Linguistic content analysis as a tool for improving adaptive instruction

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

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

1 Scopus citations

Abstract

This study investigates methods to automatically assess the features of content texts within an intelligent tutoring system (ITS). Coh-Metrix was used to calculate linguistic indices for texts (n = 66) within the reading strategy ITS, iSTART. Coh-Metrix indices for the system texts were compared to students' (n = 126) self-explanation scores to examine the degree to which linguistic indices predicted students' self-explanation quality. Initial analyses indicated no relation between self-explanation scores on a given text and its linguistic properties. However, subsequent analyses indicated the presence of robust text effects when analyses were separated for high and low reading ability students.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence in Education - 16th International Conference, AIED 2013, Proceedings
Pages692-695
Number of pages4
DOIs
StatePublished - Jul 16 2013
Event16th International Conference on Artificial Intelligence in Education, AIED 2013 - Memphis, TN, United States
Duration: Jul 9 2013Jul 13 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7926 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other16th International Conference on Artificial Intelligence in Education, AIED 2013
CountryUnited States
CityMemphis, TN
Period7/9/137/13/13

Keywords

  • ITS
  • Natural Language Processing
  • Readability
  • System Adaptability
  • Text Characteristics
  • Tutoring

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Varner, L. K., Jackson, G. T., Snow, E. L., & McNamara, D. (2013). Linguistic content analysis as a tool for improving adaptive instruction. In Artificial Intelligence in Education - 16th International Conference, AIED 2013, Proceedings (pp. 692-695). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7926 LNAI). https://doi.org/10.1007/978-3-642-39112-5-90