Application of an Automated Essay Scoring engine to English writing assessment using Many-Facet Rasch Measurement

Kinnie Kin Yee CHAN, Trevor BOND, Zi YAN

Research output: Contribution to journalArticlespeer-review

8 Citations (Scopus)

Abstract

We investigated the relationship between the scores assigned by an Automated Essay Scoring (AES) system, the Intelligent Essay Assessor (IEA), and grades allocated by trained, professional human raters to English essay writing by instigating two procedures novel to written-language assessment: the logistic transformation of AES raw scores into hierarchically ordered grades, and the co-calibration of all essay scoring data in a single Rasch measurement framework. A total of 3453 essays were written by 589 US students (in Grades 4, 6, 8, 10, and 12), in response to 18 National Assessment of Educational Progress (NAEP) writing prompts at three grade levels (4, 8, & 12). We randomly assigned one of two versions of the assessment, A or B, to each student. Each version comprised a narrative (N), an informative (I), and a persuasive (P) prompt. Nineteen experienced assessors graded the essays holistically using NAEP scoring guidelines, using a rotating plan in which each essay was rated by four raters. Each essay was additionally scored using the IEA. We estimated the effects of rater, prompt, student, and rubric by using a Many-Facet Rasch Measurement (MFRM) model. Last, within a single Rasch measurement scale, we co-calibrated the students’ grades from human raters and their grades from the IEA to compare them. The AES machine maintained equivalence with human scored ratings and were more consistent than those from human raters. Copyright © 2022 The Author(s).

Original languageEnglish
Pages (from-to)61-85
JournalLanguage Testing
Volume40
Issue number1
Early online dateFeb 2022
DOIs
Publication statusPublished - Jan 2023

Citation

Chan, K. K. Y., Bond, T., & Yan, Z. (2023). Application of an Automated Essay Scoring engine to English writing assessment using Many-Facet Rasch Measurement. Language Testing, 40(1), 61-85. doi: 10.1177/02655322221076025

Keywords

  • Alt. title: 多面Rasch測量(MFRM)模型應用於自動文章評分(AES)系統作英文作文評估
  • Automated Essay Scoring (AES) system
  • English essay assessment
  • FACETS
  • Human raters
  • Intelligent Essay Assessor (IEA)
  • Many-Facet Rasch Measurement (MFRM)

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