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…

This study explores the potential to enhance the performance of convolutional neural networks (CNNs) for automated scoring of kinematic graph answers through data augmentation using Deep Convolutional Generative Adversarial Networks (DCGANs). By developing and fine-tuning a DCGAN model to generate high-quality graph images, we explored its…

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…

This paper reports on a multiyear program of international collaborative research delivered with the aim of conceptualising, validating and prototyping rubrics for evaluating and reporting university activities and outcomes relevant to the UN SDGs. The paper sets foundations by building on earlier analysis of research on university engagement with…

This chapter investigates the integration of generative AI (GenAI), specifically ChatGPT, into institutional and course-level assessment at Western New England University. It explores the potential of GenAI to streamline the assessment process, making it more efficient, equitable, and objective. Through the development of a proprietary GenAI tool,…

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,…

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…

Running Records are thought to be an excellent formative assessment tool because they generate results that educators can use to make their teaching more responsive. Despite the technical nature of scoring Running Records and the kinds of important decisions that are attached to their analysis, few studies have investigated assessor accuracy. We…

This paper introduces an application of cross-classified item response theory (IRT) modeling to an assessment utilizing the embedded standard setting (ESS) method (Lewis & Cook). The cross-classified IRT model is used to treat both item and person effects as random, where the item effects are regressed on the target performance levels (target…

Performance-based assessment is a common approach to assess the development and acquisition of practice competencies among health professions students. Judgments related to the quality of performance are typically operationalized as ratings against success criteria specified within a rubric. The extent to which the rubric is understood,…

English proficiency assessments have become a necessary metric for filtering and selecting prospective candidates for both academia and industry. With the rise in demand for such assessments, it has become increasingly necessary to have the automated human-interpretable results to prevent inconsistencies and ensure meaningful feedback to the…

Scoring essays is generally an exhausting and time-consuming task for teachers. Automated Essay Scoring (AES) facilitates the scoring process to be faster and more consistent. The most logical way to assess the performance of an automated scorer is by measuring the score agreement with the human raters. However, we provide empirical evidence that…