Exploring the effectiveness of a novel feedback mechanism within an intelligent tutoring system

Jeremiah Sullins, Scotty Craig, Xiangen Hu

Research output: Contribution to journalArticle

7 Scopus citations

Abstract

The purpose of this study was to explore the effectiveness of a new feedback mechanism within an intelligent tutoring system called AutoTutor LITE. Participants were randomly assigned to one of three feedback manipulation conditions within the context of complex scientific material: 1) learners' characteristics curves; 2) random; 3) no feedback. Results revealed that the participants receiving the new feedback mechanism (LCC) showed significantly higher learning gains when compared to the random feedback or no feedback manipulations. Additionally, there were no differences discovered between random feedback and no feedback. Interpretation and implications of results are discussed.

Original languageEnglish (US)
Pages (from-to)220-236
Number of pages17
JournalInternational Journal of Learning Technology
Volume10
Issue number3
DOIs
StatePublished - Jan 1 2015

Keywords

  • Cognition
  • Feedback
  • ITS
  • Intelligent tutoring system
  • Learning
  • Learning technologies

ASJC Scopus subject areas

  • Education

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