Multi-level Rasch Model Analysis of Computer-assisted Automated Scoring of English Listening and Speaking Tests
Junyan Liu, Bo Zhang · 2020 International Conference on Computer Engineering and Application (ICCEA) · 2020
The present study uses FACETS, a many-facet Rasch model measurement computer program, to explore the differences in rater severity and consistency among computer automatic scoring and 15 expert raters' rating on 215 examinees' speaking records derived from a mock examination of the Computer-based English Listening-Speaking Test (Guangdong). It finds that the rater severity differences among computer automatic scoring and expert raters' rating do not exert decisive influences on examinees' score distribution. The low bias rate of computer automatic scoring indicates that computer automatic scoring is better than human raters in terms of inner-consistency.