Practitioner-customizable clinical information systems: a case study to ground further research and development opportunities

The uptake of electronic records and information technology support in intensive care medicine has been slower than many people predicted. One of the engineering challenges to overcome has been the subtle, but important, variation in clinical practice in different units. A relatively recent innovation that addresses this challenge is practitioner-customizable clinical information systems, allowing clinicians wide scope in adjusting their systems to suit their clinical practice. However, these systems present a significant design challenge, not only of added technical complexity, but in providing tools that support clinicians in doing many of the tasks of a software engineer. This paper reviews the use of a commercially available clinical information system that is intended to be practitioner-customizable, and considers the further design and development of tools to support healthcare practitioners doing end-user customization on their own clinical information systems.Peer Reviewe

End user programming of awareness systems : addressing cognitive and social challenges for interaction with aware environments

The thesis is put forward that social intelligence in awareness systems emerges from end-Users themselves through the mechanisms that support them in the development and maintenance of such systems. For this intelligence to emerge three challenges have to be addressed, namely the challenge of appropriate awareness abstractions, the challenge of supportive interactive tools, and the challenge of infrastructure. The thesis argues that in order to advance towards social intelligent awareness systems, we should be able to interpret and predict the success or failure of such systems in relationship to their communicational objectives and their implications for the social interactions they support. The FN-AAR (Focus-Nimbus Aspects Attributes Resources) model is introduced as a formal model which by capturing the general characteristics of the awareness-systems domain allows predictions about socially salient patterns pertaining to human communication and brings clarity to the discussion around relevant concepts such as social translucency, symmetry, and deception. The thesis recognizes that harnessing the benefits of context awareness can be problematic for end-users and other affected individuals, who may not always be able to anticipate, understand or appreciate system function, and who may so feel their own sense of autonomy and privacy threatened. It introduces a set of tools and mechanisms that support end-user control, system intelligibility and accountability. This is achieved by minimizing the cognitive effort needed to handle the increased complexity of such systems and by enhancing the ability of people to configure and maintain intelligent environments. We show how these tools and mechanisms empower end-users to answer questions such as "how does the system behave", "why is something happening", "how would the system behave in response to a change in context", and "how can the system’s behaviour be altered" to achieve intelligibility, accountability, and end-user control. Finally, the thesis argues that awareness applications overall can not be examined as static configurations of services and functions, and that they should be seen as the results of both implicit and explicit interaction with the user. Amelie is introduced as a supportive framework for the development of context-aware applications that encourages the design of the interactive mechanisms through which end-users can control, direct and advance such systems dynamically throughout their deployment. Following the recombinant computing approach, Amelie addresses the implications of infrastructure design decisions on user experience, while by adopting the premises of the FN-AAR model Amelie supports the direct implementation of systems that allow end-users to meet social needs and to practice extant social skills

TOWARD SYMBIOTIC HUMAN-AI INTERACTION FOCUSING ON PROGRAMMING BY EXAMPLE

Programming has become a new literacy, but is still inaccessible to ordinary people. Programming-by-example (PBE) is an alternative approach that allows people to teach computers repetitive tasks by demonstrating couple input and output examples of the tasks. While the advancements of PBE have been mainly driven by algorithmic improvements, a growing community of researchers started realizing the importance of issues on the human side of PBE. For instance, inexperienced users often find it hard to provide complete and consistent examples, which is crucial for computers to learn the correct programs. Unfortunately, most PBE systems have limited ways to communicate with users about what it can or cannot do, and how to handle unsuccessful situations. The lack of symbiotic interaction between human users and PBE engines remain as a major hurdle against a widespread adoption of PBE techniques. To address the issues on the human side of PBE, this dissertation has four research threads. First, we began with two formative studies to establish a better understanding of inexperienced users' needs and mental models. Second, based on the findings of the formative studies, we developed a Visual Environment for Symbiotic Programming, called VESPY. VESPY interleaves visual programming and PBE techniques, enabling users (1) to decompose complex tasks into small modules on its 2-d grid, and (2) to complete each module by providing input and output examples. Four sample programs demonstrate VESPY's remarkable versatility. However, we also noticed that VESPY still had a number of usability issues. Third, to better understand the usability issues and how to help users out from common mistakes, we conducted an online user study that observed how inexperience users perform program decomposition and disambiguation, which are the two core activities of PBE. We identified seven types of mistakes, and reaffirmed that informative feedback on those mistakes is crucial for designing usable systems. Finally, we explored the design space of feedback components, in order to understand their impact on user's experience. My dissertation contributes to the AI and HCI communities with: (i) identification of unmet needs of end-users of the Web; (ii) characterization of non-programmers’ mental model; (iii) design process of interleaving visual programming and PBE; (iv) identification of mistakes people make while using PBE; and (v) design and assessment of feedback components for PBE users