Are you reading my mind? Modeling students' reading comprehension skills with natural language processing techniques

Laura K. Allen, Erica L. Snow, Danielle McNamara

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

17 Scopus citations

Abstract

This study builds upon previous work aimed at developing a student model of reading comprehension ability within the intelligent tutoring system, iSTART. Currently, the system evaluates students' self-explanation performance using a local, sentence-level algorithm and does not adapt content based on reading ability. The current study leverages natural language processing tools to build models of students' comprehension ability from the linguistic properties of their self-explanations. Students (n = 126) interacted with iSTART across eight training sessions where they self-explained target sentences from complex science texts. Coh-Metrix was then used to calculate the linguistic properties of their aggregated self-explanations. The results of this study indicated that the linguistic indices were predictive of students' reading comprehension ability, over and above the current system algorithms. These results suggest that natural language processing techniques can inform stealth assessments and ultimately improve student models within intelligent tutoring systems.

Original languageEnglish (US)
Title of host publicationACM International Conference Proceeding Series
PublisherAssociation for Computing Machinery
Pages246-254
Number of pages9
Volume16-20-March-2015
ISBN (Print)9781450334174
DOIs
Publication statusPublished - Mar 16 2015
Event5th International Conference on Learning Analytics and Knowledge, LAK 2015 - Poughkeepsie, United States
Duration: Mar 16 2015Mar 20 2015

Other

Other5th International Conference on Learning Analytics and Knowledge, LAK 2015
CountryUnited States
CityPoughkeepsie
Period3/16/153/20/15

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Keywords

  • Corpus linguistics
  • Intelligent Tutoring Systems
  • NATURAL Language Processing
  • Reading comprehension
  • Stealth assessment

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

Cite this

Allen, L. K., Snow, E. L., & McNamara, D. (2015). Are you reading my mind? Modeling students' reading comprehension skills with natural language processing techniques. In ACM International Conference Proceeding Series (Vol. 16-20-March-2015, pp. 246-254). Association for Computing Machinery. https://doi.org/10.1145/2723576.2723617