Comparison ofe-rater® Automated Essay Scoring Model Calibration Methods Based on Distributional Targets

Autor:	David M. Williamson, Catherine Trapani, F. Jay Breyer, Mo Zhang
Rok vydání:	2012
Předmět:	Percentile Uniform distribution (continuous) Social Psychology Scale (ratio) Automated essay scoring computer.software_genre Midpoint Education Normal distribution Modeling and Simulation Calibration Data mining computer Mathematics
Zdroj:	International Journal of Testing. 12:345-364
ISSN:	1532-7574 1530-5058
Popis:	This article describes two separate, related studies that provide insight into the effectiveness of e-rater score calibration methods based on different distributional targets. In the first study, we developed and evaluated a new type of e-rater scoring model that was cost-effective and applicable under conditions of absent human rating and small candidate volume. This new model type, called the Scale Midpoint Model, outperformed an existing e-rater scoring model that is often adopted by certain e-rater system users without modification. In the second study, we examined the impact of three distributional score calibration approaches on existing models’ performance. These approaches included percentile calibrations on e-rater scores in accordance with a human rating distribution, normal distribution, and uniform distribution. Results indicated that these score calibration approaches did not have overall positive effects on the performance of existing e-rater scoring models.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::64a61690ceb9808be6a6b4b1b96594fd https://doi.org/10.1080/15305058.2011.645973 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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