ERIC Number: EJ1232278
Record Type: Journal
Publication Date: 2019
Pages: 9
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-2231-3338
EISSN: N/A
Using Regression to Reduce L2 Teachers' Scoring Workload: Predicting Essay Quality from Several Rhetorical Moves
Uzun, Kutay
Journal on English Language Teaching, v9 n3 p27-35 Jul-Sep 2019
Scoring essays written in L2 is one of the most arduous and time-taking tasks for language teachers due to the heavy work involved in the process. In this respect, the present study aimed to build a regression model to predict essay quality using only one or two rhetorical moves in the setting of an English Language Teaching department in Turkey. The corpus of the study consisted of 265 essays written by 105 students of English Language Teaching. The essays were written through one semester in a 2nd year English Literature course in the form of literary analysis essays which aimed to identify how an author or poet dealt with a theme or character in a literary work. For data analysis, the Genre-Based Literary Analysis Essay Scoring Rubric was initially used to score all the essays within the corpus. After the normality tests, two regression models were built in order to predict essay scores using the thesis statement scores and a combination of thesis statement and opinion statement scores. The results showed that the chosen rhetorical moves could significantly predict essay scores. Using predictive models, teachers can distinguish poor, mediocre, and good essays without scoring of whole essays.
Descriptors: Scoring, Essays, Second Language Instruction, English (Second Language), Language Teachers, College Students, Rhetoric, Foreign Countries, Predictor Variables, Prediction, Scores
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Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Turkey
Grant or Contract Numbers: N/A