Test score comparability in international large-scale assessments (LSA) is of utmost importance in measuring the effectiveness of education systems and understanding the impact of education on economic growth. To effectively compare test scores on an international scale, score linking is widely used to convert raw scores from different linguistic…

Different sources of assessment evidence are reviewed during International Baccalaureate (IB) grade awarding to convert marks into grades and ensure fair results for students. Qualitative and quantitative evidence are analysed to determine grade boundaries, with statistical evidence weighed against examiner judgement and teachers' feedback on…

Intelligent systems of essay grading constitute important tools for educational technologies. They can significantly replace the manual scoring efforts and provide instructional feedback as well. These systems typically include two main parts: a feature extractor and an automatic grading model. The latter is generally based on computational and…

Trend scoring constructed response items (i.e. rescoring Time A responses at Time B) gives rise to two-way data that follow a product multinomial distribution rather than the multinomial distribution that is usually assumed. Recent work has shown that the difference in sampling model can have profound negative effects on statistics usually used to…

There is a vast body of literature documenting the positive impacts that rater training and calibration sessions have on inter-rater reliability as research indicates several factors including frequency and timing play crucial roles towards ensuring inter-rater reliability. Additionally, increasing amounts research indicate possible links in…

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 introduce a short answer scoring engine made up of an ensemble of deep neural networks and a Latent Semantic Analysis-based model to score short constructed responses for a large suite of questions from a national assessment program. We evaluate the performance of the engine and show that the engine achieves above-human-level performance on a…

Purpose: The authors constructed an automatic essay scoring (AES) model in a discussion forum where the result was compared with scores given by human evaluators. This research proposes essay scoring, which is conducted through two parameters, semantic and keyword similarities, using a SentenceTransformers pre-trained model that can construct the…

This study aims to examine whether differences exist in the factors influencing the difficulty of scoring English summaries and determining scores based on the raters' attributes, and to collect candid opinions, considerations, and tentative suggestions for future improvements to the analytic rubric of summary writing for English learners. In this…

Machine learning algorithms that automatically score scientific explanations can be used to measure students' conceptual understanding, identify gaps in their reasoning, and provide them with timely and individualized feedback. This paper presents the results of a study that uses Hebrew NLP to automatically score student explanations in Biology…

Rubrics (e.g., Valid Assessment of Learning in Undergraduate Education (VALUE) rubrics) that measure specific skills exist, and researchers have demonstrated their benefits; however, most of them were designed for use with undergraduate students. Although some rubrics have been created to assess dissertations and oral defenses, few have been…

Background/Context: Pass/fail standardized exams frequently selectively rescore failing exams and retest failing examinees. This practice distorts the test score distribution and can confuse those who do analysis on these distributions. In 2011, the Wall Street Journal showed large discontinuities in the New York City Regent test score…

For some students, standardized tests serve as a conduit to disclose sensitive issues of harm or distress that may otherwise go unreported. By detecting this writing, known as "crisis papers," testing programs have a unique opportunity to assist in mitigating the risk of harm to these students. The use of machine learning to…

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,…

A diversity of approaches for critically appraising qualitative and quantitative evidence exist and emphasize different aspects. These approaches lack clear processes to facilitate rating the overall quality of the evidence for aggregated findings that combine qualitative and quantitative evidence. We draw on a meta-aggregation of implementation…