The majority of current research in Automated Essay Scoring (AES) focuses on prompt-specific scoring either the overall quality an essay or with regards to certain traits. In real-world applications obtaining labelled data for a target prompt is often expensive unfeasible, requiring AES system be able perform well when predicting scores essays from unseen prompts. As result, some recent has bee...

This study compares automated scoring increases and linguistic changes for student writers in two groups: a group that used an intelligent tutoring system embedded with an automated writing evaluation component (Writing Pal) and a group that used only the automated writing evaluation component. The primary goal is to examine automated scoring differences in both groups from pretest to posttest ...

This study describes an approach for modeling the discourse coherence of spontaneous spoken responses in the context of automated assessment of non-native speech. Although the measurement of discourse coherence is typically a key metric in human scoring rubrics for assessments of spontaneous spoken language, little prior research has been done to assess a speaker’s coherence in the context of a...

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...

In this study, we present a pronunciation scoring method for second language learners of English (hereafter, L2 learners). This study presents a method using both confidence scoring and classifiers. Classifiers have an advantage over confidence scoring for specialization in the specific phonemes where L2 learners make frequent errors. Classifiers (Landmark-based Support Vector Machines) were tr...

This study focuses on modeling discourse coherence in the context of automated assessment of spontaneous speech from non-native speakers. Discourse coherence has always been used as a key metric in human scoring rubrics for various assessments of spoken language. However, very little research has been done to assess a speaker's coherence in automated speech scoring systems. To address this, we ...