Jill C. Burstein - Princeton NJ Martin S. Chodorow - New York NY Bruce A. Kaplan - Lawrenceville NJ Karen Kukich - Annandale NJ Chi Lu - Princeton NJ Donald A. Rock - Lawrenceville NJ Susanne Wolff - New York NY
A method of grading an essay using an automated essay scoring system is provided. The method comprises the automated steps of (a) parsing the essay to produce parsed text, wherein the parsed text is a syntactic representation of the essay, (b) using the parsed text to create a vector of syntactic features derived from the essay, (c) using the parsed text to create a vector of rhetorical features derived from the essay, (d) creating a first score feature derived from the essay, (e) creating a second score feature derived from the essay, and (f) processing the vector of syntactic features, the vector of rhetorical features, the first score feature, and the second score feature to generate a score for the essay. The essay scoring system comprises a Syntactic Feature Analysis program which creates a vector of syntactic features of the electronic essay text, a Rhetorical Feature Analysis program which creates a vector of rhetorical features of the electronic essay text, an EssayContent program which creates a first Essay Score Feature, an ArgContent program which creates a second Essay Score Feature, and a scoring engine which generates a final score for the essay from the vector of syntactic features, the vector of rhetorical features, the first score feature, and the second score feature.
Jill Burstein - Princeton NJ, US Slava Andreyev - Pennington NJ, US Chi Lu - Princeton NJ, US
Assignee:
Educational Testing Service - Princeton NJ
International Classification:
G09B 3/02
US Classification:
434353, 704 1
Abstract:
To automatically evaluate an essay, the essay is applied to a plurality of trait models and a plurality of trait scores are determined based on the plurality of trait models. Each of these trait scores having been generated from a respective trait model. In addition, a score is determined based on the plurality of trait scores.
Jill Burstein - Princeton NJ, US Slava Andreyev - Pennington NJ, US Chi Lu - Princeton NJ, US
Assignee:
Educational Testing Service - Princeton NJ
International Classification:
G09B 11/00
US Classification:
434353, 434362
Abstract:
To automatically evaluate an essay, the essay is applied to a plurality of trait models and a plurality of trait scores are determined based on the plurality of trait models. Each of these trait scores having been generated from a respective trait model. In addition, a score is determined based on the plurality of trait scores.
Jill Burstein - Princeton NJ, US Vyacheslav Andreyev - Pennington NJ, US Chi Lu - Princeton NJ, US
Assignee:
Educational Testing Service - Princeton NJ
International Classification:
G09B 11/00 G09B 7/00
US Classification:
434353
Abstract:
Systems and methods for building a trait model for essay evaluation are provided. At least one evaluated essay is received. A plurality of features pertaining to one or more traits from the at least one evaluated essay are identified and extracted. The one or more traits comprise writing errors, discourse, or vocabulary usage. A plurality of vector files based upon the plurality of features are created. A trait model for essay evaluation based upon the plurality of vector files is built. The trait model is evaluated, where the evaluation includes mapping features of a new essay to the trait model by navigating a multi-branched decision tree. At each branch of the decision tree, a value associated with the features of the new essay is used to determine how to proceed through the trait model.
System And Method For Computer-Based Automatic Essay Scoring
Jill C. Burstein - Princeton NJ Martin S. Chodorow - New York NY Bruce A. Kaplan - Lawrenceville NJ Karen Kukich - Annandale NJ Chi Lu - Princeton NJ Donald A. Rock - Lawrenceville NJ Susanne Wolff - New York NY
Assignee:
Educational Testing Service - Princeton NJ
International Classification:
G09B 700
US Classification:
434353
Abstract:
A method of grading an essay using an automated essay scoring system is provided. The method comprises the automated steps of (a) parsing the essay to produce parsed text, wherein the parsed text is a syntactic representation of the essay, (b) using the parsed text to create a vector of syntactic features derived from the essay, (c) using the parsed text to create a vector of rhetorical features derived from the essay, (d) creating a first score feature derived from the essay, (e) creating a second score feature derived from the essay, and (f) processing the vector of syntactic features, the vector of rhetorical features, the first score feature, and the second score feature to generate a score for the essay. The essay scoring system comprises a Syntactic Feature Analysis program which creates a vector of syntactic features of the electronic essay text, a Rhetorical Feature Analysis program which creates a vector of rhetorical features of the electronic essay text, an EssayContent program which creates a first Essay Score Feature, an ArgContent program which creates a second Essay Score Feature, and a scoring engine which generates a final score for the essay from the vector of syntactic features, the vector of rhetorical features, the first score feature, and the second score feature.
Automatic Essay Scoring System Using Content-Based Techniques
Jill C. Burstein - Howell NJ Randy Mark Kaplan - West Chester PA Susanne Wolff - New York NY Chi Lu - Princeton NJ
Assignee:
Educational Testing Service - Princeton NJ
International Classification:
G06F 1730 G06K 900
US Classification:
704 1
Abstract:
A system for carrying out a content-based process for automatically scoring essays is disclosed. The system includes a computer; a data storage device; a parse tree file stored in the data storage device, the parse tree file being representative of an essay in a parse tree format; a morphology stripping program; a concept extraction program for creating, on the basis of a morphology-stripped parse tree file, a phrasal node file; and a rule matching scoring program for scoring the essay on the basis of the phrasal node file.
Chi Ling Lu (1991-1995), Steve Rhodes (1957-1961), Kamrul Alam (1999-2003), Julie Howse (1976-1980), Dennis Liew (1989-1993), Colin Darlington (1996-2000)