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…

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…

This study uses a computerized formative assessment system that provides automated scoring and feedback to help students write scientific arguments in a climate change curriculum. We compared the effect of contextualized versus generic automated feedback on students' explanations of scientific claims and attributions of uncertainty to those…

In automated essay scoring (AES), essays are automatically graded without human raters. Many AES models based on various manually designed features or various architectures of deep neural networks (DNNs) have been proposed over the past few decades. Each AES model has unique advantages and characteristics. Therefore, rather than using a single-AES…

Automated Essay Scoring (AES) technologies provide innovative solutions to score the written essays with a much shorter time span and at a fraction of the current cost. Traditionally, AES emphasized the importance of capturing the "coherence" of writing because abundant evidence indicated the connection between coherence and the overall…

The effectiveness of feedback in enhancing learning outcomes is well documented within Educational Data Mining (EDM). Various prior research have explored methodologies to enhance the effectiveness of feedback to students in various ways. Recent developments in Large Language Models (LLMs) have extended their utility in enhancing automated…

Purpose: The evaluation of spelling performance in aphasia reveals deficits in written language and can facilitate the design of targeted writing treatments. Nevertheless, manual scoring of spelling performance is time-consuming, laborious, and error prone. We propose a novel method based on the use of distance metrics to automatically score…

Creativity is an imperative skill for today's learners, one that has important contributions to issues of inclusion and equity in education. Therefore, assessing creativity is of major importance in educational contexts. However, scoring creativity based on traditional tools suffers from subjectivity and is heavily time- and labour-consuming. This…

Argumentation is fundamental to science education, both as a prominent feature of scientific reasoning and as an effective mode of learning--a perspective reflected in contemporary frameworks and standards. The successful implementation of argumentation in school science, however, requires a paradigm shift in science assessment from the…

Advancements in technology and computer-based testing has allowed for greater flexibility in assessing examinee knowledge on large-scale, high-stakes assessments. Through computer-based delivery, cognitive ability and skills can be effectively assessed cost-efficiently and measure domains that are difficult or even impossible to measure with…

In automated essay scoring (AES), scores are automatically assigned to essays as an alternative to grading by humans. Traditional AES typically relies on handcrafted features, whereas recent studies have proposed AES models based on deep neural networks to obviate the need for feature engineering. Those AES models generally require training on a…

Background: Digital-first assessments leverage the affordances of technology in all elements of the assessment process--from design and development to score reporting and evaluation to create test taker-centric assessments. Objectives: The goal of this paper is to describe the engineering, machine learning, and psychometric processes and…

In April 2021, The Association for Assessment and Research in Counseling Executive Council commissioned a time-referenced task group to revise the Responsibilities of Users of Standardized Tests (RUST) Statement (3rd edition) published by the Association for Assessment in Counseling (AAC) in 2003. The task group developed a work plan to implement…

Researchers often develop instruments using correctness scores (and a variety of theories and techniques, such as Item Response Theory) for validation and scoring. Less frequently, observations of children's strategies are incorporated into the design, development, and application of assessments. We conducted individual interviews of 833…