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

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

Research output: Chapter or Contribution to BookChapter

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.
Original languageAmerican English
Title of host publicationProceedings: 2014 13th International Conference on Machine Learning and Applications
EditorsXue-wen Chen, Guangzhi Qu, Plamen Angelov, Cesar Ferri, Jian-huang Lai, M.Arif Wani
Place of PublicationDetroit, Michigan
Pages553-556
Number of pages4
ISBN (Electronic)978-1-4799-7415-3
DOIs
StatePublished - Dec 3 2014
Event13th International Conference on Machine Learning and Applications, - Detroit, Michigan
Duration: Dec 3 2014 → …

Conference

Conference13th International Conference on Machine Learning and Applications,
Period12/3/14 → …

Keywords

  • Cohmetrix
  • arguments
  • intelligent tutoring systems
  • text classification

Disciplines

  • Computational Linguistics
  • Computer Sciences
  • Higher Education
  • Artificial Intelligence and Robotics

Cite this