A Cognitive Model of Pedagogical Question Asking

Abstract

Soldiers will be interacting more directly with high-technology, computer-based training systems in the Army of the future. Soldier trainees interacting with these machines will profit from the ability to ask questions as they learn. A fundamental problem we need to address is how to create computer- based tutorial dialogues that will allow soldiers training on these systems to ask questions easily and naturally. The first step toward creating interactive tutorial dialogues is to understand the cognitive role of pedagogical question asking in a computer-based learning environment. Questions asked during acquisition of a complex skill reflect the information military students require at different stages of learning. Evaluation of the kinds of questions asked in a particular MOS should provide information descriptive of each student's current knowledge state. Question analysis can be used for defining the goals, operators, and methods a student is using or needs at a given time during the instructional sequence. Mapping the questions asked at a particular point during the acquisition process onto the conceptual representation for the MOS will indicate what kind of knowledge is being processed by a student.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1988
Accession Number
ADA194139

Entities

People

  • Merryanna L. Swartz

Organizations

  • U.S. Army Research Institute for the Behavioral and Social Sciences

Tags

Communities of Interest

  • Biomedical
  • Engineered Resilient Systems
  • Human Systems

DTIC Thesaurus Topics

  • Classification
  • Cognition
  • Cognitive Science
  • Computers
  • Environment
  • Language
  • Learning
  • Military Research
  • Military Training
  • Natural Languages
  • Psychology
  • Sequences
  • Social Sciences
  • Students
  • Test And Evaluation
  • Trainees
  • Training

Readers

  • Instructional Design and Training Evaluation.
  • STEM Education
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.