Rule-Learning Events in the Acquisition of a Complex Skill

An Evaluation of Cascade

Research output: Contribution to journalArticle

66 Citations (Scopus)

Abstract

Acquiring a complex cognitive skill often involves learning principles of the task domain in the midst of solving problems or studying examples. Cascade is a model of such learning. It includes both rule-based reasoning and several kinds of analogical, case-based reasoning. Task domain principles are represented as rules, and Cascade learns new rules at rule-learning events, which are initiated by an impasse and utilize multiple kinds of reasoning. In this article, I evaluate Cascade's model of rule-learning events by analyzing ones gleaned from protocols of physics students solving problems and studying examples. As expected, Cascade's model is overly simple, but it appears feasible to extend it to cover all the observed learning events. The data themselves were surprising in that there are few learning events relative to the number that could have occurred, and those that did occur often involved forms of reasoning that are considerably shallower than expected. The data suggest ways that instruction can be improved to increase both the quantity and depth of learning events.

Original languageEnglish (US)
Pages (from-to)71-125
Number of pages55
JournalJournal of the Learning Sciences
Volume8
Issue number1
StatePublished - 1999
Externally publishedYes

Fingerprint

Learning
event
evaluation
learning
student of physics
Physics
Students
instruction

ASJC Scopus subject areas

  • Developmental and Educational Psychology
  • Education

Cite this

Rule-Learning Events in the Acquisition of a Complex Skill : An Evaluation of Cascade. / VanLehn, Kurt.

In: Journal of the Learning Sciences, Vol. 8, No. 1, 1999, p. 71-125.

Research output: Contribution to journalArticle

@article{523adc8d57dd4fb1bf6fe0803589861c,
title = "Rule-Learning Events in the Acquisition of a Complex Skill: An Evaluation of Cascade",
abstract = "Acquiring a complex cognitive skill often involves learning principles of the task domain in the midst of solving problems or studying examples. Cascade is a model of such learning. It includes both rule-based reasoning and several kinds of analogical, case-based reasoning. Task domain principles are represented as rules, and Cascade learns new rules at rule-learning events, which are initiated by an impasse and utilize multiple kinds of reasoning. In this article, I evaluate Cascade's model of rule-learning events by analyzing ones gleaned from protocols of physics students solving problems and studying examples. As expected, Cascade's model is overly simple, but it appears feasible to extend it to cover all the observed learning events. The data themselves were surprising in that there are few learning events relative to the number that could have occurred, and those that did occur often involved forms of reasoning that are considerably shallower than expected. The data suggest ways that instruction can be improved to increase both the quantity and depth of learning events.",
author = "Kurt VanLehn",
year = "1999",
language = "English (US)",
volume = "8",
pages = "71--125",
journal = "Journal of the Learning Sciences",
issn = "1050-8406",
publisher = "Routledge",
number = "1",

}

TY - JOUR

T1 - Rule-Learning Events in the Acquisition of a Complex Skill

T2 - An Evaluation of Cascade

AU - VanLehn, Kurt

PY - 1999

Y1 - 1999

N2 - Acquiring a complex cognitive skill often involves learning principles of the task domain in the midst of solving problems or studying examples. Cascade is a model of such learning. It includes both rule-based reasoning and several kinds of analogical, case-based reasoning. Task domain principles are represented as rules, and Cascade learns new rules at rule-learning events, which are initiated by an impasse and utilize multiple kinds of reasoning. In this article, I evaluate Cascade's model of rule-learning events by analyzing ones gleaned from protocols of physics students solving problems and studying examples. As expected, Cascade's model is overly simple, but it appears feasible to extend it to cover all the observed learning events. The data themselves were surprising in that there are few learning events relative to the number that could have occurred, and those that did occur often involved forms of reasoning that are considerably shallower than expected. The data suggest ways that instruction can be improved to increase both the quantity and depth of learning events.

AB - Acquiring a complex cognitive skill often involves learning principles of the task domain in the midst of solving problems or studying examples. Cascade is a model of such learning. It includes both rule-based reasoning and several kinds of analogical, case-based reasoning. Task domain principles are represented as rules, and Cascade learns new rules at rule-learning events, which are initiated by an impasse and utilize multiple kinds of reasoning. In this article, I evaluate Cascade's model of rule-learning events by analyzing ones gleaned from protocols of physics students solving problems and studying examples. As expected, Cascade's model is overly simple, but it appears feasible to extend it to cover all the observed learning events. The data themselves were surprising in that there are few learning events relative to the number that could have occurred, and those that did occur often involved forms of reasoning that are considerably shallower than expected. The data suggest ways that instruction can be improved to increase both the quantity and depth of learning events.

UR - http://www.scopus.com/inward/record.url?scp=0041381613&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0041381613&partnerID=8YFLogxK

M3 - Article

VL - 8

SP - 71

EP - 125

JO - Journal of the Learning Sciences

JF - Journal of the Learning Sciences

SN - 1050-8406

IS - 1

ER -