essay scoring systems have been made available (PEG;Page 1966; e-rater®Burstein et al., 1998; Intelligent Essay AssessorTm;Foltz, Kintsch, and Landauer 1998; and, Intellimetric TM ; Elliot, 2003). In addition, based on the demands of users of the automated scoring technology, tools have been developed that perform more detailed evaluations of student writing. One such application is Critique Wr...

Automated Essay Scoring (AES) refers to the Artificial Intelligence (AI) application with “intelligence” in assessing and scoring essays. There are several well-known commercial AES adopted by western countries, as well many research works conducted investigating automated essay scoring. However, most of products not related Malaysian English test context. The tend score essays based on rubrics...

While recent years have seen a surge of interest in automated essay grading, including work on grading essays with respect to particular dimensions such as prompt adherence, coherence, and technical quality, there has been relatively little work on grading the essay dimension of argument strength, which is arguably the most important aspect of argumentative essays. We introduce a new corpus of ...

Standardized tests are hampered by the manual effort required to score student-written essays. In this paper, we show how linear regression can be used to automatically grade essays on standardized tests. We combine simple, shallow features of the essays, such as character length and word length, with part-of-speech patterns. Our combined model gives significant reduction in prediction error. W...

Automated methods for essay scoring have made great progress in recent years, achieving accuracies very close to human annotators. However, a known weakness of such automated scorers is not taking into account the semantic relevance of the submitted text. While there is existing work on detecting answer relevance given a textual prompt, very little previous research has been done to incorporate...

In automated essay scoring (AES), essays are automatically graded without human raters. Many AES models based on various manually designed features or architectures of deep neural networks have been proposed over the past few decades. Each model has unique advantages and characteristics. Therefore, rather than using a single model, appropriate integration predictions from is expected to achieve...