Search (5 results, page 1 of 1)

0.0613591 = product of:
  0.2454364 = sum of:
    0.2454364 = weight(_text_:engineering in 8755) [ClassicSimilarity], result of:
      0.2454364 = score(doc=8755,freq=6.0), product of:
        0.23872319 = queryWeight, product of:
          5.372528 = idf(docFreq=557, maxDocs=44218)
          0.044434052 = queryNorm
        1.0281214 = fieldWeight in 8755, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          5.372528 = idf(docFreq=557, maxDocs=44218)
          0.078125 = fieldNorm(doc=8755)
  0.25 = coord(1/4)

Abstract

Cognitive systems engineering is the discipline underlying the design of computer-based information systems to support human work and endeavor. The book describes a cross-disciplinary framework for the integration of model concenpts from many different disciplines, such as engineering, psychology, cognitive science, management science, information and computer science. It is based on actual work performance in several domains

0.049595967 = product of:
  0.19838387 = sum of:
    0.19838387 = weight(_text_:engineering in 3249) [ClassicSimilarity], result of:
      0.19838387 = score(doc=3249,freq=2.0), product of:
        0.23872319 = queryWeight, product of:
          5.372528 = idf(docFreq=557, maxDocs=44218)
          0.044434052 = queryNorm
        0.83102053 = fieldWeight in 3249, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          5.372528 = idf(docFreq=557, maxDocs=44218)
          0.109375 = fieldNorm(doc=3249)
  0.25 = coord(1/4)

0.03067955 = product of:
  0.1227182 = sum of:
    0.1227182 = weight(_text_:engineering in 6113) [ClassicSimilarity], result of:
      0.1227182 = score(doc=6113,freq=6.0), product of:
        0.23872319 = queryWeight, product of:
          5.372528 = idf(docFreq=557, maxDocs=44218)
          0.044434052 = queryNorm
        0.5140607 = fieldWeight in 6113, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          5.372528 = idf(docFreq=557, maxDocs=44218)
          0.0390625 = fieldNorm(doc=6113)
  0.25 = coord(1/4)

Abstract

This paper presents a framework for design of work support systems for modern, dynamic work environemnt in which stable work procedures are replaced with discretionary tasks and many action possibilities are available to the user. In this situation, classic task analysis is less effective and a framework is therefore presented for work analysis, separating a representation of the work domain, its means and ends, its relational structure, and the effective task strategies among which the user may choose, from a representation of the users' general background, resources, cognitive style and subjective preferences. The aim is to design systems for information seeking in complex work domains characterized by rapid changes in users' information needs that leave the freedom open to a user to choose a task strategy that suites the user in the particular situation. An important feature of this approach is a human-work interface with a transparent presentation of the action possibilities and functional/intentional boundaries of the work domain relevant for typical task situations and user categories. This is illustrated by examples from 2 different domains that merge the cognitive engineering approach with information science disciplines: the library domain, and information seeking in the engineering design domain using the Internet

0.014170276 = product of:
  0.056681104 = sum of:
    0.056681104 = weight(_text_:engineering in 2755) [ClassicSimilarity], result of:
      0.056681104 = score(doc=2755,freq=2.0), product of:
        0.23872319 = queryWeight, product of:
          5.372528 = idf(docFreq=557, maxDocs=44218)
          0.044434052 = queryNorm
        0.23743443 = fieldWeight in 2755, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          5.372528 = idf(docFreq=557, maxDocs=44218)
          0.03125 = fieldNorm(doc=2755)
  0.25 = coord(1/4)

Abstract

Collaborative integration of knowledge in distributed and cross-disciplinary work domains poses a number of challenges to classification, comprising: 1) how to analyze the actors' current practice of integration of knowledge and 2) how to model consistent semantic support of diverse interpretive perspectives among the actors. This paper introduces a cognitive systems engineering approach to modelling collaborative integration of knowledge in work domains. A generic means-ends model provides a theoretical foundation for mapping the territory of collaborative work. A decision task model captures the actors' distributed decision-making in integration of knowledge. The problem of collaborative integration of knowledge in a distributed web-based film collaboratory is explored through an empirical case of collaborative film indexing. The empirical study identified a lack of tools for consistent support of integration of knowledge. The means-ends model and the decision task model guided the design of a conceptual structure of the common workspace of film indexing. The paper concludes with a proposal for further work an models for integration of knowledge through ecological classification schemes. 1. Introduction Current work practice and knowledge production to an increasing degree involves actors from different disciplines, cultures and organisations. Additionally, current work practice not only relies an authoritative orderings of knowledge, but also relies an the dynamism of the actors' ongoing collaborative integration of knowledge, i.e. their shared interpretations of knowledge, exchange of perspectives and joint knowledge production. Consequently, in order to support the actors' ongoing collaborative integration of knowledge, the design of support tools, like classification schemes, must address not only the order of knowledge, but also the situational contexts where collaborative integration of knowledge occurs. This paper introduces an ecological approach to integration of knowledge across boundaries in distributed collaboratory work environments, which is founded an (a) work domain analysis (b) the development of models for collaborative integration of knowledge. The work domain analysis is based an means-ends analysis of the territory of work and the actors' information needs during decision making. The result is conceptual structures of collaborative work that can be used to create collaborative classification schemes. Previous work an design of ecological classification schemes proposed that such schemes should be based an a finegrained empirical analysis of actors' collaborative decision tasks in order to identify the knowledge produced and needed by the actors (Pejtersen & Albrechtsen, 2000).

0.007525251 = product of:
  0.030101003 = sum of:
    0.030101003 = product of:
      0.060202006 = sum of:
        0.060202006 = weight(_text_:22 in 5835) [ClassicSimilarity], result of:
          0.060202006 = score(doc=5835,freq=2.0), product of:
            0.15560047 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.044434052 = queryNorm
            0.38690117 = fieldWeight in 5835, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.078125 = fieldNorm(doc=5835)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Date

5. 8.2006 13:22:44