@inproceedings{488a21630daf454a9c7721c28ae26785,
title = "Determining paragraph type from paragraph position",
abstract = "Students must be able to competently compose essays in order to succeed in school and progress into the workplace. Current intelligent tutoring systems (ITS) attempt to provide individual training that is lacking in the current educational system. To provide efficient individual training through ITS, the systems must be able to effectively assess writing input from students. Necessary components for computer-based writing tutors are algorithms that mimic human judgments of writing. The current study attempts to establish a connection between paragraph position and human ratings of paragraph type through the use of computational measures provided by Coh-Metrix. We find that expert raters do not easily identify paragraph type and ratings of paragraph type do not map onto paragraph position.",
author = "Dempsey, {Kyle B.} and McCarthy, {Philip M.} and Myers, {John C.} and Jennifer Weston and McNamara, {Danielle S.}",
year = "2009",
month = nov,
day = "4",
language = "English (US)",
isbn = "9781577354192",
series = "Proceedings of the 22nd International Florida Artificial Intelligence Research Society Conference, FLAIRS-22",
pages = "33--38",
booktitle = "Proceedings of the 22nd International Florida Artificial Intelligence Research Society Conference, FLAIRS-22",
note = "22nd International Florida Artificial Intelligence Research Society Conference, FLAIRS-22 ; Conference date: 19-03-2009 Through 21-03-2009",
}