Difference between revisions of "Automated Essay Scoring"
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Bridgeman et al. (2009) [https:// | 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 06:37, 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 11th grade essays written by Hispanic students and Asian-American students than White students
- 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
- E-Rater system performed comparably accurately for male and female students when assessing their 11th grade essays, TOEFL, and GRE writings
Bridgeman et al. (2012) pdf
- A later version of automated scoring models for evaluating English essays, or e-rater
- E-rater gave significantly lower score than human rater when assessing African-American students’ written responses to issue prompt in GRE
- 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
- E-Rater system correlated comparably well with human rater when assessing TOEFL and GRE essays written by male and female students
Ramineni & Williamson (2018) pdf
- Revised automated scoring engine for assessing GSE essay
- E-rater gave African American test-takers significantly lower scores than human raters when assessing their written responses to argument prompts
- The shorter essays written by African American test-takers were more likely to receive lower scores as showing weakness in content and organization
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