Difference between revisions of "National Origin or National Location"
Jump to navigation
Jump to search
(Clarity edit Ogan paper) |
|||
| Line 1: | Line 1: | ||
Bridgeman | Bridgeman et al. (2009) [https://www.researchgate.net/publication/242203403_Considering_Fairness_and_Validity_in_Evaluating_Automated_Scoring page] | ||
* Automated scoring models for evaluating English essays, or e-rater | * Automated scoring models for evaluating English essays, or e-rater | ||
Revision as of 07:37, 19 May 2022
Bridgeman et al. (2009) page
- Automated scoring models for evaluating English essays, or e-rater
- 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 same country, except for Philippines where model built on that country which was outperformed slightly by model built on U.S. data
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