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Steven R. Haynes

Bio: Steven R. Haynes is an academic researcher from Pennsylvania State University. The author has contributed to research in topics: Soar & Empirical research. The author has an hindex of 12, co-authored 45 publications receiving 527 citations. Previous affiliations of Steven R. Haynes include London School of Economics and Political Science & Penn State College of Information Sciences and Technology.

Papers
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Journal ArticleDOI
TL;DR: In this paper, a case study of one community's emergency planning activities is presented, where five aspects of community preparedness are discussed: collaborative efforts, local area details, local culture, geographic information, and emergency plans.
Abstract: Emergencies often have causes and effects that are global. However, emergencies are also inherently local: They occur in a particular place and point in time. While it is critical for governments and society to better organize emergency management top-down, it is also important to become more aware of local community-level values, planning, involvement, knowledge, and skill. Local communities plan collaboratively for potential emergencies of varying scales. Our discipline of Human-Computer Interaction studies the interaction between people and computers. Researchers in this field consider how information technology affects emergency management. They aim to improve emergency management through the design of useful and novel interfaces to technology. The purpose of our work was to take a broader perspective on emergency management and investigate the models and patterns of emergency-related work practices. In particular, we examined emergency management from a local community perspective. This focus on local communities partly stems from our prior research on community groups and their use of information technology. It is also motivated by the realization that emergencies are local events, which happen in communities. This paper reports on a study of one community’s emergency planning activities. Five aspects of community preparedness are discussed: collaborative efforts, local area details, local culture, geographic information, and emergency plans, and a case study provides concrete examples of each. Local community preparedness is complex and gives rise to many collaboration issues. Revealing this complexity, the paper offers some implications for community emergency management

74 citations

Journal ArticleDOI
TL;DR: Designs that can be reused to create intelligent agents capable of explaining themselves are described and inscribe lessons learned from prior research and provide guidance for incorporating explanation facilities into intelligent systems.
Abstract: Explanation is an important capability for usable intelligent systems, including intelligent agents and cognitive models embedded within simulations and other decision support systems. Explanation facilities help users understand how and why an intelligent system possesses a given structure and set of behaviors. Prior research has resulted in a number of approaches to provide explanation capabilities and identified some significant challenges. We describe designs that can be reused to create intelligent agents capable of explaining themselves. The designs include ways to provide ontological, mechanistic, and operational explanations. These designs inscribe lessons learned from prior research and provide guidance for incorporating explanation facilities into intelligent systems. The designs are derived from both prior research on explanation tool design and from the empirical study reported here on the questions users ask when working with an intelligent system. We demonstrate the use of these designs through examples implemented using the Herbal high-level cognitive modeling language. These designs can help build better agents-they support creating more usable and more affordable intelligent agents by encapsulating prior knowledge about how to generate explanations in concise representations that can be instantiated or adapted by agent developers.

70 citations

Proceedings ArticleDOI
06 Nov 2004
TL;DR: The results suggest that scenario-based evaluation is effective in helping to focus evaluation efforts and in identifying the range of technical, human, organizational and other contextual factors that impact system success.
Abstract: We report on the use of scenario-based methods for evaluating collaborative systems. We describe the method, the case study where it was applied, and provide results of its efficacy in the field. The results suggest that scenario-based evaluation is effective in helping to focus evaluation efforts and in identifying the range of technical, human, organizational and other contextual factors that impact system success. The method also helps identify specific actions, for example, prescriptions for design to enhance system effectiveness. However, we found the method somewhat less useful for identifying the measurable benefits gained from a CSCW implementation, which was one of our primary goals. We discuss challenges faced applying the technique, suggest recommendations for future research, and point to implications for practice.

66 citations

Dissertation
01 Jan 2002
TL;DR: This study proposes a model of IS explanation structure and content derived from formal theories of explanation with a method for obtaining this content based on design rationale and investigates the relationship between the information systems development context, and the context in which such systems are used.
Abstract: This dissertation investigates the relationship between the information systems (IS) development context, and the context in which such systems are used. Misunderstandings and ambiguities emerge in the space between these contexts and often result in construction of systems that fail to meet the requirements and expectations of their intended users. This study explores this problem using an approach derived from three largely separate and distinct fields: explanation facilities in information systems, theories of explanation, and design rationale. Explanation facilities are typically included in knowledge-based information systems, where their purpose is to provide system users with the underlying reasons for why the system reaches a particular conclusion or makes a particular recommendation. Prior research suggests that the presence of an explanation facility leads to increased acceptance of these conclusions and recommendations, therefore enhancing system usability. Theory of explanation is a field of study in which philosophers attempt to describe the unique nature of explanation and to identify criteria for explanation evaluation. Design rationale research is concerned with the capture, representation, and use of the deep domain and artefact knowledge that emerges from the design process. The design rationale approach goes beyond specification and suggests that to understand a system requires knowledge of the arguments that led to its realisation. This study proposes a model of IS explanation structure and content derived from formal theories of explanation with a method for obtaining this content based on design rationale. The study has four goals: to derive a theory of explanation specific to the domain of information systems; to examine this definition empirically through a study involving IS development and management professionals; to investigate in a case study whether the information needed to populate the explanation model can be captured using design rationale techniques; and construction of prototype software to deliver explanations per the proposed framework.

41 citations

28 Feb 2006
TL;DR: This symposium will identify lessons for the development of high level behavior representation languages as well as for their users by identifying generalities and common lessons.
Abstract: : There has only been a short history of high level languages to model human cognition based on cognitive architectures. TAQL is an early example (Yost, 1993). TAQL showed a large (3x) speed increase over plain Soar, but because it did not support Soar's learning mechanism and because Soar changed soon after its release, TAQL's impact was not as great as its developer probably would have liked. It is time again to consider high level behavior representation languages. Cognitive models and intelligent agents are becoming more complex and pervasive. This is driving the need for development environments that make it easier to create, share, and reuse cognitive models. Several high level modeling languages have recently been created and several of them are described briefly here. These languages are each different, but they have a common goal of making modeling human data easier to perform. We can now see some generalities and common lessons. By holding this symposium we will identify lessons for the development of these languages as well as for their users. These languages are reviewed briefly in the next section.

35 citations