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,…

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,…

The development of explanations for scientific phenomena is crucial in science assessment. However, the scoring of students' written explanations is a challenging and resource-intensive process. Large language models (LLMs) have demonstrated the potential to address these challenges, particularly when the explanations are written in English, an…

Topic models are mathematical and statistical models used to analyze textual data. The objective of topic models is to gain information about the latent semantic space of a set of related textual data. The semantic space of a set of textual data contains the relationship between documents and words and how they are used. Topic models are becoming…

It is particularly important to identify and address issues of fairness and equity in educational contexts as academic performance can have large impacts on the types of opportunities that are made available to students. While it is always the hope that educators approach student assessment with these issues in mind, there are a number of factors…

The Research Excellence Framework is a high-stakes exercise used by the UK government to allocate billions of pounds of quality-related research (QR) funding and used by the media to rank universities and their departments in national league tables. The 2008, 2014 and 2021 assessments were zero-sum games in terms of league table position because…

We have dramatically advanced our ability to create rich, complex, and effective assessments across a range of uses through technology advancement. Artificial Intelligence (AI) enabled assessments represent one such area of advancement--one that has captured our collective interest and imagination. Scientists and practitioners within the domains…

The proliferation of large language models represents a paradigm shift in the landscape of automated essay scoring (AES) systems, fundamentally elevating their accuracy and efficacy. This study presents an extensive examination of large language models, with a particular emphasis on the transformative influence of transformer-based models, such as…

Scoring procedures for the constructed-response (CR) items in large-scale mixed-format educational assessments often involve checks for rater agreement or rater reliability. Although these analyses are important, researchers have documented rater effects that persist despite rater training and that are not always detected in rater agreement and…

Artificial Intelligence is at the heart of modern society with computers now capable of making process decisions in many spheres of human activity. In education, there has been intensive growth in systems that make formal and informal learning an anytime, anywhere activity for billions of people through online open educational resources and…

Educational tests are standardized so that all examinees are tested on the same material, under the same testing conditions, and with the same scoring protocols. This uniformity is designed to provide a level "playing field" for all examinees so that the test is "the same" for everyone. Thus, standardization is designed to…

PISA presents a new image for academic achievement, which has prompted Japanese education reforms over the past decade to innovate teaching and learning for 'PISA-style literacy'. Supported by theoretical foundations, particularly with regard to the concept of 'PISA literacy' and 'authentic assessment', these reforms have accomplished progress in…

In this digital ITEMS module, Dr. Sue Lottridge, Amy Burkhardt, and Dr. Michelle Boyer provide an overview of automated scoring. Automated scoring is the use of computer algorithms to score unconstrained open-ended test items by mimicking human scoring. The use of automated scoring is increasing in educational assessment programs because it allows…

Although much attention has been given to rater effects in rater-mediated assessment contexts, little research has examined the overall stability of leniency and severity effects over time. This study examined longitudinal scoring data collected during three consecutive administrations of a large-scale, multi-state summative assessment program.…

This research report provides a description of the processes of evaluating the "deployability" of automated scoring (AS) systems from the perspective of large-scale educational assessments in operational settings. It discusses a comprehensive psychometric evaluation that entails analyses that take into consideration the specific purpose…