This study explores the effectiveness of using ChatGPT, an Artificial Intelligence (AI) language model, as an Automated Essay Scoring (AES) tool for grading English as a Foreign Language (EFL) learners' essays. The corpus consists of 50 essays representing various types including analysis, compare and contrast, descriptive, narrative, and opinion…

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…

The rating of proficiency tests that use the Inter-agency Roundtable (ILR) and American Council on the Teaching of Foreign Languages (ACTFL) guidelines claims that each major level is based on hierarchal linguistic functions that require mastery of multidimensional traits in such a way that each level subsumes the levels beneath it. These…

Severity and centrality are two main kinds of rater effects posing threats to the validity and fairness of performance assessments. Adopting Jin and Wang's (2018) extended facets modeling approach, we separately estimated the magnitude of rater severity and centrality effects in the web-based TestDaF (Test of German as a Foreign Language) writing…

Recent advances in machine learning have made automated scoring of learner speech widespread, and yet validation research that provides support for applying automated scoring technology to assessment is still in its infancy. Both the educational measurement and language assessment communities have called for greater transparency in describing…

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…

In this research report, we describe the design and empirical findings for a large-scale study of essay writing ability with approximately 2,500 high school students in Germany and Switzerland on the basis of 2 tasks with 2 associated prompts, each from a standardized writing assessment whose scoring involved both human and automated components.…

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…

Based on the articles written by mainland Chinese scholars published in the most influential Chinese and international journals, the present article analyzed the language testing research, compared the tendencies of seven categories between 2000-2009 and 2010-2019, and put forward future research directions by referring to international hot…

As a result of the fact that judgments of non-native speech are closely tied to social biases, oral proficiency ratings are susceptible to error because of rater background and social attitudes. In the present study we seek first to estimate the variance attributable to rater background and attitudinal variables on novice raters' assessments of L2…

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…