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Statistical and Measurement Properties of Features Used in Essay Assessment

Author(s):
Haberman, Shelby J.
Publication Year:
2004
Report Number:
RR-04-21
Source:
ETS Research Report
Document Type:
Report
Page Count:
58
Subject/Key Words:
Essay Assessment, Holistic Scoring, Human Scoring, Electronic Essay Rater (E-rater), Rasch Model, Automated Scoring and Natural Language Processing

Abstract

The usefulness of joint and conditional maximum-likelihood is considered for the Rasch model under realistic testing conditions in which the number of examinees is very large and the number is items is relatively large. Conditions for consistency and asymptotic normality are explored, effects of model error are investigated, measures of prediction are estimated, and generalized residuals are developed.

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