Automation is becoming more prevalent on commercial ships. When automation is introduced, the mariner's tasks change. Certain manual tasks may no longer be required, and there are new tasks specific to the operation of the automated system. In some cases, tasks which were formerly performed by two or more mariners are now combined into the responsibility of a single crew member. As the knowledge and skills required to operate a vessel change, the U.S. Coast Guard needs to reflect these changes in its qualifications and licensing/certification requirements. However, the U.S. Coast Guard currently lacks a systematic approach for determining the effects of new automation on mariner qualifications. This paper presents an overview of four different, but complementary, methodologies being developed to assess how a given automated system changes shipboard tasks and the knowledge and skills required of the crew. The report focuses on one of these methods, a powerful new application of cognitive analysis. Cognitive analysis identifies the mental demands (such as visual detection, computation, and memory) placed on the mariner while performing shipboard tasks. A comparison of the mental demands associated with manual versus automated tasks can highlight differences in the knowledge, skills, and abilities required to perform the tasks. Thus, cognitive analysis identifies changes which may be needed in training and licensing/certification as a result of shipboard automation. The body of the report is a technical documentation of the cognitive analysis method. Shipboard automation, Task analysis, Training, Licensing examination content, Qualifications, Cognitive analysis, Human factors.


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    Title :

    Cognitive Analysis of Navigation Tasks: A Tool for Training Assessment and Equipment Design


    Contributors:
    T. F. Sanquist (author) / J. D. Lee (author) / A. M. Rothblum (author)

    Publication date :

    1994


    Size :

    86 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English





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