A human-computer collaboration approach to improve accuracy of an automated English scoring system

Authors:
Jee Eun Kim;Kong Joo Lee
Affiliations:
Hankuk University of Foreign Studies, Seoul, Korea;Chungnam National University, Daejeon, Korea
Venue:
IUNLPBEA '10 Proceedings of the NAACL HLT 2010 Fifth Workshop on Innovative Use of NLP for Building Educational Applications
Year:
2010

Citing 1
Cited 1

A corpus-based approach to automatic compound extraction

ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics

Building an automated English sentence evaluation system for students learning English as a second language

Computer Speech and Language

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper explores an issue of redundant errors reported while automatically scoring English learners' sentences. We use a human-computer collaboration approach to eliminate redundant errors. The first step is to automatically select candidate redundant errors using PMI and RFC. Since those errors are detected with different IDs although they represent the same error, the candidacy cannot be confirmed automatically. The errors are then handed over to human experts to determine the candidacy. The final candidates are provided to the system and trained with a decision tree. With those redundant errors eliminated, the system accuracy has been improved.