Extracting Information from Natural Language Input to an Intelligent Tutoring System
M. Glass, and M. Evens. Far East Journal of Experimental and Theoretical Artificial Intelligence, 1 (2):
87-125(August 2008)
Abstract
We have constructed a new module to process student natural language
input to CIRCSIM-Tutor, an intelligent tutoring system designed to help medical students learn to solve problems involving the negative
feedback process that regulates blood pressure in the human body.
CIRCSIM-Tutor spends most of its time engaging the student in a
natural language-based dialogue. The new input understander uses an
information extraction approach that is robust enough to handle freeform student input. We describe an evaluation of CIRCSIM-Tutor by forty-two students at Rush Medical College, with particular emphasis on the performance of the input understander.
Description
Glass: Extracting information from natural language... - Google Scholar
%0 Journal Article
%1 Glass08
%A Glass, Michael S.
%A Evens, Martha W.
%D 2008
%J Far East Journal of Experimental and Theoretical Artificial Intelligence
%K CIRCSIM-Tutor intelligent language natural tutoring
%N 2
%P 87-125
%T Extracting Information from Natural Language Input to an Intelligent Tutoring System
%U http://www.pphmj.com
%V 1
%X We have constructed a new module to process student natural language
input to CIRCSIM-Tutor, an intelligent tutoring system designed to help medical students learn to solve problems involving the negative
feedback process that regulates blood pressure in the human body.
CIRCSIM-Tutor spends most of its time engaging the student in a
natural language-based dialogue. The new input understander uses an
information extraction approach that is robust enough to handle freeform student input. We describe an evaluation of CIRCSIM-Tutor by forty-two students at Rush Medical College, with particular emphasis on the performance of the input understander.
@article{Glass08,
abstract = {We have constructed a new module to process student natural language
input to CIRCSIM-Tutor, an intelligent tutoring system designed to help medical students learn to solve problems involving the negative
feedback process that regulates blood pressure in the human body.
CIRCSIM-Tutor spends most of its time engaging the student in a
natural language-based dialogue. The new input understander uses an
information extraction approach that is robust enough to handle freeform student input. We describe an evaluation of CIRCSIM-Tutor by forty-two students at Rush Medical College, with particular emphasis on the performance of the input understander.},
added-at = {2011-06-13T14:04:03.000+0200},
author = {Glass, Michael S. and Evens, Martha W.},
biburl = {https://www.bibsonomy.org/bibtex/2944ffdd8aea25d105653b6158794e752/jennymac},
description = {Glass: Extracting information from natural language... - Google Scholar},
interhash = {bce23020f39ff032c875d26e3ecdd5cd},
intrahash = {944ffdd8aea25d105653b6158794e752},
journal = {Far East Journal of Experimental and Theoretical Artificial Intelligence},
keywords = {CIRCSIM-Tutor intelligent language natural tutoring},
month = {August},
number = 2,
pages = {87-125},
timestamp = {2011-06-13T14:04:04.000+0200},
title = {Extracting Information from Natural Language Input to an Intelligent Tutoring System},
url = {http://www.pphmj.com},
volume = 1,
year = 2008
}