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Automated Scoring for the TOEFL Junior Comprehensive Writing and Speaking Test TOEFL iBT TOEFL

Author(s):
Evanini, Keelan; Heilman, Michael; Wang, Xinhao; Blanchard, Daniel
Publication Year:
2015
Report Number:
RR-15-09
Source:
ETS Research Report
Document Type:
Report
Page Count:
13
Subject/Key Words:
Electronic Essay Rater (E-rater), SpeechRater, TOEFL Junior, Automated Scoring, TOEFL iBT

Abstract

A generic scoring model from the e-rater automated essay scoring engine was used to score the email, opinion, and listen-write items in the Writing section, and the form-level results based on the five responses in the Writing section from each test taker showed a human–machine correlation of r=.83 (compared to a human–human correlation of r=.90). For scoring the Speaking section, new automated speech recognition models were first trained, and then item-specific scoring models were built for the read-aloud picture narration, and listen-speak items using preexisting features from the SpeechRater automated speech scoring engine (with the addition of a new content feature for the listen-speak items). The form-level results based on the five items in the Speaking section from each test taker showed a human–machine correlation of r=.81 (compared to a human–human correlation of r=.89).

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