Draft VersionHow to Excel AWA, bringing the research simplified to the students of GMAT, GRE & TOEFL : Draft VersionHow to Excel AWA, bringing the research simplified to the students of GMAT, GRE & TOEFL By
Satyadhar Joshi
Contents of Plan : Contents of Plan What is E rater
How to optimize you score
Research on the structure of e rater
Basic errors of grammar derived from GMAT
Minimizing errors using critical reading of your own essay
Conclusion
Introduction to E-rater (GRE-GMAT) : Introduction to E-rater (GRE-GMAT) It’s a software developed by ETS
It is used to rate Essays
Very sophisticated techniques used
Evaluating Multiple Aspects of Coherence in Student Essays : Evaluating Multiple Aspects of Coherence in Student Essays http://www.aclweb.org/anthology-new/N/N04/N04-1024.pdf
Exploring the Feedback and Revision Features of CriterionYigal Attali ETS, Princeton, NJPaper presented at the National Council on Measurement in Education : Exploring the Feedback and Revision Features of CriterionYigal Attali ETS, Princeton, NJPaper presented at the National Council on Measurement in Education Summary
Relation of length to grade
Critique, is comprised of a suite of programs that evaluates and provides feedback for errors in grammar, usage, and mechanics, identifies the essay’s discourse structure, and recognizes undesirable stylistic features
The writing analysis tools identify five main types of grammar, usage, and mechanics errors – agreement errors, verb formation errors, wrong word use, missing punctuation, and typographical errors. http://www.ets.org/Media/Research/pdf/erater_NCME_2004_Attali_B.pdf
Types of error : Types of error http://www.ets.org/Media/Research/pdf/erater_NCME_2004_Attali_B.pdf
Grammar Errors : Grammar Errors http://www.ets.org/Media/Research/pdf/erater_NCME_2004_Attali_B.pdf
Three main errors in Grammar : Three main errors in Grammar Be very careful about fragmented sentences.
Possessive errors of vs. ’s
Subject Very Agreement
Garbled sentences
Usage Errors in Essay : Usage Errors in Essay
Style Errors : Style Errors
Devastating errors : Devastating errors Below are the ranking of most costly errors which can take your score down:
Garbled sentences
Repetition of words
Missing Apostrophe
Fused Words
Capital Nouns
Inappropriate use of words or phases
Garbled Words : Garbled Words I cdnuolt blveiee taht I cluod aulaclty unesdnatnrd waht I was rdgnieg>The phaonmneal pweor of the hmuan mnid aoccdrnig to a rscheearch at > Cmabrigde Uinervtisy, it deosn't mattaer in whaht oredr the ltteers in a wrod are, the olny iprmoatnt tihng is taht the frist and lsat ltteer be in the rghit pclae. The rset can be a taotl mses and you can sitll raed it wouthit a porbelm.
Framing of Paragraph : Framing of Paragraph First and last lines are important
Conveying words are important use all of them
Idioms are important
Paragraphs should have sentences of good length
Writing strategy must includes an introductory paragraph, at least a three-paragraph body with each paragraph in the body consisting of a pair of main point and supporting idea elements, and a concluding paragraph.
Missing elements could include supporting ideas for up to the three expected main points or a missing introduction, conclusion, or main point. On the other hand, identification of main points beyond the minimum three would not contribute to the score.
Slide 14 :
Using pre-knowledge : Using pre-knowledge Examples are important
One area of each examples that the E-rater understand
Idioms : Idioms Lexicon complexity is an important parameter, use as many good words as possible
Punctuations : Punctuations One of the most important area of Essays
Publication Referred : Publication Referred Tetreault, J. & Chodorow, M. (2008). The ups and downs of prepositional error detection in ESL writing (PDF). In Proceedings of the 22nd International Conference on Computational Linguistics (pp. 865-872). Manchester, UK: COLING 2008 Organizing Committee.
Tetreault, J., & Chodorow, M. (2008, August). Native judgments of non-native usage: Experiments in preposition error detection (PDF). In COLING 2008: Proceedings of the workshop on Human Judgements in Computational Linguistics (pp. 24-32). Manchester, UK: COLING 2008 Organizing Committee.
Chodorow, M., Tetreault, J., & Han, N-R. (2007). Detection of grammatical errors involving prepositions (PDF). In Proceedings of the Fourth ACL-SIGSEM Workshop on Prepositions (pp. 25-30). Prague, Czech Republic: Association for Computational Linguistics.
Higgins, D., & Burstein, J. (2006). Sentence similarity measures for essay coherence (PDF). In Proceedings of the seventh international workshop on computational semantics (IWCS-7), Tilburg, The Netherlands.
Burstein, J., & Higgins, D. (2005). Advanced capabilities for evaluating student writing: Detecting off-topic essays without topic-specific training (PDF). In Proceedings of the international conference on artificial intelligence in Education, Amsterdam, The Netherlands.
Attali, Y. (2004, April). Exploring the feedback and revision features of Criterion (PDF). Paper presented at the annual meeting of the National Council on Measurement in Education, San Diego, CA.
Publication Referred continued : Publication Referred continued Han, N-R., Chodorow, M., & Leacock, C. (2004). Detecting errors in English article usage with a maximum entropy classifier trained on a large, diverse corpus (PDF). In Proceedings of the 4th International Conference on Language Resources and Evaluation, Lisbon, Portugal: European Language Resources Association.
Higgins, D., Burstein, J., Marcu, D., & Gentile, C. (2004). Evaluating multiple aspects of coherence in student essays (PDF). In S. Dumais, D. Marcu, & S. Roukos (Eds.), HLT-NAACL 2004: Main Proceedings (pp. 185-192). Boston, MA: Association for Computational Linguistics.
Burstein, J., Chodorow, M., & Leacock, C. (2003, August). Criterion: Online essay evaluation: An application for automated evaluation of student essays (PDF). Proceedings of the fifteenth annual conference on innovative applications of artificial intelligence, Acapulco, Mexico. (This paper received an AAAI Deployed Application Award.)
Burstein, J., & Wolska, M. (2003, April). Toward evaluation of writing style: Finding overly repetitive word use in student essays (PDF). In Proceedings of the 10th conference of the European chapter of the Association for Computational Linguistics, Budapest, Hungary.
Burstein, J., Marcu, D., Andreyev, S., & Chodorow, M. (2001, July). Towards automatic classification of discourse elements in essays (PDF). In Proceedings of the 39th Annual Meeting of the Association for Computational Linguistics (pp. 98-105). Toulouse, France: Association for Computational Linguistics.
Leacock, C., & Chodorow, M. (2001). Automatic assessment of vocabulary usage without negative evidence (TOEFL® Research Rep. No. 67, ETS RR-01-21). Princeton, NJ: ETS.
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