DEVELOPMENT OF A TAXONOMY OF HUMAN PERFORMANCE: A REVIEW OF BIOLOGICAL TAXONOMY AND CLASSIFICATION

Abstract

The review of systematic biology was undertaken to determine whether any of the concepts and methods from systematic biology could be applied to the problems of task taxonomy and task classification. Although the review found that biology could not supply ready solutions to problems in the classification of tasks, certain taxonomic concepts were extracted which should be of value. The importance of a well-developed logic and rationale for classification was noted. Moreover, it was determined that the purpose of a classification must be established before the nature of the objects to be classified or the methods of classification can be specified. In considering the logic for classification three types of classification were identified and defined: teleological, consociative, and theoretical classification. Of these three, only theoretical classifications, classifications which describe the objects of interest in terms of inherent attributes of the objects themselves, are generally applicable or theoretically useful. Three approaches to the development of theoretical classification also were considered. Numerical taxonomy, the most empirical of the three biological approaches to classification, was found to provide a sound basis for the development of classificatory systems and was suggested as a model for the development of task classifications.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1969
Accession Number
AD0705255

Entities

People

  • George C. Theologus

Organizations

  • American Institutes for Research

Tags

Communities of Interest

  • Air Platforms
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Animals
  • Biology
  • Classification
  • Computer Programming
  • Computer Science
  • Computers
  • Databases
  • Diseases And Disorders
  • Human Resources
  • Judgment
  • Motor Skills
  • Nomenclature
  • Observation
  • Psychology
  • Systems Engineering
  • Taxonomy
  • Vulnerability

Readers

  • Instructional Design and Training Evaluation.
  • Neural Network Machine Learning.
  • Systems Analysis and Design