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 language | American English |
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Title of host publication | Proceedings: 2014 13th International Conference on Machine Learning and Applications |
Editors | Xue-wen Chen, Guangzhi Qu, Plamen Angelov, Cesar Ferri, Jian-huang Lai, M.Arif Wani |
Place of Publication | Detroit, Michigan |
Pages | 553-556 |
Number of pages | 4 |
ISBN (Electronic) | 978-1-4799-7415-3 |
DOIs | |
State | Published - Dec 3 2014 |
Event | 13th International Conference on Machine Learning and Applications, - Detroit, Michigan Duration: Dec 3 2014 → … |
Conference
Conference | 13th International Conference on Machine Learning and Applications, |
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Period | 12/3/14 → … |
Keywords
- Cohmetrix
- arguments
- intelligent tutoring systems
- text classification
Disciplines
- Computational Linguistics
- Computer Sciences
- Higher Education
- Artificial Intelligence and Robotics