Does size matter? Investigating user input at a larger bandwidth

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

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

3 Scopus citations

Abstract

This study expands upon an existing model of students' reading comprehension ability within an intelligent tutoring system. The current system evaluates students' natural language input using a local student model. We examine the potential to expand this model by assessing the linguistic features of self-explanations aggregated across entire passages. We assessed the relationship between 126 students' reading comprehension ability and the cohesion of their aggregated self-explanations with three linguistic features. Results indicated that the three cohesion indices accounted for variance in reading ability over and above the features used in the current algorithm. These results demonstrate that broadening the window of NLP analyses can strengthen student models within ITSs.

Original languageEnglish (US)
Title of host publicationFLAIRS 2013 - Proceedings of the 26th International Florida Artificial Intelligence Research Society Conference
Pages546-549
Number of pages4
StatePublished - Dec 13 2013
Event26th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2013 - St. Pete Beach, FL, United States
Duration: May 22 2013May 24 2013

Publication series

NameFLAIRS 2013 - Proceedings of the 26th International Florida Artificial Intelligence Research Society Conference

Other

Other26th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2013
CountryUnited States
CitySt. Pete Beach, FL
Period5/22/135/24/13

ASJC Scopus subject areas

  • Artificial Intelligence

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    Varner, L. K., Jackson, G. T., Snow, E. L., & McNamara, D. (2013). Does size matter? Investigating user input at a larger bandwidth. In FLAIRS 2013 - Proceedings of the 26th International Florida Artificial Intelligence Research Society Conference (pp. 546-549). (FLAIRS 2013 - Proceedings of the 26th International Florida Artificial Intelligence Research Society Conference).