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    A Method for Eliciting, Preserving, and Sharing the Knowledge of Forecasters

    Source: Weather and Forecasting:;2006:;volume( 021 ):;issue: 003::page 416
    Author:
    Hoffman, Robert R.
    ,
    Coffey, John W.
    ,
    Ford, Kenneth M.
    ,
    Novak, Joseph D.
    DOI: 10.1175/WAF927.1
    Publisher: American Meteorological Society
    Abstract: As in many domains of modern work, a concern in weather forecasting is the loss of expertise, due either to reassignment or retirement. This note reports upon a project that demonstrates a procedure that can be used to capture forecasters' knowledge of weather concepts. The System To Organize Representations in Meteorology-Local Knowledge (STORM-LK) focuses on weather phenomena in the Gulf Coast region. Forecasters and aerographers at Whiting Field, Naval Air Station, in Pensacola, Florida, participated in a knowledge elicitation procedure that yielded diagrammatic models of their knowledge in the form of ?concept maps.? The demonstration suggests the following: 1) the feasibility of using the approach to elicit knowledge so that it might be preserved and shared and 2) the use of concept maps to integrate and navigate through the various instructional and data resources that are used in forecasting. It is envisioned that a knowledge model patterned after STORM-LK could be created for other regions, and for many other topics. Throughout the weather forecasting community, the approach presented here could support the processes of knowledge capture and preservation at the organizational level, with the ultimate goal of fostering active learning and the achievement of local expertise.
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      A Method for Eliciting, Preserving, and Sharing the Knowledge of Forecasters

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4231304
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    contributor authorHoffman, Robert R.
    contributor authorCoffey, John W.
    contributor authorFord, Kenneth M.
    contributor authorNovak, Joseph D.
    date accessioned2017-06-09T17:35:08Z
    date available2017-06-09T17:35:08Z
    date copyright2006/06/01
    date issued2006
    identifier issn0882-8156
    identifier otherams-87615.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4231304
    description abstractAs in many domains of modern work, a concern in weather forecasting is the loss of expertise, due either to reassignment or retirement. This note reports upon a project that demonstrates a procedure that can be used to capture forecasters' knowledge of weather concepts. The System To Organize Representations in Meteorology-Local Knowledge (STORM-LK) focuses on weather phenomena in the Gulf Coast region. Forecasters and aerographers at Whiting Field, Naval Air Station, in Pensacola, Florida, participated in a knowledge elicitation procedure that yielded diagrammatic models of their knowledge in the form of ?concept maps.? The demonstration suggests the following: 1) the feasibility of using the approach to elicit knowledge so that it might be preserved and shared and 2) the use of concept maps to integrate and navigate through the various instructional and data resources that are used in forecasting. It is envisioned that a knowledge model patterned after STORM-LK could be created for other regions, and for many other topics. Throughout the weather forecasting community, the approach presented here could support the processes of knowledge capture and preservation at the organizational level, with the ultimate goal of fostering active learning and the achievement of local expertise.
    publisherAmerican Meteorological Society
    titleA Method for Eliciting, Preserving, and Sharing the Knowledge of Forecasters
    typeJournal Paper
    journal volume21
    journal issue3
    journal titleWeather and Forecasting
    identifier doi10.1175/WAF927.1
    journal fristpage416
    journal lastpage428
    treeWeather and Forecasting:;2006:;volume( 021 ):;issue: 003
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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