The Most Preferred and Effective Reviewer of L2 Writing among Automated Grading System, Peer Reviewer and Teacher

Abstract

Who is the most preferred and deemed the most helpful reviewer in improving student writing? This study exercised
a blended teaching method which consists of three currently prevailing reviewers: the automated grading system
(AGS, a web-based method), the peer review (a process-oriented approach), and the teacher grading technique (the
product-oriented approach) in a Writing (IV) class involving 22 technological sophomore students of Modern
Languages Department. The questionnaire results indicated the participants preferred the teacher as the reviewer to
their peers followed by the automated grading system and considered the teacher the most effective in helping their
writing. Three L2 teachers including one native speaker of English reviewed an essay which was the only and the
most inconsistent case between a human rater and a machine rater in the study (2.3 vs. 3.6). This case surfaced an
essential problem that the automated grading system couldn’t detect and correct expressions transferred from L1.
Data also revealed that teachers without training, their grammatical error identification rates are respectively 82.9%,
31.4% and 74.3%. After training, student reviewers could detect and correct from 70.2 to 79.3 percent of grammar
errors on average.