@inproceedings{df314cb852a94f94bc2ca23eea48bb00,
title = "Linguistic content analysis as a tool for improving adaptive instruction",
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.",
keywords = "ITS, Natural Language Processing, Readability, System Adaptability, Text Characteristics, Tutoring",
author = "Varner, {Laura K.} and Jackson, {G. Tanner} and Snow, {Erica L.} and Danielle McNamara",
year = "2013",
doi = "10.1007/978-3-642-39112-5_90",
language = "English (US)",
isbn = "9783642391118",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "692--695",
booktitle = "Artificial Intelligence in Education - 16th International Conference, AIED 2013, Proceedings",
note = "16th International Conference on Artificial Intelligence in Education, AIED 2013 ; Conference date: 09-07-2013 Through 13-07-2013",
}