An Intelligent Tutoring System for Argument-Making in Higher Education: A Pilot Study

Ching-Hua Chuan; Daniel Dinsmore; Joseph Schmuller; Tyler Morris

doi:10.1109/ICMLA.2014.112

An Intelligent Tutoring System for Argument-Making in Higher Education: A Pilot Study

Ching-Hua Chuan, Daniel Dinsmore, Joseph Schmuller, Tyler Morris

University of North Florida

Producción científica: Chapter

Resumen

This paper presents a pilot study on an intelligent tutoring system for domain-independent argument making. Students' responses to an open-ended question were collected as the instances for supervised text classification based on the grade given by the instructor using structured outcome of the learning observation taxonomy. The responses were processed using Cohmetrix as well as n-gram models to generate attributes for the classification task. The best result of 81.74% in classification correct rate was obtained when all grade classes were used.

Idioma original	American English
Título de la publicación alojada	Proceedings: 2014 13th International Conference on Machine Learning and Applications
Editores	Xue-wen Chen, Guangzhi Qu, Plamen Angelov, Cesar Ferri, Jian-huang Lai, M.Arif Wani
Lugar de publicación	Detroit, Michigan
Páginas	553-556
Número de páginas	4
ISBN (versión digital)	978-1-4799-7415-3
DOI	https://doi.org/10.1109/ICMLA.2014.112
Estado	Published - dic 3 2014
Evento	13th International Conference on Machine Learning and Applications, - Detroit, Michigan Duración: dic 3 2014 → …

Conference

Conference	13th International Conference on Machine Learning and Applications,
Período	12/3/14 → …

Disciplines

Computational Linguistics
Computer Sciences
Higher Education
Artificial Intelligence and Robotics

Acceder al documento

10.1109/ICMLA.2014.112Licencia: Unspecified

Otros archivos y enlaces

Link to publication

Citar esto

An Intelligent Tutoring System for Argument-Making in Higher Education: A Pilot Study. / Chuan, Ching-Hua; Dinsmore, Daniel; Schmuller, Joseph et al.
Proceedings: 2014 13th International Conference on Machine Learning and Applications. ed. / Xue-wen Chen; Guangzhi Qu; Plamen Angelov; Cesar Ferri; Jian-huang Lai; M.Arif Wani. Detroit, Michigan, 2014. p. 553-556.

Producción científica: Chapter

Chuan, C-H, Dinsmore, D, Schmuller, J & Morris, T 2014, An Intelligent Tutoring System for Argument-Making in Higher Education: A Pilot Study. En X Chen, G Qu, P Angelov, C Ferri, J Lai & MA Wani (eds.), Proceedings: 2014 13th International Conference on Machine Learning and Applications. Detroit, Michigan, pp. 553-556, 13th International Conference on Machine Learning and Applications, 12/3/14. https://doi.org/10.1109/ICMLA.2014.112

Chuan, Ching-Hua ; Dinsmore, Daniel ; Schmuller, Joseph et al. / An Intelligent Tutoring System for Argument-Making in Higher Education : A Pilot Study. Proceedings: 2014 13th International Conference on Machine Learning and Applications. editor / Xue-wen Chen ; Guangzhi Qu ; Plamen Angelov ; Cesar Ferri ; Jian-huang Lai ; M.Arif Wani. Detroit, Michigan, 2014. pp. 553-556

@inbook{5c9927644e5144c4bb3d7113c9dca781,

title = "An Intelligent Tutoring System for Argument-Making in Higher Education: A Pilot Study",

abstract = " This paper presents a pilot study on an intelligent tutoring system for domain-independent argument making. Students' responses to an open-ended question were collected as the instances for supervised text classification based on the grade given by the instructor using structured outcome of the learning observation taxonomy. The responses were processed using Cohmetrix as well as n-gram models to generate attributes for the classification task. The best result of 81.74% in classification correct rate was obtained when all grade classes were used. ",

keywords = "Cohmetrix, arguments, intelligent tutoring systems, text classification",

author = "Ching-Hua Chuan and Daniel Dinsmore and Joseph Schmuller and Tyler Morris",

note = "C. -H. Chuan, D. Dinsmore, J. Schmuller and T. Morris, {"}An Intelligent Tutoring System for Argument-Making in Higher Education: A Pilot Study,{"} 2014 13th International Conference on Machine Learning and Applications, Detroit, MI, USA, 2014, pp. 553-556, doi: 10.1109/ICMLA.2014.112.; 13th International Conference on Machine Learning and Applications, ; Conference date: 03-12-2014",

year = "2014",

month = dec,

day = "3",

doi = "10.1109/ICMLA.2014.112",

language = "American English",

pages = "553--556",

editor = "Xue-wen Chen and Guangzhi Qu and Plamen Angelov and Cesar Ferri and Jian-huang Lai and M.Arif Wani",

booktitle = "Proceedings: 2014 13th International Conference on Machine Learning and Applications",

}

TY - CHAP

T1 - An Intelligent Tutoring System for Argument-Making in Higher Education

T2 - 13th International Conference on Machine Learning and Applications,

AU - Chuan, Ching-Hua

AU - Dinsmore, Daniel

AU - Schmuller, Joseph

AU - Morris, Tyler

N1 - C. -H. Chuan, D. Dinsmore, J. Schmuller and T. Morris, "An Intelligent Tutoring System for Argument-Making in Higher Education: A Pilot Study," 2014 13th International Conference on Machine Learning and Applications, Detroit, MI, USA, 2014, pp. 553-556, doi: 10.1109/ICMLA.2014.112.

PY - 2014/12/3

Y1 - 2014/12/3

N2 - This paper presents a pilot study on an intelligent tutoring system for domain-independent argument making. Students' responses to an open-ended question were collected as the instances for supervised text classification based on the grade given by the instructor using structured outcome of the learning observation taxonomy. The responses were processed using Cohmetrix as well as n-gram models to generate attributes for the classification task. The best result of 81.74% in classification correct rate was obtained when all grade classes were used.

AB - This paper presents a pilot study on an intelligent tutoring system for domain-independent argument making. Students' responses to an open-ended question were collected as the instances for supervised text classification based on the grade given by the instructor using structured outcome of the learning observation taxonomy. The responses were processed using Cohmetrix as well as n-gram models to generate attributes for the classification task. The best result of 81.74% in classification correct rate was obtained when all grade classes were used.

KW - Cohmetrix

KW - arguments

KW - intelligent tutoring systems

KW - text classification

UR - https://miami.pure.elsevier.com/en/publications/an-intelligent-tutoring-system-for-argument-making-in-higher-educ

U2 - 10.1109/ICMLA.2014.112

DO - 10.1109/ICMLA.2014.112

M3 - Chapter

SP - 553

EP - 556

BT - Proceedings: 2014 13th International Conference on Machine Learning and Applications

A2 - Chen, Xue-wen

A2 - Qu, Guangzhi

A2 - Angelov, Plamen

A2 - Ferri, Cesar

A2 - Lai, Jian-huang

A2 - Wani, M.Arif

CY - Detroit, Michigan

Y2 - 3 December 2014

ER -