Learning Events in the Acquisition of Three Skills

Abstract

Current theories of cognitive skill acquisition, new problem solving rules are constructed by proceduralization, production compounding, chunking, syntactic generalization, and a variety of other mechanisms. All these mechanisms are assumed to run rather quickly, so a rule's acquisition should be a matter of a few seconds at most. Such 'learning events' might be visible in protocol data. This paper discusses a method for locating the initial use of a rule in protocol data. The method is applied to protocols of subjects learning three tasks; a river crossing puzzle, the Tower of Hanoi, and a topic in college physics. Rules were discovered at the rate of about one every half hour. Most rules required several learning events before they were used consistently, which is not consistent with the one-trial learning predicted by explanation-based learning methods. Some observed patterns of learning events were consistent with a learning mechanism based on syntactic generalization rules. Although most rules seem to have been acquired at impasses--occasions when the subject does not know what to do next--there were clear cases of rules being learned without visible signs of an impasse, which does not support the popular hypothesis that all learning occurs at impasses. Keywords: Strategy discovery; Skill acquisition; Machine learning; Cognitive science; Impasses-driven learning.

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Document Details

Document Type
Technical Report
Publication Date
Jul 21, 1989
Accession Number
ADA219038

Entities

People

  • Kurt VanLehn

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Acquisition
  • Cognitive Science
  • Computer Science
  • Computers
  • Crossings
  • Information Science
  • Instructions
  • Machine Learning
  • Military Research
  • Observation
  • Procurement
  • Psychology
  • River Crossings
  • Simulations
  • Students
  • United States
  • Universities

Readers

  • Artificial Intelligence

Technology Areas

  • AI & ML