DocumentCode
2690579
Title
Towards the use of semi-structured annotators for Automated Essay Grading
Author
Hon Wai Lam ; Dillon, Tharam ; Chang, Elizebeth
Author_Institution
Curtin Bus. Sch., Curtin Univ. of Technol., Perth, WA, Australia
fYear
2010
fDate
13-16 April 2010
Firstpage
228
Lastpage
233
Abstract
The amount of time teachers spend grading essays has increased over the past decade, prompting the development of systems that are able to lighten the workload. Many systems have thus far used linear regression or semi-supervised methods towards this objective. This paper discusses some of the main Automated Essay Grading systems, highlighting some of their strengths and weaknesses, in addition to providing a brief overview of Text Mining and meta-data annotation techniques that could be used to facilitate the process of grading essays through an automated system.
Keywords
data mining; text analysis; automated essay grading system; linear regression; meta-data annotation; semi-structured annotator; semi-supervised method; text mining; Artificial intelligence; Artificial neural networks; Humans; Semantics; Speech; Text mining; Training; Automated Essay Grading; Named Entity Recognition; Part-of-speech Tagging; Text Mining; meta-data annotation;
fLanguage
English
Publisher
ieee
Conference_Titel
Digital Ecosystems and Technologies (DEST), 2010 4th IEEE International Conference on
Conference_Location
Dubai
ISSN
2150-4938
Print_ISBN
978-1-4244-5551-5
Type
conf
DOI
10.1109/DEST.2010.5610643
Filename
5610643
Link To Document