Learning Physics Via Explanation-Based Learning of Correctness and Analogical Search Control,

Abstract

Cascade models humans learning college physics by studying examples and solving problems. It simulates the main qualitative phenomena visible in human protocols of learning, including several strategies for analogical and non-analogical problem solving, and two strategies for studying examples. It learns at the knowledge level by acquiring new physics rules, and it learns search control knowledge. Most importantly, it models a recently observed phenomemon, the self explanation effect, which correlates student's example studying strategies with they amount they learn.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1991
Accession Number
ADA240775

Entities

People

  • Kurt VanLehn
  • Randolph M. Jones

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Air Platforms
  • Autonomy

DTIC Thesaurus Topics

  • Acquisition
  • Applied Computer Science
  • Artificial Intelligence
  • California
  • Classification
  • Cognitive Science
  • Computer Science
  • Computers
  • Equations
  • Machine Learning
  • Physics
  • Procurement
  • Security
  • Students
  • United States
  • Universities
  • Workshops

Fields of Study

  • Education
  • Physics

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  • Artificial Intelligence