Question-driven Explanatory Reasoning about Devices that Malfunction

Abstract

The process of personnel selection and assignment involves appropriate matches between the abilities of personnel and the jobs assigned to them. For some jobs, personnel need to be selected and trained on the basis of how well they can operate, repair, and maintain particular devices. We have recently discovered two quick and valid methods of determining whether a person has a deep understanding of a mechanical or electronic device. One method involves question asking, the other eye movements. Regarding question asking, we present a breakdown scenario (e.g., the key turns but the bolt doesnt move, in the context of a cylinder lock) and observe the quality of the questions that participants ask about causes of the malfunction. Regarding eye tracking, we present the breakdown and observe whether deep comprehenders were more likely to fixate on likely damaged components that explain the breakdown. This research tested a cognitive model of question asking (called PREG).

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Document Details

Document Type
Technical Report
Publication Date
Dec 28, 2000
Accession Number
ADA385401

Entities

People

  • Arthur C. Graesser

Organizations

  • University of Memphis

Tags

Communities of Interest

  • Autonomy
  • Human Systems

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Cognition
  • Cognitive Science
  • Communication Systems
  • Computational Science
  • Computer Programming
  • Computers
  • Educational Psychology
  • Eye Movements
  • Language
  • Natural Language Processing
  • Personnel Selection
  • Psychological Tests
  • Psychology
  • Regression Analysis
  • Statistics
  • Students

Readers

  • Artificial Intelligence
  • Educational Psychology
  • Instructional Design and Training Evaluation.

Technology Areas

  • Microelectronics