agent roles and generic requirements to avoid errors and system failure. The advice is based on research in human reliability engineering

Responding to the need within the human-computer interaction field to address ubiquitous and multitasking systems more scientifically, this research extends the usefulness of a new research framework for a particular class of systems. Notification systems are interfaces used in a divided-attention, multitasking situation, attempting to deliver current, valued information through a variety of platforms and modes in an efficient and effective manner. Through review of literature and experiences with empirical dual-task perceptual studies, we recognize a lack of unifying framework for understanding, classifying, analyzing, developing, evaluating, and discussing notification systems--fundamentally inhibiting scientific growth and knowledge reuse that should help designers advance the state-of-the-art. To this end, we developed a framework (referred to as the IRC framework) for notification systems research based on a core taxonomy of critical parameters describing user goals. Next, we extend the framework, focusing on three key aspects: 1) a system description process, allowing articulation of abstract design objectives that focus on critical user requirements; 2) interface usability evaluation tools, enabling comparison of the design and user's models, while supporting generalizability of research and early identification of usability concerns; and 3) design comparison and reuse mechanisms, saving time and effort in requirements analysis and early design stages by enabling design reuse and appreciation of design progress. Results from this research include the development of tools to express IRC design models (IRCspec) and user's models (IRCresults), and the extension of the critical parameters concept. Validation studies with novice designers show sufficient assessment accuracy and consistency. Leveraging these tools that help designers express abstract, yet critical, design intentions and effects as classification and retrieval indices, we develop a repository for reusable design knowledge (a claims library). Responding to challenges of design knowledge access that we observed through initial user testing, we introduce a vision for an integrated design environment (LINK-UP) to operationalize the IRC framework and notification systems claims library in a computer-aided design support system. Proof-of-concept testing results encourage the thought that when valuable design tools embody critical parameters and are coupled with readily accessible reusable design knowledge, interface development will improve as a scientific endeavor. Ph. D.