Using item-response theory to model rater effects provides an alternative solution for rater monitoring and diagnosis, compared to using standard performance metrics. In order to fit such models, the ratings data must be sufficiently connected in order to estimate rater effects. Due to popular rating designs used in large-scale testing scenarios,…

We investigated the relationship between the scores assigned by an Automated Essay Scoring (AES) system, the Intelligent Essay Assessor (IEA), and grades allocated by trained, professional human raters to English essay writing by instigating two procedures novel to written-language assessment: the logistic transformation of AES raw scores into…

Automated assessment using Natural Language Processing (NLP) has the potential to make English speaking assessments more reliable, authentic, and accessible. Yet without careful examination, NLP may exacerbate social prejudices based on gender or native language (L1). Current NLP-based assessments are prone to such biases, yet research and…

Purpose: This study builds a new system for automatically assessing learners' speech elicited from an oral discourse completion task (DCT), and evaluates the prediction capability of the system with a view to better understanding factors deemed influential in predicting speaking proficiency scores and the pedagogical implications of the system.…

A challenge of large-scale oral communication assessments is to feasibly assess a broad construct that includes interactional competence. One possible approach in addressing this challenge is to use a spoken dialog system (SDS), with the computer acting as a peer to elicit a ratable speech sample. With this aim, an SDS was built and four trained…

Managing crowded classes in terms of classroom assessment is a difficult task due to the amount of time which needs to be devoted to providing feedback to student products. In this respect, the present study aimed to develop an automated essay scoring environment as a potential means to overcome this problem. Secondarily, the study aimed to test…

Automated essay scoring engines (AESEs) are becoming increasingly popular as an efficient method for performance assessments in writing, including many language assessments that are used worldwide. Before they can be used operationally, AESEs must be "trained" using machine-learning techniques that incorporate human ratings. However, the…

Assessing language skills in an integrative form has drawn the attention of assessment experts in recent years. While some research data exists on integrative listening/reading-to-write assessment, there is comparatively little research literature on listening-to-speak integrated assessment. Also, little attention has been devoted to the role of…

Recent technology advancements have increased the prospects for automated spoken language technology to provide feedback on speaking performance. In this study we examined user perceptions of using an automated feedback system for preparing for the TOEFL iBT® test. Test takers and language teachers evaluated three types of machine-generated…

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…

An assumption underlying speaking tests is that scores reflect the ability to produce online, non-rehearsed speech. Speech produced in testing situations may, however, be less spontaneous if extensive test preparation takes place, resulting in memorized or rehearsed responses. If raters detect these patterns, they may conceptualize speech as…

Two factors were investigated that are thought to contribute to consistency in rater scoring judgments: rater training and experience in scoring. Also considered were the relative effects of scoring rubrics and exemplars on rater performance. Experienced teachers of English (N = 20) scored recorded responses from the TOEFL iBT speaking test prior…

The "e-rater"® automated essay scoring system is used operationally in the scoring of "TOEFL iBT"® independent and integrated tasks. In this study we explored the psychometric added value of reporting four trait scores for each of these two tasks, beyond the total e-rater score.The four trait scores are word choice, grammatical…

There has been a growing interest in the use of integrated tasks in the field of second language testing to enhance the authenticity of language tests. However, the role of text integration in test takers' performance has not been widely investigated. The purpose of the current study is to examine the effects of text-based relational (i.e.,…

This report presents work on the development of a new corpus of non-native English writing. It will be useful for the task of native language identification, as well as grammatical error detection and correction, and automatic essay scoring. In this report, the corpus is described in detail.