We present in this paper the architecture of MetaTutor, an intelligent
tutoring system that teaches students meta-cognitive
strategies while learning about complex science topics. A
more in-depth presentation of the micro-dialogue component
in MetaTutor is provided. This component handles the
meta-cognitive strategy of subgoal generation. This strategy
involves subgoal assessment and feedback generation.
We present a taxonomy-driven method for subgoal assessment
and feedback. The method yields very good to excellent
human-computer agreement scores for subgoal assessment
(average kappa=0.77).
Description
Proceedings of the Twenty-Third International Florida Artificial Intelligence Research Society Conference (FLAIRS 2010)
%0 Conference Proceedings
%1 Rus_Intelligent_tutoring
%A Rus, Vasile
%A Lintean, Mihai
%A Azevedo, Roger
%D 2010
%K MetaTutor intelligent subgoal tutoring
%T Computational Aspects of Intelligent Tutoring System MetaTutor
%X We present in this paper the architecture of MetaTutor, an intelligent
tutoring system that teaches students meta-cognitive
strategies while learning about complex science topics. A
more in-depth presentation of the micro-dialogue component
in MetaTutor is provided. This component handles the
meta-cognitive strategy of subgoal generation. This strategy
involves subgoal assessment and feedback generation.
We present a taxonomy-driven method for subgoal assessment
and feedback. The method yields very good to excellent
human-computer agreement scores for subgoal assessment
(average kappa=0.77).
@proceedings{Rus_Intelligent_tutoring,
abstract = {We present in this paper the architecture of MetaTutor, an intelligent
tutoring system that teaches students meta-cognitive
strategies while learning about complex science topics. A
more in-depth presentation of the micro-dialogue component
in MetaTutor is provided. This component handles the
meta-cognitive strategy of subgoal generation. This strategy
involves subgoal assessment and feedback generation.
We present a taxonomy-driven method for subgoal assessment
and feedback. The method yields very good to excellent
human-computer agreement scores for subgoal assessment
(average kappa=0.77).},
added-at = {2011-06-09T12:18:40.000+0200},
author = {Rus, Vasile and Lintean, Mihai and Azevedo, Roger},
biburl = {https://www.bibsonomy.org/bibtex/282caaddcc56e26358f2e891afa6fc02d/jennymac},
description = {Proceedings of the Twenty-Third International Florida Artificial Intelligence Research Society Conference (FLAIRS 2010)},
interhash = {a1f4735c937d1c8d154ad1e648db6032},
intrahash = {82caaddcc56e26358f2e891afa6fc02d},
keywords = {MetaTutor intelligent subgoal tutoring},
timestamp = {2011-06-09T12:18:40.000+0200},
title = {Computational Aspects of Intelligent Tutoring System MetaTutor},
year = 2010
}