Year: 2017
Type: conference-paper
Abstract: Automated Essay Scoring (AES) has been quite popular and is being widely used.However, lack of appropriate methodology for rating nonnative English speakers' essays has meant a lopsided advancement in this field.In this paper, we report initial results of our experiments with nonnative AES that learns from manual evaluation of nonnative essays.For this purpose, we conducted an exercise in which essays written by nonnative English speakers in test environment were rated both manually and by the automated system designed for the experiment.In the process, we experimented with a few features to learn about nonnative phraseology and its impact on the manual evaluation of the essays.The proposed methodology of automated essay evaluation has yielded a correlation coefficient of 0.750 with the manual evaluation.
Authors: Independent Scholar, New Delhi, India, Amber Nigam
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: bronze
OpenAlex ID: W2625795985