This scope-review presents the milestones of how Hierarchical Rater Models (HRMs) become operable to used in automated essay scoring (AES) to improve instructional evaluation. Although essay evaluations--a useful instrument for evaluating higher-order cognitive abilities--have always depended on human raters, concerns regarding rater bias,…

Objectively scoring constructed-response items on educational assessments has long been a challenge due to the use of human raters. Even well-trained raters using a rubric can inaccurately assess essays. Unfolding models measure rater's scoring accuracy by capturing the discrepancy between criterion and operational ratings by placing essays on an…

Efficient constructed response (CR) scoring requires both accuracy and speed from human raters. This study was designed to determine if setting scoring rate expectations would encourage raters to score at a faster pace, and if so, if there would be differential effects on scoring accuracy for raters who score at different rates. Three rater groups…

Evaluating written texts is believed to be a time-consuming process that can lack consistency and objectivity. Automated essay scoring (AES) can provide solutions to some of the limitations of human scoring. This research aimed to evaluate the performance of one AES system, Grammarly, in comparison to human raters. Both approaches' performances…

While automated essay scoring (AES) can reliably grade essays at scale, automated writing evaluation (AWE) additionally provides formative feedback to guide essay revision. However, a neural AES typically does not provide useful feature representations for supporting AWE. This paper presents a method for linking AWE and neural AES, by extracting…

We evaluate the feasibility of developing predictive models of rater behavior, that is, "rater-specific" models for predicting the scores produced by a rater under operational conditions. In the present study, the dependent variable is the score assigned to essays by a rater, and the predictors are linguistic attributes of the essays…

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…

Rater training is essential in ensuring the quality of constructed response scoring. Most of the current knowledge about rater training comes from experimental contexts with an emphasis on short-term effects. Few sources are available for empirical evidence on whether and how raters become more accurate as they gain scoring experiences or what…

This study explored possible reasons why IELTS candidates usually score low in writing by investigating the effects of two different test designs and scoring criteria on Iranian IELTS candidates' obtained grades in IELTS and World Englishes (WEs) essay writing tests. To this end, first, a WEs essay writing test was preliminarily designed. Then, 17…

Standardisation is a procedure used by Awarding Organisations to maximise marking reliability, by teaching examiners to consistently judge scripts using a mark scheme. However, research shows that people are better at comparing two objects than judging each object individually. Consequently, Oxford, Cambridge and RSA (OCR, a UK awarding…

The difference in how humans read and how Automated Essay Scoring (AES) systems process written language leads to a situation where a portion of student responses will be comprehensible to human markers, but unable to be parsed by AES systems. This paper examines a number of pieces of student writing that were marked by trained human markers, but…

The present study leveraged advances in automated essay scoring (AES) technology to explore a proof of concept for a writing screener using the "Project Essay Grade" (PEG) program. First, the study investigated the extent to which an AES-scored multi-prompt writing screener accurately classified students as at risk of failing a Common…

To score an essay response, raters draw on previously trained skills and knowledge about the underlying rubric and score criterion. Cognitive processes such as remembering, forgetting, and skill decay likely influence rater performance. To investigate how forgetting influences scoring, we evaluated raters' scoring accuracy on TOEFL and GRE essays.…

This report investigates whether the time between scoring sessions has an influence on operational and nonoperational scoring accuracy. The study evaluates raters' scoring accuracy on constructed-response essay responses for the "GRE"® General Test. Binomial linear mixed-effect models are presented that evaluate how the effect of various…

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…