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 ...

This study examined the construct validity of the e-rater automated essay scoring engine as an alternative to human scoring in the context of TOEFL essay writing. Analyses were based on a sample of students who repeated the TOEFL within a short time period. Two e-rater scores were investigated in this study, the first based on optimally predicting the human essay score and the second based on e...

End-to-end argument mining has enabled the development of new automated essay scoring (AES) systems that use argumentative features (e.g., number of claims, number of support relations) in addition to traditional legacy features (e.g., grammar, discourse structure) when scoring persuasive essays. While prior research has proposed different argumentative features as well as empirically demonstra...

Automated essay scoring (AES) is gaining increasing attention in the education sector as it significantly reduces burden of manual and allows ad hoc feedback for learners. Natural language processing based on machine learning has been shown to be particularly suitable text classification AES. While many machine-learning approaches AES still rely a bag words (BOW) approach, we consider transform...

Grammatical error detection and automated essay scoring are two tasks in the area of automated assessment. Traditionally these tasks have been treated independently with different machine learning models and features used for each task. In this paper, we develop a multi-task neural network model that jointly optimises for both tasks, and in particular we show that neural automated essay scoring...

Modern automated essay scoring systems rely on identifying linguistically-relevant features to estimate essay quality. This paper attempts to bridge work in psycholinguistics and natural language processing by proposing sentence processing complexity as a feature for automated essay scoring, in the context of English as a Foreign Language (EFL). To quantify processing complexity we used a psych...

Automated Essay Scoring 2 Introduction This chapter documents the advent and rise of automated essay scoring (AES) as a means of both assessment and instruction. The first section discusses what AES is, how it works, and who the major purveyors of the technology are. The second section describes outgrowths of the technology as it applies to ongoing projects in measurement and education. In 1973...

Latent semantic analysis (LSA) is an automated, statistical technique for comparing the semantic similarity of words or documents. In this paper, I examine the application of LSA to automated essay scoring. I compare LSA methods to earlier statistical methods for assessing essay quality, and critically review contemporary essay-scoring systems built on LSA, including the Intelligent Essay Asses...