Automated Versus Human Essay Scoring: A Comparative Study
نویسندگان
چکیده
منابع مشابه
Automated Essay Scoring Versus Human Scoring: A Correlational Study
The purpose of the current study was to analyze the relationship between automated essay scoring (AES) and human scoring in order to determine the validity and usefulness of AES for large-scale placement tests. Specifically, a correlational research design was used to examine the correlations between AES performance and human raters’ performance. Spearman rank correlation coefficient tests were...
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The ability to communicate in natural language has long been considered a defining characteristic of human intelligence. Furthermore, we hold our ability to express ideas in writing as a pinnacle of this uniquely human language facility—it defies formulaic or algorithmic specification. So it comes as no surprise that attempts to devise computer programs that evaluate writing are often met with ...
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We present the first system developed for automated grading of high school essays written in Swedish. The system uses standard text quality indicators and is able to compare vocabulary and grammar to large reference corpora of blog posts and newspaper articles. The system is evaluated on a corpus of 1 702 essays, each graded independently by the student’s own teacher and also in a blind re-grad...
متن کاملA Study of Distributed Semantic Representations for Automated Essay Scoring
Automated essay scoring (AES) applies machine learning and NLP techniques to automatically rate essays written in an educational setting, by which the workload of human raters is considerably reduced. Current AES systems utilize common text features such as essay length, tf-idf weight, and the number of grammar errors to learn a scoring function. Despite the effectiveness brought by those commo...
متن کاملA Neural Approach to Automated Essay Scoring
Traditional automated essay scoring systems rely on carefully designed features to evaluate and score essays. The performance of such systems is tightly bound to the quality of the underlying features. However, it is laborious to manually design the most informative features for such a system. In this paper, we develop an approach based on recurrent neural networks to learn the relation between...
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ژورنال
عنوان ژورنال: Theory and Practice in Language Studies
سال: 2012
ISSN: 1799-2591
DOI: 10.4304/tpls.2.4.719-725