Task analysis of discrete and continuous skills: a dual methodology approach to human skills capture for automation.

There is a growing requirement within the field of intelligent automation for a formal methodology to capture and classify explicit and tacit skills deployed by operators during complex task performance. This paper describes the development of a dual methodology approach which recognises the inheren...

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Publicado en:Theoretical Issues in Ergonomics Science Vol. 16; no. 5; pp. 513 - 533
Autores principales: Everitt, J., Fletcher, S., Caird-Daley, A.
Formato: research tables/charts Journal Article
Publicado: Taylor & Francis Ltd Sep2015
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Task analysis of discrete and continuous skills: a dual methodology approach to human skills capture for automation.
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          Everitt, J.
          Fletcher, S.
          Caird-Daley, A.
        affil: Industrial Psychology and Human Factors Group, School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield, UK
      sug:
        subj:
          Job Performance
          Automation
          Task Performance and Analysis
          Ergonomics
          Human
          Male
          Female
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      ab: There is a growing requirement within the field of intelligent automation for a formal methodology to capture and classify explicit and tacit skills deployed by operators during complex task performance. This paper describes the development of a dual methodology approach which recognises the inherent differences betweencontinuoustasks anddiscretetasks and which proposes separate methodologies for each. Both methodologies emphasise capturing operators’ physical, perceptual, and cognitive skills, however, they fundamentally differ in their approach. The continuous task analysis recognises the non-arbitrary nature of operation ordering and that identifying suitable cues for subtask is a vital component of the skill. Discrete task analysis is a more traditional, chronologically ordered methodology and is intended to increase the resolution of skill classification and be practical for assessing complex tasks involving multiple unique subtasks through the use of taxonomy of generic actions for physical, perceptual, and cognitive actions.
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    language: English
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