This study compared the results from nine automated essay scoring engines on eight essay scoring prompts drawn from six states that annually administer high-stakes writing assessments. Student essays from each state were randomly divided into three sets: a training set (used for modeling the essay prompt responses and consisting of text and ratings from two human raters along with a final or re...

Automated essay scoring with latent semantic analysis (LSA) has recently been subject to increasing interest. Although previous authors have achieved grade ranges similar to those awarded by humans, it is still not clear which and how parameters improve or decrease the effectiveness of LSA. This paper presents an analysis of the effects of these parameters, such as text preprocessing, weighting...

Abstract Automated essay scoring (AES) is the task of automatically assigning scores to essays as an alternative grading by humans. Although traditional AES models typically rely on manually designed features, deep neural network (DNN)-based that obviate need for feature engineering have recently attracted increased attention. Various DNN-AES with different characteristics been proposed over pa...

This paper describes a deployed educational technology application: the Criterion Online Essay Evaluation Service, a web-based system that provides automated scoring and evaluation of student essays. Criterion has two complementary applications: E-rater, an automated essay scoring system and Critique Writing Analysis Tools , a suite of programs that detect errors in grammar, usage, and mechani...

Automated essay scoring tools are often criticized on the basis of construct validity. Specifically, it has been argued that computational scoring algorithms may be unaligned to higher-level indicators of quality writing, such as writers’ demonstrated knowledge and understanding of the essay topics. In this paper, we consider how and whether the scoring algorithms within an intelligent writing ...