Automated Essay Scoring (AES) tools aim to improve the efficiency and consistency of essay scoring by using machine learning algorithms. In the existing research work on this topic, most researchers agree that human-automated score agreement remains the benchmark for assessing the accuracy of machine-generated scores. To measure the performance of…

The advent of artificial intelligence (AI), particularly large language models (LLMs) like ChatGPT and Gemini, has significantly impacted the educational landscape, offering unique opportunities for learning and assessment. In the realm of written assessment grading, traditionally viewed as a laborious and subjective process, this study sought to…

Through Many-Facet Rasch analysis, this study explores the rating differences between 1 computer automatic rater and 5 expert teacher raters on scoring 119 students in a computerized English listening-speaking test. Results indicate that both automatic and the teacher raters demonstrate good inter-rater reliability, though the automatic rater…

Computerized classification of student answers offers the possibility of instant feedback and improved learning. Open response (OR) questions provide greater insight into student thinking and understanding than more constrained multiple choice (MC) questions, but development of automated classifiers is more difficult, often requiring training a…

Similarity reports of plagiarism detectors should be approached with caution as they may not be sufficient to support allegations of plagiarism. This study developed a 50-item rubric to simplify and standardize evaluation of academic papers. In the spring semester of 2011-2012 academic year, 161 freshmen's papers at the English Language Teaching…

In this research, we investigated the suitability of implementing "e-rater"® automated essay scoring in a high-stakes large-scale English language testing program. We examined the effectiveness of generic scoring and 2 variants of prompt-based scoring approaches. Effectiveness was evaluated on a number of dimensions, including agreement…

This article considers the claim that machine scoring of writing test responses agrees with human readers as much as humans agree with other humans. These claims about the reliability of machine scoring of writing are usually based on specific and constrained writing tasks, and there is reason for asking whether machine scoring of writing requires…

We present a novel approach to the automated marking of student programming assignments. Our technique quantifies the structural similarity between unmarked student submissions and marked solutions, and is the basis by which we assign marks. This is accomplished through an efficient novel graph similarity measure ("AssignSim"). Our experiments…

The hurried pace of the modern classroom does not permit formative feedback on writing assignments at the frequency or quality recommended by the research literature. One solution for increasing individual feedback to students is to incorporate some form of computer-generated assessment. This study explores the use of automated assessment of…

Purpose: The purpose of this study was to determine whether children exposed to 2 languages would benefit from the phonotactic probability cues of a single language in the same way as monolingual peers and to determine whether crosslinguistic influence would be present in a fast-mapping task. Method: Two groups of typically developing children…

Students at the University of Edinburgh do almost all their work on computers, but at the end of the semester they are examined by handwritten essays. Intuitively it would be appealing to allow students the choice of handwriting or typing, but this raises a concern that perhaps this might not be "fair"--that the choice a student makes,…

This paper describes a study of the computer essay-scoring program BETSY. While the use of computers in rating written scripts has been criticised in some quarters for lacking transparency or lack of fit with how human raters rate written scripts, a number of essay rating programs are available commercially, many of which claim to offer comparable…

A renewed focus on foreign language (FL) learning and speech for communication has resulted in computer-assisted language learning (CALL) software developed with Automatic Speech Recognition (ASR). ASR features for FL pronunciation (Lafford, 2004) are functional components of CALL designs used for FL teaching and learning. The ASR features…

As class sizes increase, methods of assessments shift from costly traditional approaches (e.g. expert-graded writing assignments) to more economic and logistically feasible methods (e.g. multiple-choice testing, computer-automated scoring, or peer assessment). While each method of assessment has its merits, it is peer assessment in particular,…

National Assessment of Educational Progress writing sample essays from 1988 and 1990 (495 and 599 essays) were subjected to computerized grading and human ratings. Cross-validation suggests that computer scoring is superior to a two-judge panel, a finding encouraging for large programs of essay evaluation. (SLD)