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ERIC Number: EJ1272190
Record Type: Journal
Publication Date: 2020
Pages: 9
Abstractor: As Provided
ISSN: ISSN-1916-4742
An AWE-Based Diagnosis of L2 English Learners' Written Errors
Lei, Jiun-Iung
English Language Teaching, v13 n10 p111-119 2020
While Automated Writing Evaluation (AWE) can perform an error diagnosis (Chen & Cheng, 2008), previous studies used to exclude it from the process of error analysis. This study aimed to examine the reactions of Grammarly Premium towards a group of night school students' English writings at a Taiwanese technical university. The participants of the research produced 175 essays. The researcher checked the data against the AWE program. 1042 errors were detected and classified into 40 types. The 40 types of errors were at three hierarchical levels: a word and phrase level, a sentence level, and a discourse level. This study suggested future studies to view AWE's functions in a new perspective and find it a space in the process of error diagnosis.
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Publication Type: Journal Articles; Reports - Research
Education Level: Adult Education; Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Taiwan
Grant or Contract Numbers: N/A