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…

Background/purpose: Generative artificial intelligence (GenAI) is often promoted as a transformative tool for assessment, yet evidence of its validity compared to human raters remains limited. This study examined whether an AI-based rater could be used interchangeably with trained faculty in scoring complex coursework. Materials/methods:…

Studies on automatic scoring systems in writing assessments have also evaluated the relationship between human and machine scores for the reliability of automated essay scoring systems. This study investigated the magnitudes of indices for inter-rater agreement and discrepancy, especially regarding human and machine scoring, in writing assessment.…

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…

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…

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.…

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…

Adopting Linacre's guidelines for evaluating rating scale effectiveness, we examined whether and how a six-point rating scale functioned differently across raters, speech acts, and second language (L2) proficiency levels. We developed a 12-item Computerized Oral Discourse Completion Task (CODCT) for assessing the production of requests, refusals,…

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…

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.,…

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…

Research and development of a new type of scoring rubric for the integrated speaking tasks of "TOEFL iBT"® are described. These "analytic rating guides" could be helpful if tasks modeled after those in TOEFL iBT were used for formative assessment, a purpose which is different from TOEFL iBT's primary use for admission…

There is a growing body of research literature that considers how the mode of assessment, either computer-based or paper-based, might affect candidates' performances. Despite this, there is a fairly narrow literature that shifts the focus of attention to those making assessment judgements and which considers issues of assessor consistency when…

This paper describes a study comparing paper-based marking (PBM) and onscreen marking (OSM) in Hong Kong utilising English language essay scripts drawn from the live 2007 Hong Kong Certificate of Education Examination (HKCEE) Year 11 English Language Writing Paper. In the study, 30 raters from the 2007 HKCEE Writing Paper marked on paper 100…