Difference between revisions of "National Origin or National Location"

Revision as of 16:09, 18 May 2022

Bridgeman, Trapani, and Attali (2009) pdf

E-Rater gave significantly better scores for TOEFL essays (independent task) written by speakers of Chinese and Korean
E-Rater correlated poorly with human rater and give better scores for GRE essays (both issue and argument prompts) written by Chinese speakers

Bridgeman, Trapani, and Attali (2012) pdf

A later version of E-Rater system for automatic grading of GSE essay
Chinese students were given higher scores than when graded by human essay raters
Speakers of Arabic and Hindi were given lower scores

Ogan et al. (2015) pdf

Multi-national models predicting learning gains from student's help-seeking behavior
Models built on only U.S.or combined data sets performed extremely poorly for Costa Rica
Models performed better when built on and applied for the dataset, except for Philippines which was outperformed slightly by U.S. model

Li et al. (2021) pdf

Model predicting student achievement on the standardized examination PISA
Inaccuracy of the U.S.-trained model was greater for students from countries with lower scores of national development (e.g. Indonesia, Vietnam, Moldova)

Wang et al. (2018) pdf

Automated scoring model for evaluating English spoken responses
SpeechRater gave a significantly lower score than human raters for German
SpeechRater scored in favor of Chinese group, with H1-rater scores higher than mean

Bridgeman et al. (2009) pdf

Automated scoring models for evaluating English essays, or e-rater
E-rater gave significantly higher score for students from China and South Korea than 14 other countries when assessing independent writing task in Test of English as a Foreign Language (TOEFL)
E-rater gave slightly higher scores for GRE analytical writing, both argument and issue prompts, by students from China whose written responses tended to be the longest and below average on grammar, usage and mechanics

Bridgeman et al. (2012) pdf

A later version of automated scoring models for evaluating English essays, or e-rater
E-rater gave better scores for test-takers from Chinese speakers (Mainland China, Taiwan, Hong Kong) and Korean speakers when assessing TOEFL (independent prompt) and GRE essays
E-rater gave lower scores for Arabic, Hindi, and Spanish speakers when assessing their written responses to independent prompt in TOEFL

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-Bridgeman, Trapani, and Attali (2012) [https://www.researchgate.net/publication/233291671_Comparison_of_Human_and_Machine_Scoring_of_Essays_Differences_by_Gender_Ethnicity_and_Country pdf]
+Bridgeman et al. (2012) [https://www.tandfonline.com/doi/pdf/10.1080/08957347.2012.635502?needAccess=true pdf]
 * A later version of automated scoring models for evaluating English essays, or e-rater
-* E-rater gave slightly higher scores for test-takers from Chinese speakers (Mainland China, Taiwan, Hong Kong) and Korean speakers when assessing written responses to independent prompt in Test of English as a Foreign Language (TOEFL)
+* E-rater gave  better scores for test-takers from Chinese speakers (Mainland China, Taiwan, Hong Kong) and Korean speakers when assessing TOEFL (independent prompt)  and  GRE essays
-* E-rater gave slightly lower scores for Arabic and Hindi speakers when assessing their written responses to independent prompt in TOEFL
+* E-rater gave lower scores for Arabic, Hindi, and Spanish speakers when assessing their written responses to independent prompt in TOEFL
-* E-rater gave  significantly higher scores for test-takers from Mainland China than from Taiwan, Korea and Japan when assessing their GRE writings which tended to be below average on grammar, usage, and mechanics but longest response