Are you committed? Investigating interactions among reading commitment, natural language input, and students' learning outcomes

Laura K. Varner, G. Tanner Jackson, Erica L. Snow, Danielle S. McNamara

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

1 Scopus citations

Abstract

The current study identifies relations among students’ natural language input, individual differences in reading commitment, and learning gains in an intelligent tutoring system. Students (n = 84) interacted with iSTART across eight training sessions. Linguistic features of students’ generated self-explanations (SEs) were analyzed using Coh-Metrix. Results indicated that linguistic properties of students’ training SEs were predictive of learning gains, and that the strength and nature of these relations differed for students of low and high commitment to reading.

Original languageEnglish (US)
Title of host publicationProceedings of the 6th International Conference on Educational Data Mining, EDM 2013
EditorsSidney K. D'Mello, Rafael A. Calvo, Andrew Olney
PublisherInternational Educational Data Mining Society
ISBN (Electronic)9780983952527
StatePublished - Jan 1 2013
Event6th International Conference on Educational Data Mining, EDM 2013 - Memphis, United States
Duration: Jul 6 2013Jul 9 2013

Publication series

NameProceedings of the 6th International Conference on Educational Data Mining, EDM 2013

Conference

Conference6th International Conference on Educational Data Mining, EDM 2013
CountryUnited States
CityMemphis
Period7/6/137/9/13

Keywords

  • Intelligent tutoring systems
  • Learning
  • Natural language processing
  • Reading commitment

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

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