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Benefits of Modularity in an Automated Essay Scoring System.

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Title: Benefits of Modularity in an Automated Essay Scoring System.
Language: English
Authors: Burstein, Jill, Marcu, Daniel
Peer Reviewed: N
Page Count: 7
Publication Date: 2000
Document Type: Reports - Descriptive
Descriptors: Essays, Scoring, Student Evaluation, Test Scoring Machines
Abstract: "E-rater" is an operational automated essay scoring application that combines several natural language processing (NLP) tools for the purpose of identifying linguistic features in essay responses to assess the quality of the text. The application currently identifies a variety of syntactic, discourse, and topical analysis features. Two clear visions have guided e-rater's development. First, new linguistically based features were to be added to strengthen connections between human scoring guide criteria and e-rater scores. Secondly, e-rater was to be adapted to provide explanatory feedback about writing quality automatically. This paper provides two examples of the flexibility of e-rater's modular architecture for continued application development toward these goals. The paper discusses how additional features from rhetorical parse trees were integrated into e-rater and how the salience of automatically generated discourse-based essay summaries was evaluated for use as instructional feedback through the reuse of e-rater's topical analysis module. (Contains 10 references.) (Author/SLD)
Entry Date: 2001
Accession Number: ED447168
Database: ERIC
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  Availability: 0
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  – Url: https://eric.ed.gov/contentdelivery/servlet/ERICServlet?accno=ED447168
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PubType: Report
PubTypeId: report
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IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Benefits of Modularity in an Automated Essay Scoring System.
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  Data: English
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  Data: <searchLink fieldCode="AR" term="%22Burstein%2C+Jill%22">Burstein, Jill</searchLink><br /><searchLink fieldCode="AR" term="%22Marcu%2C+Daniel%22">Marcu, Daniel</searchLink>
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  Data: N
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  Group: Src
  Data: 7
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2000
– Name: TypeDocument
  Label: Document Type
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  Data: Reports - Descriptive
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  Data: <searchLink fieldCode="DE" term="%22Essays%22">Essays</searchLink><br /><searchLink fieldCode="DE" term="%22Scoring%22">Scoring</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Evaluation%22">Student Evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Test+Scoring+Machines%22">Test Scoring Machines</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: "E-rater" is an operational automated essay scoring application that combines several natural language processing (NLP) tools for the purpose of identifying linguistic features in essay responses to assess the quality of the text. The application currently identifies a variety of syntactic, discourse, and topical analysis features. Two clear visions have guided e-rater's development. First, new linguistically based features were to be added to strengthen connections between human scoring guide criteria and e-rater scores. Secondly, e-rater was to be adapted to provide explanatory feedback about writing quality automatically. This paper provides two examples of the flexibility of e-rater's modular architecture for continued application development toward these goals. The paper discusses how additional features from rhetorical parse trees were integrated into e-rater and how the salience of automatically generated discourse-based essay summaries was evaluated for use as instructional feedback through the reuse of e-rater's topical analysis module. (Contains 10 references.) (Author/SLD)
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  Label: Entry Date
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  Data: 2001
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  Data: ED447168
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RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 7
    Subjects:
      – SubjectFull: Essays
        Type: general
      – SubjectFull: Scoring
        Type: general
      – SubjectFull: Student Evaluation
        Type: general
      – SubjectFull: Test Scoring Machines
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      – TitleFull: Benefits of Modularity in an Automated Essay Scoring System.
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            NameFull: Burstein, Jill
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            NameFull: Marcu, Daniel
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              M: 01
              Type: published
              Y: 2000
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