Evaluating performance of grammatical error detection to maximize learning effect

Coling 2010 - 23rd International Conference on Computational Linguistics, Proceedings of the Conference

Volumn 2, Issue , 2010, Pages 894-900

  Nagata, Ryo ^a   Nakatani, Kazuhide ^a  

^a KONAN UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

DETECTION METHODS; F-MEASURE; GRAMMATICAL ERRORS; LEARNING EFFECTS;

COMPUTATIONAL LINGUISTICS;

ERROR DETECTION;

EID: 80053157617     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (19)

1. Bitchener, John, Stuart Young, and Denise Cameron. 2005. The effect of different types of corrective feedback on ESL student writing. Journal of Second Language Writing, 14(3):191-205. (Pubitemid 41824128)
2. Brockett, Chris, William B. Dolan, and Michael Gamon. 2006. Correcting ESL errors using phrasal SMT techniques. In Proc. of 21th International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, pages 249-256, Sydney, Australia, July.
3. Burstein, Jill, Karen Kukich, Susanne Wolff, Chi Lu, Martin Chodorow, Lisa Braden-Harder, and Mary D. Harris. 1998. Automated scoring using a hybrid feature identification technique. In Proc. of 36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics, pages 206-210.
4. Chodorow, Martin and Claudia Leacock. 2000. An unsupervised method for detecting grammatical errors. In Proc. of 1st Meeting of the North America Chapter of ACL, pages 140-147.
5. Chodorow, Martin and Claudia Leacock. 2002. Techniques for detecting syntactic errors in text. In IE-ICE Technical Report (TL2002-39), pages 37-41.
6. Chodorow, Martin, Joel R. Tetreault, and Na-Rae Han. 2007. Detection of grammatical errors involving prepositions. In Proc. of 4th ACL-SIGSEM Workshop on Prepositions, pages 25-30.
7. Ferris, Dana and Barrie Roberts. 2001. Error feedback in L2 writing classes: How explicit does it need to be? Journal of Second Language Writing, 10(3):161-184. (Pubitemid 33651015)
8. Han, Na-Rae, Martin Chodorow, and Claudia Leacock. 2004. Detecting errors in English article usage with a maximum entropy classifier trained on a large, diverse corpus. In Proc. of 4th International Conference on Language Resources and Evaluation, pages 1625-1628.
9. Han, Na-Rae, Martin Chodorow, and Claudia Leacock. 2006. Detecting errors in English article usage by non-native speakers. Natural Language Engineering, 12(2):115-129. (Pubitemid 43786487)
10. Hirota, Shigeaki. 1992. Mastery (in Japanese). Kiri-hara Shoten, Tokyo.
11. Iizuka, Shigeru and Satoshi Hagino. 1997. Prestige. Buneido, Tokyo.
12. Izumi, Emi, Kiyotaka Uchimoto, Toyomi Saiga, Thep-chai Supnithi, and Hitoshi Isahara. 2003. Automatic error detection in the Japanese learners'English spoken data. In Proc. of 41st Annual Meeting of ACL, pages 145-148.
13. Konishi, Tomoshichi and Kosei Minamide. 2007. Genious English-Japanese dictionary, 4th ed. Taishukan, Tokyo.
14. Nagata, Ryo, Fumito Masui, Atsuo Kawai, and Naoki Isu. 2004. Recognizing article errors based on the three head words. In Proc. of Cognition and Exploratory Learning in Digital Age, pages 184-191.
15. Nagata, Ryo, Takahiro Wakana, Fumito Masui, Atsuo Kawai, and Naoki Isu. 2005. Detecting article errors based on the mass count distinction. In Proc. of 2nd International Joint Conference on Natural Language Processing, pages 815-826.
16. Nagata, Ryo, Astuo Kawai, Koichiro Morihiro, and Naoki Isu. 2006. A feedback-augmented method for detecting errors in the writing of learners of English. In Proc. of 44th Annual Meeting of ACL, pages 241-248.
17. Okihara, Katsuaki. 1985. English writing (in Japanese). Taishukan, Tokyo.
18. Robb, Thomas, Steven Ross, and Ian Shortreed. 1986. Salience of feedback on error and its effect on EFL writing quality. TESOL QUARTERY, 20(1):83-93.
19. Yarowsky, David. 1995. Unsupervised word sense disambiguation rivaling supervised methods. In Proc. of 33rd Annual Meeting of ACL, pages 189-196.