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Direct linkKang, Okim; Rubin, Don; Kermad, Alyssa – Language Testing, 2019
As a result of the fact that judgments of non-native speech are closely tied to social biases, oral proficiency ratings are susceptible to error because of rater background and social attitudes. In the present study we seek first to estimate the variance attributable to rater background and attitudinal variables on novice raters' assessments of L2…
Descriptors: Evaluators, Second Language Learning, Language Tests, English (Second Language)
Download full textHeidari, Jamshid; Khodabandeh, Farzaneh; Soleimani, Hassan – JALT CALL Journal, 2018
The emergence of computer technology in English language teaching has paved the way for teachers' application of Mobile Assisted Language Learning (mall) and its advantages in teaching. This study aimed to compare the effectiveness of the face to face instruction with Telegram mobile instruction. Based on a toefl test, 60 English foreign language…
Descriptors: Comparative Analysis, Conventional Instruction, Teaching Methods, Computer Assisted Instruction
Attali, Yigal; Sinharay, Sandip – ETS Research Report Series, 2015
The "e-rater"® automated essay scoring system is used operationally in the scoring of "TOEFL iBT"® independent and integrated tasks. In this study we explored the psychometric added value of reporting four trait scores for each of these two tasks, beyond the total e-rater score.The four trait scores are word choice, grammatical…
Descriptors: Writing Tests, Scores, Language Tests, English (Second Language)
Wei, Jing; Llosa, Lorena – Language Assessment Quarterly, 2015
This article reports on an investigation of the role raters' language background plays in raters' assessment of test takers' speaking ability. Specifically, this article examines differences between American and Indian raters in their scores and scoring processes when rating Indian test takers' responses to the Test of English as a Foreign…
Descriptors: North Americans, Indians, Evaluators, English (Second Language)
Crossley, Scott A.; Kyle, Kristopher; Allen, Laura K.; Guo, Liang; McNamara, Danielle S. – Grantee Submission, 2014
This study investigates the potential for linguistic microfeatures related to length, complexity, cohesion, relevance, topic, and rhetorical style to predict L2 writing proficiency. Computational indices were calculated by two automated text analysis tools (Coh- Metrix and the Writing Assessment Tool) and used to predict human essay ratings in a…
Descriptors: Computational Linguistics, Essays, Scoring, Writing Evaluation
Xi, Xiaoming; Mollaun, Pam – Language Learning, 2011
We investigated the scoring of the Speaking section of the Test of English as a Foreign Language[TM] Internet-based (TOEFL iBT[R]) test by speakers of English and one or more Indian languages. We explored the extent to which raters from India, after being trained and certified, were able to score the TOEFL examinees with mixed first languages…
Descriptors: Speech Communication, Scoring, Foreign Countries, English (Second Language)
