Effects of adaptive prompted self-explanation on robust learning of second language grammar

Ruth Wylie, Melissa Sheng, Teruko Mitamura, Kenneth R. Koedinger

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

Prompted self-explanation is a successful intervention for many domains. However, in our previous work within the domain of second language grammar learning, we found no advantage for self-explanation over practice alone. Here, we continue testing the generality of self-explanation through the development of an adaptive self-explanation tutor and report on results of a classroom evaluation (N=92) in which we compare the adaptive tutor to a practice-only tutor. We investigate both procedural and declarative knowledge acquisition as well as long-term retention. Results show that while self-explanation takes more time than practice alone, it leads to greater learning of declarative knowledge. However, there are no differences between conditions on immediate or long-term retention measures of procedural knowledge.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence in Education - 15th International Conference, AIED 2011
Pages588-590
Number of pages3
DOIs
StatePublished - 2011
Externally publishedYes
Event15th International Conference on Artificial Intelligence in Education, AIED 2011 - Auckland, New Zealand
Duration: Jun 28 2011Jul 1 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6738 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other15th International Conference on Artificial Intelligence in Education, AIED 2011
Country/TerritoryNew Zealand
CityAuckland
Period6/28/117/1/11

Keywords

  • Long-term Retention
  • Second Language Learning
  • Self-explanation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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