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...

We have set out to create a system that gives essay feedback by identifying stronger and weaker parts of a given essay. In order to do this, we have created a two step model: the first step uses an LSTM to turn a chunk of an essay into an encoding vector. The second step uses a feed forward network to assign a score to an encoding. We believe that if the feed forward network is able to predict ...

In this paper we describe an application of weighted abductive theorem proving that is used to create a model of students’ qualitative reasoning for the Why2-Atlas tutoring system. The system encourages a student to write an essay in natural language so that the essay provides both an explanation as well as an answer to a qualitative mechanics problem. The student’s essay is first mapped into a...

The aim of this paper is to clearly demonstrate the importance of finding a good balance between genetic search and local search in the implementation of hybrid evolutionary multi-criterion optimization (EMO) algorithms. We first modify the local search part of an existing multi-objective genetic local search (MOGLS) algorithm. In the modified MOGLS algorithm, the computation time spent by loca...

Writing has been increasingly regarded by the testers of language tests as an important indicator to assess the language skill of testees. As such tests become more and more popular and the number of testees becomes larger, it is a huge task to score so many essays by raters. So far, many methods have been used to solve this problem and the traditional method is Latent Semantic Analysis (LSA). ...

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...

The e-rater system 1 , an automated essay scoring system, developed at Educational Testing Service (ETS), is currently being used to score essay responses on the Graduate Management Admissions Test (GMAT). The average agreement between human readers, and between independent human readers and e-rater is approximately 92%. There is much interest in the larger writing community in examining the sy...

Neural approaches to automated essay scoring have recently shown state-of-theart performance. The automated essay scoring task typically involves a broad notion of writing quality that encompasses content, grammar, organization, and conventions. This differs from the short answer content scoring task, which focuses on content accuracy. The inputs to neural essay scoring models – ngrams and embe...

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...