A Meta-Analysis of Strategy Use and Performance in the Model of Domain Learning

Daniel L. Dinsmore, Courtney Hattan, Alexandra List

Research output: Chapter or Contribution to BookChapterpeer-review

Abstract

Informed by the Model of Domain Learning, the purpose of this chapter is to examine the relations between strategic processing and performance. The Model of Domain Learning describes how strategy use changes over the course of expertise development. Specifically, that as metacognitive and deep-level processes increase, surface-level processes decrease as learners move from acclimation to expertise. Strategy use changes, along with concomitant changes in knowledge and interest, should produce better task or problem-solving performance. The authors performed a meta-analysis on studies that used the Model of Domain Learning as their framework. Results indicated that most of these studies: relied on retrospective self-report, examined participants in acclimation (the first stage of expertise), and reported the relation between strategic processing and performance to be a small to medium effect (r = .19). Implications for future research using the Model of Domain Learning include exploring additional measures or measurements of strategic processing which may be less likely to attenuate the relation between strategic processing and performance.
Original languageAmerican English
Title of host publicationThe Model of Domain Learning:
Subtitle of host publicationUnderstanding the Development of Expertise
EditorsHelenrose Fives, Daniel Dinsmore
Place of PublicationNew York
Chapter3
Pages37-55
Number of pages19
Edition1st
ISBN (Electronic)9781315458014
DOIs
StatePublished - Dec 14 2017

Keywords

  • Model of Domain learning
  • MDL

Disciplines

  • Computer Sciences
  • Artificial Intelligence and Robotics

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