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Yao, Lili; Haberman, Shelby J.; Zhang, Mo – ETS Research Report Series, 2019
Many assessments of writing proficiency that aid in making high-stakes decisions consist of several essay tasks evaluated by a combination of human holistic scores and computer-generated scores for essay features such as the rate of grammatical errors per word. Under typical conditions, a summary writing score is provided by a linear combination…
Descriptors: Prediction, True Scores, Computer Assisted Testing, Scoring
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Attali, Yigal – ETS Research Report Series, 2007
This study examined the construct validity of the "e-rater"® automated essay scoring engine as an alternative to human scoring in the context of TOEFL® essay writing. Analyses were based on a sample of students who repeated the TOEFL within a short time period. Two "e-rater" scores were investigated in this study, the first…
Descriptors: Construct Validity, Computer Assisted Testing, Scoring, English (Second Language)
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Haberman, Shelby J.; Qian, Jiahe – ETS Research Report Series, 2004
Statistical prediction problems often involve both a direct estimate of a true score and covariates of this true score. Given the criterion of mean squared error, this study determines the best linear predictor of the true score given the direct estimate and the covariates. Results yield an extension of Kelley's formula for estimation of the true…
Descriptors: True Scores, Computation, Predictor Variables, Correlation
Hicks, Marilyn M. – 1989
Methods of computerized adaptive testing using conventional scoring methods in order to develop a computerized placement test for the Test of English as a Foreign Language (TOEFL) were studied. As a consequence of simulation studies during the first phase of the study, the multilevel testing paradigm was adopted to produce three test levels…
Descriptors: Adaptive Testing, Adults, Algorithms, Computer Assisted Testing