Making systems sensitive to the user's time and  working memory constraints

Jameson, Anthony; Schäfer, Reiner; Weis, T.; Berthold, André; Weyrath, Thomas

doi:10.1145/291080.291094

Cited by 27 publications

(15 citation statements)

References 7 publications

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“…For concreteness, consider the example scenario handled by the dialog system READY (see, e.g., Jameson et al, 1999): Users are drivers whose cars need minor repairs; they request assistance from the system in natural language by phone. Our first step in studying this scenario was to get a concrete idea of the cognitive load induced by this situation and the ways in which it is ?…”

Section: Scenario and Field Studymentioning

confidence: 99%

“…Distracting aspects of the situation can include noises and events that interfere with one's concentration on task performance, as well as internal factors like emotional stress that have similar effects. In the dynamic Bayesian networks that form the core of READY's user model, these types of influence on a user's continually changing cognitive load are modeled separately (see, e.g., Jameson et al, 1999;Schäfer and Weyrath, 1997). In this paper, we will simply consider the problem of assessing the total load currently placed on U's working memory, regardless of its origin.…”

Section: Determinants Of Cognitive Loadmentioning

confidence: 99%

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Interpreting Symptoms of Cognitive Load in Speech Input

Berthold¹,

Jameson²

1999

CISM International Centre for Mechanical Sciences

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Abstract. Users of computing devices are increasingly likely to be subject to situationally determined distractions that produce exceptionally high cognitive load. The question arises of how a system can automatically interpret symptoms of such cognitive load in the user's behavior. This paper examines this question with respect to systems that process speech input. First, we synthesize results of previous experimental studies of the ways in which a speaker's cognitive load is reflected in features of speech. Then we present a conceptualization of these relationships in terms of Bayesian networks. For two examples of such symptoms-sentence fragments and articulation rate-we present results concerning the distribution of the symptoms in realistic assistance dialogs. Finally, using artificial data generated in accordance with the preceding analyses, we examine the ability of a Bayesian network to assess a user's cognitive load on the basis of limited observations involving these two symptoms.

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Section: Scenario and Field Studymentioning

confidence: 99%

Section: Determinants Of Cognitive Loadmentioning

confidence: 99%

Interpreting Symptoms of Cognitive Load in Speech Input

Berthold¹,

Jameson²

1999

CISM International Centre for Mechanical Sciences

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“…The retrieval task itself differs from that assumed under normal IR circumstances due to the nature of conducting searches in a non-static, transient environment, where there is a greater risk that user performance may be influenced by outside factors with the increased potential for distractions of noise and interruptions (Jameson, Schfer, Weis, Berthold, & Weyrath, 1998). These distractions may even be user driven, as the user may be engaged in other activities at the time of searching and cannot commit their full attention to the task of accessing information.…”

Section: Introductionmentioning

confidence: 99%

Effective search results summary size and device screen size: Is there a relationship?

Sweeney

Crestani

2006

Information Processing & Management

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In recent years, small screen devices have seen widespread increase in their acceptance and use. Combining mobility with increased technological advances many such devices can now be considered mobile information terminals. However, user interactions with small display devices remain a challenge due to the inherent input restrictions and limited display capabilities. These challenges are particularly evident for tasks, such as information seeking. For the presentation of retrieval results we consider that a personalised and context dependent approach could offer benefits, particularly for retrieving information in a non-traditional environment. As a starting point, in this paper we report an investigation into the effects of summary length as a function of screen size, where query-biased summaries are used to present retrieval results. Following a brief description of our proposed system, we report a user study aimed at exploring whether there is an optimal summary size for three types of device (smartphone, PDA and laptop), given their different screen sizes.

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“…For the Mars Medical Assistant, Francisco-Revilla and Shipman classify three di erent situations under time pressure: emergency, consultation and educational. Time pressure is also the main characteristic of the user's pro®le used by Jameson et al (1999) in Ready.…”

Section: Situation Variablesmentioning

confidence: 99%

Review and reappraisal of adaptive interfaces: Toward biologically inspired paradigms

Rothrock

Koubek²,

Fuchs³

et al. 2002

Theoretical Issues in Ergonomics Science

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The ®eld of Adaptive Interfaces has been an active area of research for over 10 years. While there have been great advances, unresolved issues remain. The paper presents a reappraisal of adaptive interfaces with an eye toward addressing these issues using biologically inspired methods. We ®rst de®ne a general and theoretical model of adaptive interfaces based on a survey of existing research. Using our generalized adaptive interface model, we then proceed to build taxonomies of variables used for adaptation. The aim is to provide researchers, designers and builders a better understanding of the underlying mechanisms, processes and outcomes of adaptive interfaces. From our review, we propose design rules that address three primary elements of a generalized adaptive interface: the identi®ca-tion of variables that call for adaptation, the determination of necessary modi®-cations to the interface, and the selection of the decision inference mechanism. We then turn to the investigation of an alternative method for adaptive interface design. To ®nd a method that corresponds better to human decision-making, which has been characterized as situated and recognition-primed, we explored biologically inspired techniques. In particular, we focus on the correspondence between human decision-making behaviour and the concepts of emergence and self-organization. While our ruminations are speculative, the future of biologically inspired interfaces seems promising.

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Making systems sensitive to the user's time and working memory constraints

Cited by 27 publications

References 7 publications

Interpreting Symptoms of Cognitive Load in Speech Input

Interpreting Symptoms of Cognitive Load in Speech Input

Effective search results summary size and device screen size: Is there a relationship?

Review and reappraisal of adaptive interfaces: Toward biologically inspired paradigms

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